Connecting to Microsoft OneDrive

For information on the available WHL files for supported environments, and how to install the appropriate file for your Python distribution, see Package Installation.

For information on the module to import, and how to configure the necessary connection properties in a connection string, see Establishing a Connection.

Other available connection properties can be used to configure other aspects of the connector capabilities.

Python Version Support

The CData Python Connector for Microsoft OneDrive can be installed and used in Python 3.10 or newer.

Microsoft OneDrive Version Support

Microsoft OneDrive and OneDrive for Business accounts are supported via the Microsoft Graph API v1.0.

See Also

• Using the Connector: Establish connections and query Microsoft OneDrive through Python code.
• From SQLAlchemy: Use SQLAlchemy to establish a connection with dialect URL, and interact with Microsoft OneDrive data using mapped classes and Sessions.

Dependencies

The Python connectors require that Python 3.10 or newer be installed.

Installation

The CData Python Connector for Microsoft OneDrive is available as a WHL file for Windows, Linux, and Mac. Each connector is built using the Python 3.10 Stable ABI (indicated by the abi3 tag in the filename), so a single wheel supports any Python 3.10 or newer installation — there is no need to match your exact Python minor version. Use the "pip install" command with the appropriate WHL file for your platform.

Windows:

pip install cdata_onedrive_connector-26.0.9655-cp310-abi3-win_amd64.whl

Linux:

pip install cdata_onedrive_connector-26.0.9655-cp310-abi3-linux_x86_64.whl

macOS:

pip install cdata_onedrive_connector-26.0.9655-cp310-abi3-macosx_12_0_arm64.whl

The macOS wheel supports arm64 (Apple Silicon) architectures only on macOS 12 and newer.

Regardless of the environment, certain distributions might require that the "pip3 install" command be used instead, to differentiate from a Python 2 distribution that might exist already. After installation, confirm whether the connector is successfully installed by running the "pip list" command. If "cdata_onedrive_connector" is present in the list output by the command, then the installation was successful.

Upgrading

When upgrading, "pip install" does not automatically clean up old JRE files. To avoid leftover files that could cause JVM errors, uninstall the previous version before installing the new one.

Licensing

After the installation is complete, a separate step is needed to activate a license for the connector. Among the CData assets in the distribution's site packages, there is an install-license tool that activates this license. From within the distribution's site-packages folder, after navigating to the "cdata/installlic_onedrive" folder, simply use a command like the below to activate the license. Omitting the <key> argument activates a trial license:

• Windows:
  

  ./install-license.exe <key>

• Linux / Mac:
  

  ./install-license.sh <key>

Sometimes, file access issues may cause pip to install the connector in a fallback file path that is not the python distribution's main or primary site-packages location. This can make it difficult to find where the connector was installed, and from there, the license activator. In that event, this python script below will print out the full file path of the connector's native file. This file will be stored in the mentioned cdata folder, from which the installlic_onedrive folder is trivial to find:

import os
import cdata.onedrive
path = os.path.abspath(cdata.onedrive.__file__)
print(path)

Uninstallation

If the connector needs to be uninstalled for any reason, do so by running the pip uninstall command, as in the example below:

pip uninstall cdata-onedrive-connector

The objects available within our connector are accessible from the "cdata.onedrive" module. To use the module's objects directly:

1. Import the module as follows:
   

   import cdata.onedrive as mod

2. To establish a connection string, call the connect() method from the connector object using an appropriate connection string, such as:
   

   mod.connect("InitiateOAuth=GETANDREFRESH;OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;CallbackURL=http://localhost:33333;")

Authenticating to Microsoft OneDrive

Microsoft OneDrive uses the OAuth authentication standard. To authenticate using OAuth, you will need to create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties.

Entra ID (Azure AD)

Note: Microsoft has rebranded Azure AD as Entra ID. In topics that require the user to interact with the Entra ID Admin site, we use the same names Microsoft does. However, there are still CData connection properties whose names or values reference "Azure AD".

Microsoft Entra ID is a multi-tenant, cloud-based identity and access management platform. It supports OAuth-based authentication flows that enable the driver to access Microsoft OneDrive endpoints securely.

Authentication to Entra ID via a web application always requires that you first create and register a custom OAuth application. This enables your application to define its own redirect URI, manage credential scope, and comply with organization-specific security policies.

For full instructions on how to create and register a custom OAuth application, see Creating an Entra ID (Azure AD) Application.

After setting AuthScheme to AzureAD, the steps to authenticate vary, depending on the environment. For details on how to connect from desktop applications, web-based workflows, or headless systems, see the following sections.

Desktop Applications

You can authenticate from a desktop application using either the driver's embedded OAuth application or a custom OAuth application registered in Microsoft Entra ID.

Option 1: Use the Embedded OAuth Application

This is a pre-registered application, included with the driver. It simplifies setup and eliminates the need to register your own credentials and is ideal for development environments, single-user tools, or any setup where quick and easy authentication is preferred.

Set the following connection properties:

• AuthScheme: AzureAD
• InitiateOAuth:
  • GETANDREFRESH – Use for the initial login. Launches the login page and saves tokens.
  • REFRESH – Use this setting when you have already obtained valid access and refresh tokens. Reuses stored tokens without prompting the user again.

When you connect, the driver opens the Microsoft Entra sign-in page in your default browser. After signing in and granting access, the driver retrieves the access and refresh tokens and saves them to the path specified by OAuthSettingsLocation.

Option 2: Use a Custom OAuth Application

If your organization requires more control, such as managing security policies, redirect URIs, or application branding, you can instead register a custom OAuth application in Microsoft Entra ID and provide its values during connection.

During registration, record the following values:

• OAuthClientId: The client Id that was generated when you registered your custom OAuth application.
• OAuthClientSecret: The client secret that was that was generated when you registered your custom OAuth application.
• CallbackURL: A redirect URI you defined during application registration.

For full instructions on how to register a custom OAuth application and configure redirect URIs, see Creating an Entra ID (Azure AD) Application.

Set the following connection properties:

• AuthScheme: AzureAD
• InitiateOAuth:
  • GETANDREFRESH – Use for the initial login. Launches the login page and saves tokens.
  • REFRESH – Use this setting when you have already obtained valid access and refresh tokens. Reuses stored tokens without prompting the user again.
• OAuthClientId: The client Id that was generated when you registered your custom OAuth application.
• OAuthClientSecret: The client secret that was generated when you registered your custom OAuth application.
• CallbackURL: A redirect URI you defined during application registration.

After authentication, tokens are saved to OAuthSettingsLocation. These values persist across sessions and are used to automatically refresh the access token when it expires, so you don't need to log in again on future connections.

Web Applications

To authenticate from a web application, you must register a custom OAuth application in Microsoft Entra ID (formerly Azure Active Directory). Embedded OAuth apps are not supported in this context because web-based flows require a registered redirect URI and centralized credential management.

This approach is designed for hosted, multi-user environments where access must be delegated through a secure, standards-compliant OAuth workflow. It gives your organization control over the OAuth client, redirect URI, branding, and permissions scope.

Before you begin: Register a custom OAuth application in the Azure portal. During registration, collect the following values:

• OAuthClientId: The client Id that was generated when you registered your custom OAuth application.
• OAuthClientSecret: The client secret that was generated when you registered your custom OAuth application.
• CallbackURL: A redirect URI you defined during application registration.

For full instructions on how to register a custom OAuth application and configure redirect URIs, see Creating an Entra ID (Azure AD) Application.

To authenticate using AzureAD in a web application, configure the following connection properties:

• AuthScheme: AzureAD
• InitiateOAuth: OFF – Disables automatic login prompts.
• OAuthClientId: The client Id that was generated when you registered your custom OAuth application.
• OAuthClientSecret: The client secret that was generated when you registered your custom OAuth application.
• CallbackURL: A redirect URI you defined during application registration.

Because web applications typically manage OAuth flows manually on the server-side, InitiateOAuth must be set to OFF. This allows you to explicitly control when and how tokens are retrieved and exchanged using stored procedures.

After configuring these properties, follow the steps below to obtain and exchange OAuth tokens:

1. Call the GetOAuthAuthorizationURL stored procedure:
   • CallbackURL: Set to your registered redirect URI
2. Open the returned URL in a browser. Sign in with a Microsoft Entra ID account and grant access.
3. After signing in, you are redirected to your CallbackURL with a code parameter in the query string.
4. Extract the code and pass it to the GetOAuthAccessToken stored procedure:
   • AuthMode: WEB
   • Verifier: The authorization code from the CallbackURL
5. The procedure returns:
   • OAuthAccessToken: Used for authentication.
   • OAuthRefreshToken: Used to refresh the access token.
   • ExpiresIn: The lifetime of the access token in seconds.

To enable automatic token refresh, configure the following connection properties:

• InitiateOAuth: REFRESH
• OAuthRefreshToken: Your previously obtained refresh token

When InitiateOAuth is set to REFRESH, the driver uses the provided refresh token to request a new access token automatically.

After a successful connection, the driver saves the updated access and refresh tokens to the file specified by OAuthSettingsLocation.

You only need to repeat the full OAuth authorization flow if the refresh token expires, is revoked, or becomes invalid.

For more background on OAuth flows in Microsoft Entra ID, see Microsoft Entra Authentication Overview.

Headless Machines

Headless environments like CI/CD pipelines, background services, or server-based integrations do not have an interactive browser. To authenticate using AzureAD, you must complete the OAuth flow on a separate device with a browser and transfer the authentication result to the headless system.

Setup options:

• Obtain and exchange a verifier code
  • Use another device to sign in and retrieve a verifier code, which the headless system uses to request tokens.
• Transfer an OAuth settings file
  • Authenticate on another device, then copy the stored token file to the headless environment.

Using a Verifier Code

1. On a device with a browser:
   • If using a custom OAuth app, set the following properties:
     • InitiateOAuth: OFF
     • OAuthClientId: The client Id that was generated when you registered your custom OAuth application.
     • OAuthClientSecret: The client secret that was generated when you registered your custom OAuth application.
   • Call the GetOAuthAuthorizationURL stored procedure to generate a sign-in URL.
   • Open the returned URL in a browser. Sign in and grant permissions to the driver. You are redirected to the callback URL, which contains the verifier code.
   • After signing in, save the value of the code parameter from the redirect URL. You will use this later to set the OAuthVerifier connection property.
2. On the headless machine:
   • Set the following properties:
     • AuthScheme: AzureAD
     • InitiateOAuth: REFRESH
     • OAuthVerifier: The verifier code you saved.
     • OAuthSettingsLocation: The path of the file that holds the OAuth token values.
     • For custom applications:
       • OAuthClientId: The client Id that was generated when you registered your custom OAuth application.
       • OAuthClientSecret: The client secret that was generated when you registered your custom OAuth application.
   • After tokens are saved, reuse them by setting:
     • InitiateOAuth: REFRESH
     • OAuthSettingsLocation: Make sure this location grants read and write permissions to the driver to enable the automatic refreshing of the access token.
     • For custom applications:
       • OAuthClientId: The client Id that was generated when you registered your custom OAuth application.
       • OAuthClientSecret: The client secret that was generated when you registered your custom OAuth application.

Transferring OAuth Settings

1. On a device with a browser:
   • Connect using the instructions in the Desktop Applications section.
   • After connecting, tokens are saved to the file path in OAuthSettingsLocation. The default filename is OAuthSettings.txt.

2. On the headless machine:
   • Copy the OAuth settings file to the machine.
   • Set the following properties:
     • AuthScheme: AzureAD
     • InitiateOAuth: REFRESH
     • OAuthSettingsLocation: Make sure this location grants read and write permissions to the driver to enable the automatic refreshing of the access token.
     • For custom applications:
       • OAuthClientId: The client Id that was generated when you registered your custom OAuth application.
       • OAuthClientSecret: The client secret that was generated when you registered your custom OAuth application.

After setup, the driver uses the stored tokens to refresh the access token automatically, no browser or manual login is required.

Azure Service Principal

The authentication as an Azure Service Principal is handled via the OAuth Client Credentials flow. It does not involve direct user authentication. Instead, credentials are created for just the application itself. All tasks taken by the application are done without a default user context, but based on the assigned roles. The application access to the resources is controlled through the assigned roles' permissions.

Create an AzureAD App and an Azure Service Principal

When authenticating using an Azure Service Principal, you must create and register an Azure AD application with an Azure AD tenant. See Creating an Entra ID (Azure AD) Application for more details.

In your App Registration in portal.azure.com, navigate to API Permissions and select the Microsoft Graph permissions. There are two distinct sets of permissions: Delegated permissions and Application permissions. The permissions used during client credential authentication are under Application Permissions.

Assign a role to the application

To access resources in your subscription, you must assign a role to the application.

1. Open the Subscriptions page by searching and selecting the Subscriptions service from the search bar.
2. Select the subscription to assign the application to.
3. Open the Access control (IAM) and select Add > Add role assignment to open the Add role assignment page.
4. Select Owner as the role to assign to your created Azure AD app.

Complete the Authentication Choose whether to use a client secret or a certificate and follow the relevant steps below.

Client Secret

Set these connection properties:

• AuthScheme: AzureServicePrincipal to use a client secret.
• InitiateOAuth: GETANDREFRESH. You can use InitiateOAuth to avoid repeating the OAuth exchange and manually setting the OAuthAccessToken.
• AzureTenant: The tenant you want to connect to.
• OAuthClientId: The client Id in your application settings.
• OAuthClientSecret: The client secret in your application settings.

Certificate

Set these connection properties:

• AuthScheme: AzureServicePrincipalCert to use a certificate.
• InitiateOAuth: GETANDREFRESH. You can use InitiateOAuth to avoid repeating the OAuth exchange and manually setting the OAuthAccessToken.
• AzureTenant: The tenant you want to connect to.
• OAuthJWTCert: The JWT Certificate store.
• OAuthJWTCertType: The type of the certificate store specified by OAuthJWTCert.

You are now ready to connect. Authentication with client credentials takes place automatically like any other connection, except there is no window opened prompting the user. Because there is no user context, there is no need for a browser popup. Connections take place and are handled internally.

Managed Service Identity (MSI)

If you are running Microsoft OneDrive on an Azure VM and want to automatically obtain Managed Service Identity (MSI) credentials to connect, set AuthScheme to AzureMSI.

User-Managed Identities

To obtain a token for a managed identity, use the OAuthClientId property to specify the managed identity's client_id.

If your VM has multiple user-assigned managed identities, you must also specify OAuthClientId.

Java Native Interface (JNI) is a standard programming interface for writing Java native methods and embedding the Java virtual machine into native applications.

The connector leverages the JNI for improved performance on Mac and Linux.

Configure the Config INI File

The Linux and Mac editions of the Microsoft OneDrive python connector are configured with an ini file. This file is used to set several parameters, including JNI behavior. This file is to be located in:

{path_to_distribution_site-packages}/cdata/config.ini

Ensure that any configuration properties you set in the ini file fall under the following section name (adjust the 311 number if you are using an different python version from 3.11):

• For Linux:
  

  [onedrive.cpython-311-x86_64-linux-gnu.so]

• For Mac:
  

  [onedrive.cpython-311-darwin.so]

Configure the JNI connector's behavior by editing the properties in the connector's config.ini file. The connector can be configured as follows:

• LOGFILE: Set this the same way as the CDATA_LOGFILE envrionment variable below.
• JAVA_HOME: Configure the path to the JVM library location used to launch the JVM.
• CLASS_PATH: Use a colon-separated list to configure the paths to the third-party jar libraries.

Configure Environment Variables

Additionally, set the following environment variables:

• CDATA_JAVA_HOME: Configure the path to the JVM library location used to launch the JVM.
• CDATA_JVM_OPTIONS: Place JVM options here.
• CDATA_LOGFILE: Set this in the following scheme: <SCHEME>://<TAG>[|<LEVEL>]
  • SCHEME: The options are STDOUT, FILE.
    • STDOUT: Both the native wrapper and odbc core log into stdout. The Logfile and Verbosity properties can override the behavior of ODBC core.
    • FILE: The native wrapper logs into <FILENAME> while the odbc core logs into <FILENAME>.driver.log. The Logfile and Verbosity properties can override the behavior of ODBC core.
  • TAG
    • For STDOUT, set this to 1. For FILE, set this to the filename.
  • LEVEL
    • Set to one of: FATAL | ERROR | WARNING | INFO | DEBUG

The following are some examples of this syntax:

• STDOUT://1|DEBUG
• FILE:///tmp/my_py.log|DEBUG

Custom Logger

The Python connector supports a custom logging mechanism for redirecting log output to any destination, such as a cloud storage service or logging framework. Use setCustomLoggerFactory() to register a factory function that creates a logger instance for each connection.

The factory function receives the context string from the Logfile connection property (the portion after CUSTOM://) and must return an object with a writeLog(verbosity, message) method.

To enable custom logging:

1. Call setCustomLoggerFactory() with your factory function before opening connections.
2. Set Logfile to CUSTOM:// followed by a context string to identify the connection.
3. Set Verbosity to the desired log level.

The following example demonstrates a custom logger factory that creates a separate logger instance per connection:

import cdata.onedrive as mod
import time

class MyLogger:
    def __init__(self, loggerId):
        self.loggerId = loggerId
    def writeLog(self, verbosity, message):
        print("[MyLogger " + self.loggerId + "] " + message)

def createLogger(context):
    return MyLogger(context[len("MyLoggerId="):])

mod.setCustomLoggerFactory(createLogger)

conn1 = mod.connect("...;Logfile=CUSTOM://MyLoggerId=1;Verbosity=2;")
# do something with conn1
time.sleep(1)  # Wait for logs to flush from conn1

conn2 = mod.connect("...;Logfile=CUSTOM://MyLoggerId=2;Verbosity=2;")
# do something with conn2
time.sleep(1)  # Wait for logs to flush from conn2

Creating an Entra ID (Azure AD) Application

Note: Microsoft has rebranded Azure AD as Entra ID. In topics that require the user to interact with the Entra ID Admin site, we use the same names Microsoft does. However, there are still CData connection properties whose names or values reference "Azure AD".

Microsoft OneDrive supports OAuth-based authentication using Microsoft Entra ID. If you will connect via a web application and want to authenticate via Entra ID, you must first register a custom OAuth application in the Entra Admin Center, as described below.

If you will connect via a desktop application or headless machine, you can authenticate using Microsoft OneDrive's built-in embedded application credentials, which use CData branding. However, custom OAuth applications are also compatible with desktop and headless authentication flows, and may be preferable for production deployments or environments requiring strict policy control.

Registering the Application

To register an OAuth application in Microsoft Entra ID, follow these steps:

1. Go to https://portal.azure.com.
2. In the left-hand navigation pane, select Microsoft Entra ID > App registrations.
3. Click New registration.
4. Enter a name for the application.
5. Specify the types of accounts this application should support:
   • For private-use applications, select Accounts in this organization directory only.
   • For distributed applications, select one of the multi-tenant options.

   Note: If you select Accounts in this organizational directory only, when you connect with CData Python Connector for Microsoft OneDrive, you must set AzureTenant to the tenant's ID (either GUID or verified domain). Otherwise, authentication will fail.

6. Set Select a platform to Web, and set the redirect URI to http://localhost:33333 (default), or use another URI appropriate for your deployment. When using a custom redirect URI set a CallbackURL connection property; in those cases, set it to match this URI exactly.
7. Click Register. The application management screen opens. Record these values for later use:
   • Application (client) ID is used for OAuthClientId
   • Directory (tenant) ID is used for AzureTenant
8. Go to Certificates & Secrets. Click New Client Secret, set the desired expiration, and save the generated value. This value will only be shown once — record it to use with OAuthClientSecret.

9. Select the Microsoft Graph API and then add the delegated permissions Files.ReadWrite.All or Files.Read.All. Hit the 'Grant admin consent' button afterwards for the new permissions to take effect.
10. To confirm, click Add permissions.

Creating a Service Principal App in Entra ID (Azure AD)

Note: Microsoft has rebranded Azure AD as Entra ID. In topics that require the user to interact with the Entra ID Admin site, we use the same names Microsoft does. However, there are still CData connection properties whose names or values reference "Azure AD".

Microsoft OneDrive supports Service Principal-based authentication, which is role-based. This means that the Service Principal's permissions are determined by the roles assigned to it. The roles specify what resources the Service Principal can access and which operations it can perform.

If you want to use a Service Principal to authenticate to Microsoft OneDrive, you must create a custom application in Microsoft Entra ID.

To enable Service Principal authentication:

• Confirm that you have permission to register applications and assign roles in your tenant.
• Register a new application and configure credentials and permissions in the Entra Admin Center.

Registering the Application

1. Go to https://portal.azure.com.
2. In the left-hand navigation pane, select Microsoft Entra ID > App registrations.
3. Click New registration.
4. Enter a name for the application.
5. Select the desired tenant setup. Since this custom application is for Service Principal use, choose Any Microsoft Entra ID tenant – Multitenant.

6. Click Register. The application management screen opens. Note the value in Application (client) ID as the OAuthClientId and the Directory (tenant) ID as the AzureTenant

7. Select the Microsoft Graph API and then add the delegated permissions Files.ReadWrite.All or Files.Read.All. Hit the 'Grant admin consent' button afterwards for the new permissions to take effect.
8. Navigate to Certificates & Secrets and define the application authentication type. Two types of authentication are available: certificate (recommended) or client secret
   • For creating a new client secret: In Certificates & Secrets, select New Client Secret for the application and specify its duration. After the client secret is saved, Microsoft OneDrive displays the key value. This value is displayed only once, so be sure to record it for future use. Use this value for the OAuthClientSecret

9. Navigate to Authentication and select the Access tokens option.
10. Save your changes.
11. If you specified permissions that require admin consent, you can grant them from the current tenant on the API Permissions page.

Granting Admin Consent

Some custom applications require administrative permissions to operate within a Microsoft Entra ID tenant. This is especially true for applications that use Application permissions, which allow the app to run without a signed-in user. Admin consent can be granted when creating a new application, by adding relevant permissions marked as "Admin Consent Required". Admin consent is also required to use Client Credentials in the authentication flow.

These permissions must be granted by an admin. To grant admin consent:

1. Log in to https://portal.azure.com with an administrator account.
2. Navigate to Microsoft Entra ID > App registrations and select your registered application.
3. Navigate to API permissions.
4. Review the permissions listed under Application permissions. Ensure the necessary API scopes are included for your use case.
5. Click Grant admin consent to approve the requested permissions.

This gives your application permissions on the tenant under which it was created.

Fine Tuning Data Access

• DirectoryRetrievalDepth: How many folders deep you want to get results for Folders, Files, SharedResources and Permissions tables.
• DriveId: The ID of the Drive that you want to use when getting data for tables Files, Folders, SharedResources and Permissions.
• ListGroupDrives: Indicates if you would like to list your group drives or not when querying the Drives table. Useful if you're using a OneDrive for Business account.

General Changes

Date	Version	Source	Category	Type	Description
2026-05-27	26.0.9643	General	Connection	Removed	Removed the deprecated ReplaceInvalidTypesWithNull connection property. Use the ReplaceInvalidValuesWithNull property instead.
2026-05-22	26.0.9638	Python		Removed	Remove support for Intel x64 architecture on macOS
2026-05-07	26.0.9623	General	Data Model	Added	Added the ColumnCapabilities column to the sys_tablecolumns system table. This column is a bit mask denoting the column's write capabilities.
2026-05-07	26.0.9623	Python		Changed	Updated embedded JRE to jre-17.0.19+10 (Linux x64 / MacOs x64).
2026-04-21	26.0.9607	Microsoft OneDrive	Data Model	Removed	Removed the SharedWithMeResources view.
2026-04-15	26.0.9601	General	Query Exec	Changed	String comparisons using GREATER, LESS, and CONTAINS operators are now case-insensitive by default.
2026-04-08	26.0.9594	Microsoft OneDrive	Security	Changed	TLS 1.3 is now supported by default for HTTP connections.
2026-04-01	26.0.9587	Microsoft OneDrive		Removed	Removed the BatchSize connection property.
2026-04-01	26.0.9587	Microsoft OneDrive	Data Model	Changed	When IncludeLinkedColumns is enabled, additional "Linked" columns are exposed. Previously, these were described as foreign key references, but they represent entire related rows. These columns no longer return reference values.
2026-02-20	25.0.9547	Microsoft OneDrive	Data Model	Added	Added the SensitivityLabels table. Added the GetFileSensitivityLabel stored procedure. This procedure retrieves all labels and label definitions applied to the specified OneDrive item.
2026-01-16	25.0.9512	Microsoft OneDrive		Added	Added the following connection properties: UserId, GroupId, DefaultUser, and DefaultGroups. Added support for filtering records by GroupId and UserId for all User and Group filterable tables.
2026-01-13	25.0.9509	General		Added	Added support for the REGEXP_REPLACE() string function.
2025-12-21	25.0.9486	Python		Added	Added support for custom loggers in Python connectors on Linux and macOS.
2025-12-05	25.0.9470	General		Added	Added support for the INSERT INTO SELECT statement, with driver-side execution for providers that do not support the operation natively.
2025-10-30	25.0.9434	Python		Changed	Updated embedded JRE to jre-17.0.17+10 (Linux x64 / MacOs x64).
2025-10-06	25.0.9410	General		Added	Support for parsing datetime formats using ".S" and ",S" for milliseconds and nanoseconds.
2025-09-12	25.0.9386	General		Added	Added the IsInsertable, IsUpdateable, and IsDeleteable columns to the sys_tables table.
2025-09-10	25.0.9384	General		Changed	All columns in statically defined Views are now reported as read-only.
2025-09-03	25.0.9377	General		Changed	Corrected the behavior when IN criteria with NULL values are used in the projection part. It now returns NULL instead of 0. For example, "NULL IN (1,2)" returns "NULL".
2025-09-01	25.0.9375	General		Added	Added support for using the CAST function with infinity values. This function can cast "inf" and "-inf" to DOUBLE, FLOAT, or REAL.
2025-08-21	25.0.9364	General		Changed	Report behavior change: Fixed inconsistent string value comparisons in non-table queries. For example, "SELECT 'A' = 'a'" previously returned false, but it now returns true.
2025-08-13	25.0.9356	General		Changed	Changed the maximum number of pages held in memory from 15 to 5 for the page providers to decrease heap usage.
2025-07-18	25.0.9330	Microsoft OneDrive		Removed	Removed the OAuthGrantType property. The grant type is now set implicitly through the 'AuthScheme' property. For example, you can use the 'OAuthPassword' AuthScheme instead of AuthScheme=OAuth with OAuthGrantType=Password.
2025-07-07	25.0.9319	Python		Removed	Removed the 32-bit version of Windows Python.
2025-07-04	25.0.9316	Microsoft OneDrive		Removed	Removed the UseIdURL connection property because it has been deprecated.
2025-07-02	25.0.9314	Python		Removed	Removed support for Python 3.9.
2025-06-25	25.0.9307	General		Removed	Removed the "ADLS Gen 1" value from the ConnectionType property.
2025-06-25	25.0.9307	Python		Added	Added support for Python 3.13 in Windows, Linux, and Mac editions.
2025-06-25	25.0.9307	Python		Removed	Removed support for Python 3.8 as it is no longer supported.
2025-06-20	25.0.9302	General		Added	Created the following functions: TEXT_ENCODE: encodes a string into a different charset (UTF8 → UTF7 and returns a binary array as the result). TEXT_DECODE: takes a binary array and decodes it back into a string when provided the charset. BASE64_ENCODE: takes a binary array and encodes it as a base64 string (varchar). BASE64_DECODE: takes a base 64-encoded string and decodes it into a binary array.
2025-06-20	25.0.9302	Microsoft OneDrive		Added	Added the following two new columns to the Files table: createdBy_user_email and lastModifiedBy_user_email.
2025-06-18	25.0.9300	General		Changed	The internal code for exception handling has been refactored. Exception messages returned during certain error conditions may now have different wording or formatting.
2025-06-17	25.0.9299	Microsoft OneDrive		Added	Added the SharedWithMeResources view.
2025-05-27	25.0.9278	General		Removed	Removed the "Proprietary" enum option from ProxyAuthscheme.
2025-05-12	25.0.9263	Python		Changed	Updated embedded JRE to jre-17.0.15+6 (Linux x64 / MacOS x64) and jre-17.0.15+6 (MacOS aarch64).
2025-03-27	25.0.9217	Microsoft OneDrive		Added	In tables/views whose corresponding OData entity is marked with hasStream:true in its API metadata responses, the "MediaReadLink" column is added to the table/view metadata. When present, this column displays the link to the OData entity's media stream.
2025-03-19	25.0.9209	Microsoft OneDrive		Added	Added the Groups and GroupMembers views.
2025-02-15	24.0.9177	General		Added	Added support for converting unsigned integer types to the nearest signed data type that has enough precision to hold the unsigned value.This is done for JDBC only because it does not have support for unsigned data types.
2024-11-27	24.0.9097	General		Added	Added ThreadId to LogModule output. Logfile lines now include the Thread ID associated with the action being performed.
2024-06-05	24.0.8922	Python		Added	Added support for Python 3.12.
2024-05-09	24.0.8895	General		Changed	The ROUND function previously did not accept negative precision values. That feature has now been restored.
2024-03-27	23.0.8852	Microsoft OneDrive		Added	Added a permanently boolean input attribute in the DeleteDocument stored procedure to decide whether to move the file to the Recycle bin or permanently delete it from the drive.
2024-03-15	23.0.8840	General		Added	Created a new SQL function called STRING_COMPARE that provides java's String.compare() ability to SQL queries. Returns a number representative of the compared value of two strings
2023-11-29	23.0.8733	General		Changed	The ROUND function doesn't accept the negative precision values anymore.
2023-11-29	23.0.8733	General		Changed	The returning types of the FDMonth, FDQuarter, FDWeek, LDMonth, LDQuarter, LDWeek functions are changed from Timestamp to Date. The return type of the ABS function will be consistent with the parameter value type.
2023-11-28	23.0.8732	General		Added	Added the HMACSHA256 formatter to allow for secrets to be decoded if it is in base64 format
2023-10-24	23.0.8697	Microsoft OneDrive		Changed	The default value for the hidden connection property IncludeReferenceColumn has changed to false and the ParentReference columns will no longer be list by default.
2023-10-05	23.0.8678	Microsoft OneDrive		Added	Added a new Stored procedure FetchAdditionalUserFields, which will have all the column supported by Users for a particular User.
2023-10-05	23.0.8678	Microsoft OneDrive		Changed	Updated the Users view, will include only the fields returned by default in the Users endpoint and selected columns are returned by specifying them in $select.
2023-08-29	23.0.8641	Python		Added	Added support for SQLAlchemy 2.0.
2023-08-28	23.0.8640	Microsoft OneDrive		Added	Added IncludeFoldersWithFiles connection property to add Folders in the Files view. Added ResourceType column in Files view to differentiate between Files and Folders.
2023-08-04	23.0.8616	Microsoft OneDrive		Added	Added AzureServicePrincipalCert as an AuthScheme option to enable authentication with a Certificate.
2023-06-20	23.0.8571	General		Added	Added the new sys_lastresultinfo system table.
2023-05-19	23.0.8539	Python		Added	Added support for Python 3.11 on Windows, Linux and Mac.
2023-05-16	23.0.8536	Python		Removed	Removed support for Python 3.7 on Windows and Linux
2023-04-25	23.0.8515	General		Removed	Removed support for the SELECT INTO CSV statement. The core code doesn't support it anymore.
2022-12-30	22.0.8399	Microsoft OneDrive		Added	Added publication_level column to the FileVersions view.
2022-12-14	22.0.8383	General		Changed	Added the Default column to the sys_procedureparameters table.
2022-12-13	22.0.8382	Microsoft OneDrive		Added	Added the RenameResource StoredProcedure to rename files.
2022-11-25	22.0.8364	Microsoft OneDrive		Added	Added the FileVersion view. Added UserId and Version attribute in DownloadFile StoredProcedure to download different file versions.
2022-11-15	22.0.8354	Python		Changed	Updated embedded JRE to jre8u345-b01(Linux x64 / MacOS x64) and jre-17.0.5+8(MacOS aarch64).
2022-10-11	22.0.8319	Microsoft OneDrive		Added	Added FileName as an input parameter to add the name of file to the input streams on the DownloadFile StoredProcedure. Added ContentStream as an input parameter to add the content to the input streams on the UploadFile StoredProcedure.
2022-09-30	22.0.8308	General		Changed	Added the IsPath column to the sys_procedureparameters table.
2022-05-24	22.0.8179	Microsoft OneDrive		Changed	Changed provider name to Microsoft OneDrive.
2022-05-18	22.0.8173	Python		Added	Added support for Python 3.10 on Windows, Linux, and Mac Added support for Python 3.9 on Mac Added support for Mac M1
2022-05-18	22.0.8173	Python		Removed	Removed support for Python 3.6 on Windows and Linux
2021-09-02	21.0.7915	General		Added	Added support for the STRING_SPLIT table-valued function in the CROSS APPLY clause.
2021-08-07	21.0.7889	General		Changed	Added the KeySeq column to the sys_foreignkeys table.
2021-08-06	21.0.7888	General		Changed	Added the new sys_primarykeys system table.
2021-07-23	21.0.7874	General		Changed	Updated the Literal Function Names for relative date/datetime functions. Previously, relative date/datetime functions resolved to a different value when used in the projection as opposed to the predicate. For example: SELECT LAST_MONTH() AS lm, Col FROM Table WHERE Col > LAST_MONTH(). Formerly, the two LAST_MONTH() methods would resolve to different datetimes. Now, they will match. As a replacement for the previous behavior, the relative date/datetime functions in the criteria may have an 'L' appended to them. For example: WHERE col > L_LAST_MONTH(). This will continue to resolve to the same values that were previously calculated in the criteria. Note that the "L_" prefix will only work in the predicate - it not available for the projection.
2021-06-05	21.0.7826	Microsoft OneDrive		Added	Added support for the AzureServicePrinciple authentication scheme. Added support to authenticate submitting JWT certs instead of the OAuthClientSecret for the AzureServicePrinciple and AzureAD authentication schemes.
2021-04-23	21.0.7783	General		Changed	Updated how display sizes are determined for varchar primary key and foreign key columns so they will match the reported length of the column.
2021-04-16	21.0.7776	General		Changed	Reduced the length to 255 for varchar primary key and foreign key columns.
2021-04-16	21.0.7776	General		Changed	Updated implicit and metadata caching to improve performance and support for multiple connections. Old metadata caches are not compatible - you need to generate new metadata caches if you are currently using CacheMetadata.
2021-04-16	21.0.7776	General		Changed	Updated index naming convention to avoid duplicates.
2021-04-01	21.0.7761	Microsoft OneDrive		Deprecated	The Tenant connection property is deprecated and replaced with AzureTenant to match our other products.

This section provides a walk-through for writing Microsoft OneDrive data access code in Python script.

For more information on the available data source entities and how to query them with SQL, see Data Model. For the SQL syntax, see SQL Compliance.

Connecting from Code

For information on how to deploy the connector and configure the connection to Microsoft OneDrive, see Package Installation and Establishing a Connection.

For information on how to connect with the onedrive.connector module and its related classes, see Connecting.

Executing SQL

The connection's cursor object is used to directly execute SQL queries. For information on how to execute SELECT statements and process the returned result sets, see Querying Data.

Executing Stored Procedures

You can call stored procedures by using the EXECUTE statement. For further information, see Calling Stored Procedures.

Connecting with the cdata.onedrive Module:

The connector's module is used directly to establish a connection with the data source. It does this by using a connection string as its argument. For example:

import cdata.onedrive as mod
conn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;CallbackURL=http://localhost:33333;")

Once the connection is created, you can use it to execute subsequent SQL queries.

After connecting as described in Connecting, you can use the open connection to execute SQL statements.

Executing Queries

To execute SQL statements that return data, use the execute() method. Once a query is executed, the result set is fetched from the cursor. This result set can then be iterated over to process the records individually.

For example:

cur = conn.execute("SELECT Id, Name FROM Files")
rs = cur.fetchall()
for row in rs:
	print(row)

Parameterized Queries

Various Python collections, such as arrays and tuples, can act as additional arguments for the execute() method. This enables you to parameterize the queries executed and help to prevent SQL Injection.

For example:

cmd = "SELECT Id, Name FROM Files WHERE Id = ?"
params = ["Jq74mCczmFXk1tC10GB"]
cur = conn.execute(cmd, params)
rs = cur.fetchall()
for row in rs:
	print(row)

You can execute stored procedures using either the execute() or callproc() method of the connection.

Calling Stored Procedures Using Execute()

When you call stored procedures by issuing EXECUTE commands, the stored procedure arguments are parameterized. For example:

cmd = "EXECUTE DownloadResource ResourceId = ?"
params = ["B2Y1KS6A8873OCP2!152"]
conn.execute(cmd, params)

Calling Stored Procedures Using Callproc()

When you call stored procedured by issuing the callproc() method, the stored procedure arguments are a procedure name and a list of parameters. For example:

cur = conn.cursor()
params = ["B2Y1KS6A8873OCP2!152"]
cur.callproc("DownloadResource", params)

The connector is integrated with other tools and packages within Python.

Python Integration Guides

The following sections show how to create and use connections with the connector in common packages in Python:

• From SQLAlchemy
• From Pandas
• From Matplotlib
• From Petl

Complete List of Microsoft OneDrive Integration Quickstarts

For information on connecting from other applications, see Microsoft OneDrive integration guides.

The CData Python Connector for Microsoft OneDrive includes a Dialect class that enables integration with SQLAlchemy. Bear in mind that several aspects of connector functionality are not currently supported in SQLAlchemy 2.0 or above. If necessary, downgrade SQLAlchemy to version 1.4 or 1.3 before using this connector.

The following sections detail various aspects of this integration:

Connecting From SQLAlchemy

To construct a URL with which SQLAlchemy loads and uses the appropriate connector automatically, see Connecting

Reflecting Metadata With SQLAlchemy

To learn how to model Microsoft OneDrive tables with mapped classes, see Reflecting Metadata.

Querying Data From SQLAlchemy

To learn how to use mapped classes to query the associated tables, see Querying Data.

Connecting With a Dialect URL

Establishing a connection using SQLAlchemy requires a specific URL format.

from sqlalchemy import create_engine
engine = create_engine("onedrive:///?InitiateOAuth=GETANDREFRESH;OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;CallbackURL=http://localhost:33333;")

For SQLAlchemy 2.0, the dialect name is onedrive_2. To establish a connection, use the following URL format:

from sqlalchemy import create_engine
engine = create_engine("onedrive_2:///?InitiateOAuth=GETANDREFRESH;OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;CallbackURL=http://localhost:33333;")

SQLAlchemy can act as an Object-relational Map (ORM). This enables you to treat records of a database table as instantiable records. To leverage this functionality, you must reflect the underlying metadata in one of the following ways.

Note: The following examples employ SQLAlchemy 1.4.

Modeling Data Using a Mapping Class

Use "sqlalchemy.ext.declarative.declarative_base" to declare a mapping class for the table you wish to model in the ORM. A known table in the data model is modeled either partially or completely, as shown in the following example:

from sqlalchemy.ext.declarative import declarative_base
Base = declarative_base()
class Files(Base):
	__tablename__ = "Files"
	Id = Column(String, primary_key=True)
	Id = Column(String)
	Name = Column(String)

Automatically Reflecting Metadata

Rather than mapping tables manually, SQLAlchemy can discover the metadata for one or more tables automatically. To accomplish this across the entire data model, use automap_base:

from sqlalchemy import MetaData
from sqlalchemy.ext.automap import automap_base
meta = MetaData()
abase = automap_base(metadata=meta)
abase.prepare(autoload_with=engine)
Files = abase.classes.Files

You can also reflect a single table with an inspector. When reflecting this way, providing a list of specific columns to map is optional:

from sqlalchemy import MetaData, Table
from sqlalchemy import inspect
meta = MetaData()
insp = inspect(engine)
Files_table = Table("Files", meta)
insp.reflect_table(Files_table, ["Id","Name"])

After you use the steps in Connecting to connect, and use one of the methods in Reflecting Metadata to reflect some of the metadata, you can use a session object to query data.

Querying Data Using the Query Method

If the mapping class has been prepared, use it with a session object to query the data source. After binding the engine to the session, provide the mapping class to the session's query method.

For example:

engine = create_engine("onedrive:///?InitiateOAuth=GETANDREFRESH;OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;CallbackURL=http://localhost:33333;")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Files).filter_by(Id="Jq74mCczmFXk1tC10GB"):
	print("Id: ", instance.Id)
	print("Id: ", instance.Id)
	print("Name: ", instance.Name)
	print("---------")

Querying Data Using the Execute Method

The session object can also run the query with the execute() method alongside the appropriate Table object. Assuming you have an active session, the following is just as viable:

Files_table = Files.metadata.tables["Files"]
for instance in session.execute(Files_table.select().where(Files_table.c.Id == "Jq74mCczmFXk1tC10GB")):
	print("Id: ", instance.Id)
	print("FullName: ", instance.Name)
	print("City: ", instance.BillingCity)
	print("---------")

Implicit Joining

If mapped classes of related Microsoft OneDrive objects have a singular foreign key relationship, the classes are implicitly joined. After importing the necessary objects, a relationship is established between your two mapped classes, as in the example below:

from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, String, Integer, DateTime, ForeignKey
from sqlalchemy.orm import sessionmaker, relationship

Base = declarative_base()
class Contact(Base):
	__tablename__ = "Contact"
	Id = Column(Integer, primary_key=True)
	Name = Column(String)
	Email = Column(String)
	BirthDate = Column(DateTime)
	AccountId = Column(String, ForeignKey("Account.Id"))
	Account_Link = relationship("Account", back_populates="Contact_Link")

class Account(Base):
	__tablename__ = "Account"
	Id = Column(String, primary_key=True)
	Name = Column(String)
	BillingCity = Column(String)
	NumberOfEmployees = Column(Integer)
	Contact_Link = relationship("Contact", order_by=Contact.Id, back_populates="Account_Link")

Once the relationship is established, the tables are queried simultaneously using the session's query() method. For example:

rs = session.query(Account, Contact).filter(Account.Id == Contact.AccountId)
for Ac, Ct in rs:
  print("AccountId: ", Ac.Id)
  print("AccountName: ", Ac.Name)
  print("ContactId: ", Ct.Id)
  print("ContactName: ", Ct.Name)

Other Join Forms

In situations where mapped classes have either no foreign keys or multiple foreign keys, you may need different forms of the JOIN query to accommodate them. Using the earlier classes as examples, the following JOIN queries are possible as well:

• Explicit condition (necessary if there are no foreign keys in your mapped classes):
  

  rs = session.query(Account, Contact).join(Contact, Account.Id == Contact.AccountId)
  for Ac, Ct in rs:

• Left-to-right relationship:
  

  rs = session.query(Account, Contact).join(Account.Contact_Link)
  for Ac, Ct in rs:

• Left-to-right relationship with explicit target:
  

  rs = session.query(Account, Contact).join(Contact, Account.Contact_Link)
  for Ac, Ct in rs:

• String form of a left-to-right relationship:
  

  rs = session.query(Account, Contact).join("Contact_Link")
  for Ac, Ct in rs:

SQLAlchemy ORM also exposes support for other clauses in SQL, such as ORDER BY, GROUP BY, LIMIT, and OFFSET. All of these are supported by this connector:

ORDER BY

The following example sorts by a specified column using the session object's query() method:

rs = session.query(Files).order_by(Files.Size)
for instance in rs:
	print("Id: ", instance.Id)
	print("Id: ", instance.Id)
	print("Name: ", instance.Name)
	print("---------")

You can also use the session object's execute() method perform an ORDER BY. For example:

rs = session.execute(Files_table.select().order_by(Files_table.c.Size))
for instance in rs:

GROUP BY

The following example uses the session object's query() method to group records with a specified column:

rs = session.query(func.count(Files.Id).label("CustomCount"), Files.Id).group_by(Files.Id)
for instance in rs:
	print("Count: ", instance.CustomCount)
	print("Id: ", instance.Id)
	print("---------")

You can also use the session object's execute() method to perform a GROUP BY:

rs = session.execute(Files_table.select().with_only_columns([func.count(Files_table.c.Id).label("CustomCount"), Files_table.c.Id]).group_by(Files_table.c.Id))
for instance in rs:

LIMIT and OFFSET

The following example uses the session object's query() method to skip the first 100 records and fetch the following 25:

rs = session.query(Files).limit(25).offset(100)
for instance in rs:
	print("Id: ", instance.Id)
	print("Id: ", instance.Id)
	print("Name: ", instance.Name)
	print("---------")

You can also use the session object's execute() method to set a LIMIT or OFFSET:

rs = session.execute(Files_table.select().limit(25).offset(100))
for instance in rs:

Certain aggregate functions can also be used within SQLAlchemy by using the func module.

To import this module, execute:

from sqlalchemy.sql import func

Once func is imported, the following aggregate functions are available:

COUNT

The following example counts the number of records in a set of groups using the session object's query() method.

rs = session.query(func.count(Files.Id).label("CustomCount"), Files.Id).group_by(Files.Id)
for instance in rs:
	print("Count: ", instance.CustomCount)
	print("Id: ", instance.Id)
	print("---------")

You can also execute COUNT using the session object's execute() method:

rs = session.execute(Files_table.select().with_only_columns([func.count(Files_table.c.Id).label("CustomCount"), Files_table.c.Id])group_by(Files_table.c.Id))
for instance in rs:

SUM

This example calculates the cumulative amount of a numeric column in a set of groups.

rs = session.query(func.sum(Files.Size).label("CustomSum"), Files.Id).group_by(Files.Id)
for instance in rs:
	print("Sum: ", instance.CustomSum)
	print("Id: ", instance.Id)
	print("---------")

You can also invoke SUM using the session object's execute() method.

rs = session.execute(Files_table.select().with_only_columns([func.sum(Files_table.c.Size).label("CustomSum"), Files_table.c.Id]).group_by(Files_table.c.Id))
for instance in rs:

AVG

This example uses the session object's query() method to calculate the average amount of a numeric column in a set of groups:

rs = session.query(func.avg(Files.Size).label("CustomAvg"), Files.Id).group_by(Files.Id)
for instance in rs:
	print("Avg: ", instance.CustomAvg)
	print("Id: ", instance.Id)
	print("---------")

You can also use the session object's execute() method to invoke AVG:

rs = session.execute(Files_table.select().with_only_columns([func.avg(Files_table.c.Size).label("CustomAvg"), Files_table.c.Id]).group_by(Files_table.c.Id))
for instance in rs:

MAX and MIN

This example finds the maximum value and minimum value of a numeric column in a set of groups.

rs = session.query(func.max(Files.Size).label("CustomMax"), func.min(Files.Size).label("CustomMin"), Files.Id).group_by(Files.Id)
for instance in rs:
	print("Max: ", instance.CustomMax)
	print("Min: ", instance.CustomMin)
	print("Id: ", instance.Id)
	print("---------")

You can also use the session object's execute() method to invoke MAX and MIN:

rs = session.execute(Files_table.select().with_only_columns([func.max(Files_table.c.Size).label("CustomMax"), func.min(Files_table.c.Size).label("CustomMin"), Files_table.c.Id]).group_by(Files_table.c.Id))
for instance in rs:

When combined with the connector, Pandas can be used to generate data frames that contain your Microsoft OneDrive data. Once created, a data frame can be passed to various other Python packages.

Connecting

Pandas relies on an SQLAlchemy engine to execute queries. Before you can use Pandas you must import it:

import pandas as pd
from sqlalchemy import create_engine
engine = create_engine("onedrive:///?InitiateOAuth=GETANDREFRESH;OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;CallbackURL=http://localhost:33333;")

Querying Data

In Pandas, SELECT queries are provided in a call to the read_sql() method, alongside a relevant connection object. Pandas executes the query on that connection, and returns the results in the form of a data frame, which can be used for a variety of purposes.

df = pd.read_sql("""
	SELECT
	   Id,
	   Name,
     $exNumericCol;
	FROM Files;""", engine)
print(df)

Matplotlib contains a number of tools that can graphically model Microsoft OneDrive data after being fed a data frame From Pandas.

Using PyPlot

Before any Matplotlib tool, such as pyplot, can be used, it must be imported:

from matplotlib import pyplot as plt

Once a Pandas data frame is obtained, it can be used to create a plot visualizing Microsoft OneDrive data. For example, the following plot generates and displays a bar graph relating Id and Size values:

df.plot(kind="bar", x="Id", y=["Size"])
plt.show()

The connector can be used to create ETL applications and pipelines for CSV data in Python using Petl.

Install Required Modules

Install the Petl modules using the pip utility.

pip install petl

Connecting

After you import the modules, including the CData Python Connector for Microsoft OneDrive, you can use the connector's connect function to create a connection using a valid Microsoft OneDrive connection string. If you prefer not to use a direct connection, you can use a SQLAlchemy engine.

import petl as etl
import cdata.onedrive as mod
cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;CallbackURL=http://localhost:33333;")

Extract, Transform, and Load the Microsoft OneDrive Data

Create a SQL query string and store the query results in a DataFrame.

sql = "SELECT	Id, Name FROM Files "
table1 = etl.fromdb(cnxn,sql)

Loading Data

With the query results stored in a DataFrame, you can load your data into any supported Petl destination. The following example loads the data into a CSV file.

etl.tocsv(table1,'output.csv')

The extension supports schema discovery by using SQL queries to available System Tables.

Using SQL

The following sections describe the discovery of metadata through several System Tables:

• Tables and Views
• Columns
• Procedures

The connector possesses system tables that are used to discover the tables and views available in the data model. Of these system tables, "sys_tables" and "sys_views" are used to fetch information about the available tables and views respectively:

Tables

import cdata.onedrive as mod
conn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;CallbackURL=http://localhost:33333;")
cur = conn.cursor()
cmd = "SELECT * FROM sys_tables"
cur.execute(cmd)
rs = cur.fetchall()
for row in rs:
	print(row)

Views

import cdata.onedrive as mod
conn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;CallbackURL=http://localhost:33333;")
cur = conn.cursor()
cmd = "SELECT * FROM sys_views"
cur.execute(cmd, params)
rs = cur.fetchall()
for row in rs:
	print(row)

The available columns for any given table are fetched from a system table called "sys_tablecolumns". A specific table name is provided in the WHERE criteria to restrict the table from which the column information is fetched:

import cdata.onedrive as mod
conn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;CallbackURL=http://localhost:33333;")
cur = conn.cursor()
cmd = "SELECT * FROM sys_tablecolumns WHERE TableName = 'Files'"
cur.execute(cmd)
rs = cur.fetchall()
for row in rs:
	print(row)

Procedures

A system table called "sys_procedures" is queried to obtain the available stored procedures that are executed:

import cdata.onedrive as mod
conn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;CallbackURL=http://localhost:33333;")
cur = conn.cursor()
cmd = "SELECT * FROM sys_procedures"
cur.execute(cmd)
rs = cur.fetchall()
for row in rs:
	print(row)

Parameters

The input parameters of any stored procedure are similarly obtained from the "sys_procedureparameters" system table:

import cdata.onedrive as mod
conn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;CallbackURL=http://localhost:33333;")
cur = conn.cursor()
cmd = "SELECT * FROM sys_procedureparameters WHERE ProcedureName = 'DownloadResource'"
cur.execute(cmd)
rs = cur.fetchall()
for row in rs:
	print(row)

This section details a selection of advanced features of the Microsoft OneDrive connector.

User Defined Views

The connector supports the use of user defined views, virtual tables whose contents are decided by a pre-configured user defined query. These views are useful when you cannot directly control queries being issued to the drivers. For an overview of creating and configuring custom views, see User Defined Views .

SSL Configuration

Use SSL Configuration to adjust how connector handles TLS/SSL certificate negotiations. You can choose from various certificate formats;. For further information, see the SSLServerCert property under "Connection String Options" .

Firewall and Proxy

Configure the connector for compliance with Firewall and Proxy, including Windows proxies and HTTP proxies. You can also set up tunnel connections.

Caching Data

Caching Data enables faster access to data and reduces the number of API calls, improving performance. The connector supports a simple caching model where multiple connections can also share the cache over time. When configuring the cache connection, you can specify automatic or explicit data caching.

Query Processing

The connector offloads as much of the SELECT statement processing as possible to Microsoft OneDrive and then processes the rest of the query in memory (client-side).

For further information, see Query Processing.

Logging

For an overview of configuration settings that can be used to refine CData logging, see Logging. Only two connection properties are required for basic logging, but there are numerous features that support more refined logging, which enables you to use the LogModules connection property to specify subsets of information to be logged.

Exception Handling

For an overview of how exceptions are reported and the components of an exception, see Exception Handling.

The CData Python Connector for Microsoft OneDrive supports the use of user defined views: user-defined virtual tables whose contents are decided by a preconfigured query. User defined views are useful in situations where you cannot directly control the query being issued to the driver; for example, when using the driver from a tool.

Use a user defined view to define predicates that are always applied. If you specify additional predicates in the query to the view, they are combined with the query already defined as part of the view.

There are two ways to create user defined views:

• Create a JSON-formatted configuration file defining the views you want.
• DDL statements.

Defining Views Using a Configuration File

User defined views are defined in a JSON-formatted configuration file called UserDefinedViews.json. The connector automatically detects the views specified in this file.

You can also have multiple view definitions and control them using the UserDefinedViews connection property. When you use this property, only the specified views are seen by the connector.

This user defined view configuration file is formatted so that each root element defines the name of a view, and includes a child element, called query, which contains the custom SQL query for the view.

For example:

{
	"MyView": {
		"query": "SELECT * FROM Files WHERE MyColumn = 'value'"
	},
	"MyView2": {
		"query": "SELECT * FROM MyTable WHERE Id IN (1,2,3)"
	}
}

Use the UserDefinedViews connection property to specify the location of your JSON configuration file. For example:

"UserDefinedViews", "C:\\Users\\yourusername\\Desktop\\tmp\\UserDefinedViews.json"

Defining Views Using DDL Statements

The connector is also capable of creating and altering the schema via DDL Statements such as CREATE LOCAL VIEW, ALTER LOCAL VIEW, and DROP LOCAL VIEW.

Create a View

To create a new view using DDL statements, provide the view name and query as follows:

CREATE LOCAL VIEW [MyViewName] AS SELECT * FROM Customers LIMIT 20;

If no JSON file exists, the above code creates one. The view is then created in the JSON configuration file and is now discoverable. The JSON file location is specified by the UserDefinedViews connection property.

Alter a View

To alter an existing view, provide the name of an existing view alongside the new query you would like to use instead:

ALTER LOCAL VIEW [MyViewName] AS SELECT * FROM Customers WHERE TimeModified > '3/1/2020';

The view is then updated in the JSON configuration file.

Drop a View

To drop an existing view, provide the name of an existing schema alongside the new query you would like to use instead.

DROP LOCAL VIEW [MyViewName]

This removes the view from the JSON configuration file. It can no longer be queried.

Schema for User Defined Views

In order to avoid a view's name clashing with an actual entity in the data model, user defined views are exposed in the UserViews schema by default. To change the name of the schema used for UserViews, reset the UserViewsSchemaName property.

Working with User Defined Views

For example, a SQL statement with a user defined view called UserViews.RCustomers only lists customers in Raleigh:

SELECT * FROM Customers WHERE City = 'Raleigh';

An example of a query to the driver:

SELECT * FROM UserViews.RCustomers WHERE Status = 'Active';

Resulting in the effective query to the source:

SELECT * FROM Customers WHERE City = 'Raleigh' AND Status = 'Active';

That is a very simple example of a query to a user defined view that is effectively a combination of the view query and the view definition. It is possible to compose these queries in much more complex patterns. All SQL operations are allowed in both queries and are combined when appropriate.

Customizing the SSL Configuration

By default, the connector attempts to negotiate TLS with the server. The server certificate is validated against the default system trusted certificate store. You can override how the certificate gets validated using the SSLServerCert connection property.

To specify another certificate, see the SSLServerCert connection property.

Connecting Through a Firewall or Proxy

HTTP Proxies

Note: The connector uses the system proxy settings by default, without further configuration needed. If you want to connect to other proxies, set ProxyAutoDetect to False and read further.

To authenticate to an HTTP proxy, set the following:

• ProxyServer: the hostname or IP address of the proxy server that you want to route HTTP traffic through.
• ProxyPort: the TCP port that the proxy server is running on.
• ProxyAuthScheme: the authentication method the connector uses when authenticating to the proxy server.
• ProxyUser: the username of a user account registered with the proxy server.
• ProxyPassword: the password associated with the ProxyUser.

Other Proxies

Set the following properties:

• To use a proxy-based firewall, set FirewallType, FirewallServer, and FirewallPort.
• To tunnel the connection, set FirewallType to TUNNEL.
• To authenticate, specify FirewallUser and FirewallPassword.
• To authenticate to a SOCKS proxy, additionally set FirewallType to SOCKS5.

Caching Data

Caching data provides several benefits, including faster access to data and reducing the number of API calls, which improve performance. The connector supports a simple caching model where multiple connections can also share the cache over time. You can enable and configure caching features by setting the necessary connection properties.

Contents

The sections in this chapter detail the connector's caching functionality and link to the corresponding connection properties, as well as SQL statements.

Configuring the Cache Connection

Configuring the Cache Connection describes the properties that you can set when configuring the cache database.

Caching Metadata

Caching Metadata describes the CacheMetadata property. This property determines whether or not to cache the table metadata to a file store.

Automatically Caching Data

Automatically Caching Data describes how the connector automatically refreshes the cache when the AutoCache property is set.

Explicitly Caching Data

Explicitly Caching Data describes how you can decide what data is stored in the cache and when it is updated.

Data Type Mapping

Data Type Mapping shows the mappings between the data types configured in the schema and the data types in the database.

Configuring the Caching Database

This section describes the properties for caching data to the persistent store of your choice.

CacheLocation

The CacheLocation property species the path to a file-system-based database. When caching is enabled, a file-system-based database is used by default. If CacheLocation is not specified, this database is stored at the path in Location. If neither of these connection properties are specified, the connector uses a platform-dependent default location.

CacheConnection

The CacheConnection property specifies a database driver and the connection string to the caching database.

CacheDriver and CacheProvider

Both the CacheDriver and CacheProvider properties are supported. Each specifies a database driver and the connection string to the caching database. CacheDriver is designed for Linux and MacOS; CacheProvider is Windows-based.

This section describes how to enable caching metadata and how to update the metadata cache.

Before being able to query data, the connector requires relevant metadata to be retrieved. By default, metadata is cached in memory and shared across connections. But if you want to persist across processes, or if metadata requests are expensive, the solution is to cache the metadata to disk.

Enable Caching Metadata

To enable caching of metadata, set CacheMetadata = true and see Configuring the Cache Connection for instructions on how to configure your connection string. The connector caches the metadata the first time it is needed and uses the metadata cache for subsequent requests.

Update the Metadata Cache

Because metadata is cached, changes to metadata on the live source, for example, adding or removing a column or attribute, are not automatically reflected in the metadata cache. To get updates to the live metadata, you need to delete or drop the cached data.

Automatically caching data is useful when you do not want to rebuild the cache for each query. When you query data for the first time, the connector automatically initializes and builds a cache in the background. When AutoCache = true, the connector uses the cache for subsequent query executions, resulting in faster response times.

Configuring Automatic Caching

Caching the Files Table

The following example caches the Files table in the file specified by the CacheLocation property of the connection string.

SELECT Id, Name FROM Files WHERE Id = 'Jq74mCczmFXk1tC10GB'

Common Use Case

A common use for automatically caching data is to improve driver performance when making repeated requests to a live data source, such as building a report or creating a visualization. With auto caching enabled, repeated requests to the same data may be executed in a short period of time, but within an allowable tolerance (CacheTolerance) of what is considered "live" data.

With explicit caching (AutoCache = false), you decide exactly what data is cached and when to query the cache instead of the live data. Explicit caching gives you full control over the cache contents by using CACHE Statements. This section describes some strategies to use the caching features offered by the connector.

Creating the Cache

To load data in the cache, issue the following statement.

CACHE SELECT * FROM tableName WHERE ...

Once the statement is issued, any matching data in tableName is loaded into the corresponding table.

Updating the Cache

This section describes two ways to update the cache.

Updating with the SELECT Statement

The following example shows a statement that can update modified rows and add missing rows in the cached table. However, this statement does not delete extra rows that are already in the cache. This statement only merges the new rows or updates the existing rows.

CACHE SELECT * FROM Files WHERE Id = 'Jq74mCczmFXk1tC10GB'

Updating with the TRUNCATE Statement

The following example shows a statement that can update modified rows and add missing rows in the cached table. This statement can also delete rows in the cache table that are not present in the live data source.

  CACHE WITH TRUNCATE SELECT * FROM Files WHERE Id = 'Jq74mCczmFXk1tC10GB'
  

Query the Data in Online or Offline Mode

This section describes how to query the data in online or offline mode.

Online: Select Cached Tables

You can use the tableName#CACHE syntax to explicitly execute queries to the cache while still online, as shown in the following example.

SELECT * FROM Files#CACHE

Offline: Select Cached Tables

With Offline = true, SELECT statements always execute against the local cache database, regardless of whether you explicitly specify the cached table or not. Modification of the cache is disabled in Offline mode to prevent accidentally updating only the cached data. Executing a DELETE/UPDATE/INSERT statement while in Offline mode results in an exception.

The following example selects from the local cache but not the live data source because Offline = true.

SELECT * FROM Files WHERE Id='Jq74mCczmFXk1tC10GB' ORDER BY Name ASC

Delete Data from the Cache

You can delete data from the cache by building a direct connection to the database. Note that the connector does not support manually deleting data from the cache.

Common Use Case

A common use for caching is to have an application always query the cached data and only update the cache at set intervals, such as once every day or every two hours. There are two ways in which this can be implemented:

• AutoCache = false and Offline = false. All queries issued by the application explicitly reference the tableName#CACHE table. When the cache needs to be updated, the application executes a tableName#CACHE ... statement to bring the cached data up to date.
• Offline = true. Caching is transparent to the application. All queries are executed against the table as normal, so most application code does not need to be aware that caching is done. To update the cached data, simply create a separate connection with Offline = false and execute a tableName#CACHE ... statement.

The connector maps types from the data source to the corresponding data type available in the chosen cache database. The following table shows the mappings between the data types configured in the schema and the data types in the database. Some schema types have synonyms which are all listed in the Schema column.

Data Type Mapping

Note: String columns can map to different data types depending on their length.

Schema	.NET	JDBC	SQL Server	Derby	MySQL	Oracle	SQLite	Access
int, integer, int32	Int32	int	int	INTEGER	INT	NUMBER	integer	LONG
smallint, short, int16	Int16	short	smallint	SMALLINT	SMALLINT	NUMBER	integer	SHORT
double, float, real	Double	double	float	DOUBLE	DOUBLE	NUMBER	double	DOUBLE
date	DateTime	java.sql.Date	date	DATE	DATE	DATE	date	DATETIME
datetime, timestamp	DateTime	java.sql.Date	datetime	TIMESTAMP	DATETIME	TIMESTAMP	datetime	DATETIME
time, timespan	TimeSpan	java.sql.Time	time	TIME	TIME	TIMESTAMP	datetime	DATETIME
string, varchar	String	java.lang.String	If length > 4000: nvarchar(max), Otherwise: nvarchar(length)	If length > 32672: LONG VARCHAR, Otherwise VARCHAR(length)	If length > 255: LONGTEXT, Otherwise: VARCHAR(length)	If length > 4000: CLOB, Otherwise: VARCHAR2(length)	nvarchar(length)	If length > 255: LONGTEXT, Otherwise: VARCHAR(length)
long, int64, bigint	Int64	long	bigint	BIGINT	BIGINT	NUMBER	bigint	LONG
boolean, bool	Boolean	boolean	tinyint	SMALLINT	BIT	NUMBER	tinyint	BIT
decimal, numeric	Decimal	java.math.BigDecimal	decimal	DECIMAL	DECIMAL	DECIMAL	decimal	CURRENCY
uuid	Guid	java.util.UUID	nvarchar(length)	VARCHAR(length)	VARCHAR(length)	VARCHAR2(length)	nvarchar(length)	VARCHAR(length)
binary, varbinary, longvarbinary	byte[]	byte[]	binary(1000) or varbinary(max) after SQL Server 2000, image otherwise	BLOB	LONGBLOB	BLOB	BLOB	LONGBINARY

Query Processing

CData has a client-side SQL engine built into the connector library. This enables support for the full capabilities that SQL-92 offers, including filters, aggregations, functions, etc.

For sources that do not support SQL-92, the connector offloads as much of SQL statement processing as possible to Microsoft OneDrive and then processes the rest of the query in memory (client-side). This results in optimal performance.

For data sources with limited query capabilities, the connector handles transformations of the SQL query to make it simpler for the connector. The goal is to make smart decisions based on the query capabilities of the data source to push down as much of the computation as possible. The Microsoft OneDrive Query Evaluation component examines SQL queries and returns information indicating what parts of the query the connector is not capable of executing natively.

The Microsoft OneDrive Query Slicer component is used in more specific cases to separate a single query into multiple independent queries. The client-side Query Engine makes decisions about simplifying queries, breaking queries into multiple queries, and pushing down or computing aggregations on the client-side while minimizing the size of the result set.

There's a significant trade-off in evaluating queries, even partially, client-side. There are always queries that are impossible to execute efficiently in this model, and some can be particularly expensive to compute in this manner. CData always pushes down as much of the query as is feasible for the data source to generate the most efficient query possible and provide the most flexible query capabilities.

More Information

For a full discussion of how CData handles query processing, see CData Architecture: Query Execution.

Logging

Capturing connector logging can be very helpful when diagnosing error messages or other unexpected behavior.

Basic Logging

To begin capturing connector logging, set these properties:

• Logfile: A filepath that designates the name and location of the log file.
• Verbosity: A numerical value (1-5) that determines the amount of detail in the log. See the page in the Connection Properties section for an explanation of the five levels.
• MaxLogFileSize: When the limit is hit, a new log is created in the same folder with the date and time appended to the end. The default limit is 100 MB. Values lower than 100 kB will use 100 kB as the value instead.
• MaxLogFileCount: A string specifying the maximum file count of log files. When the limit is hit, a new log is created in the same folder with the date and time appended to the end and the oldest log file will be deleted. Minimum supported value is 2. A value of 0 or a negative value indicates no limit on the count.

Once these properties are set, the connector populates the log file as it carries out various tasks, such as when authentication is performed or queries are executed. If the specified file doesn't already exist, it is created.

Log Verbosity

The verbosity level determines the amount of detail that the connector reports to the Logfile. Supported Verbosity levels range from 1 to 5.

The following list describes each level:

1	Setting Verbosity to 1 logs the query, the number of rows returned by it, the start of execution and the time taken, and any errors.
2	Setting Verbosity to 2 logs everything included in Verbosity 1, cache queries, and additional information about the request.
3	Setting Verbosity to 3 also logs HTTP headers, as well as the body of the request and the response.
4	Setting Verbosity to 4 also logs transport-level communication with the data source. This includes SSL negotiation.
5	Setting Verbosity to 5 also logs communication with the data source and additional details that may be helpful in troubleshooting problems. This includes interface commands.

For normal operations, Verbosity should not be set to greater than 1. At higher verbosities you can log substantial amounts of data, which can delay execution times.

To refine the logged content further by showing/hiding specific categories of information, see LogModules.

Sensitive Data

Verbosity levels of 3 and higher may capture information that you do not want shared outside of your organization. The following lists information of concern for each level:

• Verbosity 3: The full body of the request and the response, which includes all the data returned by the connector
• Verbosity 4: SSL certificates
• Verbosity 5: Any extra transfer data not included at Verbosity 3, such as non human-readable binary transfer data

Note: Although we mask sensitive values, such as passwords, in the connection string and any request in the log, it is always best practice to review the logs for any sensitive information before sharing outside your organization.

Advanced Logging

You may want to refine the exact information that is recorded to the log file. This can be accomplished using the LogModules property. This property allows you to filter the logging using a semicolon-separated list of logging modules.

Example property value:

LogModules=INFO;EXEC;SSL;SQL;META;

Note that the logfile filtering triggered by the Verbosity connection property takes precedence over the filtering imposed by this connection property. This means that operations of a higher verbosity level than the level specified in the Verbosity connection property are not printed in the logfile, even if they belong to one of the modules specified in this connection property.

The available modules and submodules are:

Module Name	Module Description	Submodules
INFO	General Information. Includes the connection string, product version (build number), and initial connection messages.	Connec – Information related to creating or destroying connections. Messag – Generic label for messages pertaining to connections, the connection string, and product version. These messages are typically specific to the connector, rather than being received and passed along directly from the service.
EXEC	Query Execution. Includes execution messages for user-written SQL queries, parsed SQL queries, and normalized SQL queries. Success/failure messages for queries and query pages appear here as well.	Messag – Messages pertaining to query execution. These messages are typically specific to the connector, rather than being received and passed along directly from the service. Normlz – Query normalization steps. Query normalization is when the product takes the user-submitted query and rewrites the query to get the same results with optimal performance. Origin – This label applies to any messages recording a user's original query (the exact, unaltered, non-normalized query executed by the user). Page – Messages related to query paging. Parsed – Query parsing steps. Parsing is the process of converting the user-submitted query into a standardized format for easier processing.
HTTP	HTTP protocol messages. Includes HTTP requests/responses (including POST messages), as well as Kerberos related messages.	KERB – HTTP requests related to Kerberos. Messag – Messages pertaining to HTTP protocols. These messages are typically specific to the connector, rather than being received and passed along directly from the service. Unpack – This label applies to messages about zipped data being returned from the service API and unpacked by the product. Res – Messages containing HTTP responses. Req – Messages containing HTTP requests.
WSDL	Messages pertaining to the generation of WSDL/XSD files.	—
SSL	SSL certificate messages.	Certif – Messages pertaining to SSL certificates.
AUTH	Authentication related failure/success messages.	Messag – Messages pertaining to authentication. These messages are typically specific to the connector, rather than being received and passed along directly from the service. OAuth – Messages related to OAuth authentication. Krbros – Kerberos-related authentication messages.
SQL	Includes SQL transactions, SQL bulk transfer messages, and SQL result set messages.	Bulk – Messages pertaining to bulk query execution. Cache – Messages related to reading row data from and writing row data to the product's cache for better performance. Messag – Messages pertaining to SQL transactions. These messages are typically specific to the connector, rather than being received and passed along directly from the service. ResSet – Query resultsets. Transc – Messages related to handling transactions, including information about the number of jobs executed and backup table handling.
META	Metadata cache and schema messages.	Cache – Messages related to reading from and modifying column and table definitions in the product's cache for better performance. Schema – Messages related to retrieving metadata from or modifying the service schema. MemSto – Messages related to writing to or reading from in-memory metadata cache. Storag – Messages relating to storing metadata on disk or in an external data store, rather than in memory.
FUNC	Information related to executing SQL functions.	Errmsg – Error messages related to executing SQL functions.
TCP	Incoming and outgoing raw bytes on TCP transport layer messages.	Send – Raw data sent via the TCP protocol. Receiv – Raw data received via the TCP protocol.
FTP	Messages pertaining to the File Transfer Protocol.	Info – Status messages related to communication in the FTP protocol. Client – Messages related to actions taken by the FTP client (the product) during FTP communication. Server – Messages related to actions taken by the FTP server during FTP communication.
SFTP	Messages pertaining to the Secure File Transfer Protocol.	Info – Status messages related to communication in the SFTP protocol. To_Server – Messages related to actions taken by the SFTP client (the product) during SFTP communication. From_Server – Messages related to actions taken by the SFTP server during SFTP communication.
POP	Messages pertaining to data transferred via the Post Office Protocol.	Client – Messages related to actions taken by the POP client (the product) during POP communication. Server – Messages related to actions taken by the POP server during POP communication. Status – Status messages related to communication in the POP protocol.
SMTP	Messages pertaining to data transferred via the Simple Mail Transfer Protocol.	Client – Messages related to actions taken by the SMTP client (the product) during SMTP communication. Server – Messages related to actions taken by the SMTP server during SMTP communication. Status – Status messages related to communication in the SMTP protocol.
CORE	Messages relating to various internal product operations not covered by other modules.	—
DEMN	Messages related to SQL remoting.	—
CLJB	Messages about bulk data uploads (cloud job).	Commit – Submissions for bulk data uploads.
SRCE	Miscellaneous messages produced by the product that don't belong in any other module.	—
TRANCE	Advanced messages concerning low-level product operations.	—

Exception Handling

Exceptions can be surfaced from either the API or the CData Python Connector for Microsoft OneDrive. Each exception will have an error code, an error message, and a SQL state.

Error Codes

The error code classifies the type of error.

0	NONE	Used for unclassified errors and internally handled errors. This code also covers data source-specific errors that do not fit in any specific category.
65537	TCP_UNKNOWN_HOST	Unable to resolve a hostname (DNS failure).
65538	TCP_CONNECTION_REFUSED	Could not connect to the remote port.
65539	TCP_AUTH_FAILED	Login failed when using a binary authentication protocol. Use this for auth errors when the protocol is not HTTP (LDAP, SASL, Kerberos, ...).
65540	TCP_TIMEOUT	Did not receive a response after sending a request to the server.
65541	TCP_PROTOCOL	For wire protocol drivers. Either the server sent a bad packet that we are unable to process, or we cannot construct a packet to send.
131073	TLS_SERVER_UNTRUSTED	Could not verify SSL server certificate.
131074	TLS_CLIENT_UNTRUSTED	Server did not accept the client certificate we sent.
196609	OAUTH_DECRYPT_FAILED	OAuthEncryptKey did not decrypt the OAuthSettings file.
196610	OAUTH_MISSING_CLIENT_INFO	OAuthClientId / OAuthClientSecret / OAuthJWTCert is missing.
196611	OAUTH_MISSING_PROP	General OAuth property missing. OAUTH_MISSING_CLIENT_INFO is used for missing client ID/secret and JWT cert.
196612	OAUTH_NO_ACCESS_TOKEN	Unable to retrieve access token. Only use this when getting a token in GetOAuthAccessToken / RefreshOAuthAccessToken.
196613	OAUTH_TOKEN_EXPIRED	The access token expired. Normally used with a RefreshOAuth/OAuthException behavior.
196614	OAUTH_INVALID_PROP	OAuth property has an invalid value. OAUTH_MISSING_CLIENT_INFO / OAUTH_MISSING_PROP is used if the value is not set.
262145	HTTP_REQUEST_TIMEOUT	Did not receive a response from the HTTP server.
262146	HTTP_CLIENT_ERROR	Generic HTTP 4xx error. Only use for 4xx errors not covered by other codes.
262147	HTTP_AUTH_FAILED	HTTP 401 error.
262148	HTTP_LIMIT_EXCEEDED	HTTP 429 error.
262149	HTTP_SERVER_ERROR	HTTP 5xx error.
262150	HTTP_NOT_FOUND_ERROR	HTTP 404 error.
327681	CORE_TIMEOUT	General timeout. Not related to a specific network request.
327682	CORE_OP_NOT_ALLOWED	Operation blocked by provider permissions.
327683	CORE_CONNECTION_CONFIG	Connection configuration is not valid.
327684	CORE_SERIALIZE	Failed to encode data into a specific format (XML, JSON, CSV, ...).
327685	CORE_DESERIALIZE	Failed to decode data from a specific format (XML, JSON, CSV, ...).
393217	SQL_SYNTAX_ERROR	Unable to parse a SQL query.
393218	SQL_MISSING_COLUMNS	Query did not include required columns.
393219	SQL_MISSING_PARAMS	Stored procedure call did not include required parameters.
393220	SQL_QUERY_NOT_SUPPORTED	A part of the query is not allowed in the current context.
458753	SSH_SERVER_UNTRUSTED	Could not verify SSH server.
524289	STORAGE_LIST_EXCEPTION	Issue listing storage resources.
524290	STORAGE_RESOURCE_NOT_FOUND	Issue finding storage resources.
524291	STORAGE_ROOT_RESOURCE_NOT_FOUND	The root resource (bucket/share/drive) was not found; cannot create it in flat file drivers.
524292	STORAGE_RESOURCE_NOT_A_DIRECTORY	Storage resource is not a directory.
524293	STORAGE_RESOURCE_NOT_A_FILE	Storage resource is not a file.
524294	STORAGE_PERMISSIONS_DENIED	Storage permissions denied.

SQL State

The SQL state is used when throwing generic provider errors to the wrapper and indicates the success or failure of a call.

Some of the common SQL states are listed below:

07007	REQUIRED_CLAUSE	Class Code 07: Dynamic SQL Error.
08001	OPEN_CONNECTION	Class Code 08: Connection Exception. The connection was unable to be established to the application server or other server.
08004	REJECT_CONNECTION	The application server rejected establishment of the connection.
42501	PRIVILEGE_IDENTIFIED_OBJECT	Class Code 42: Syntax Error or Access Rule Violation. The authorization ID does not have the privilege to perform the specified operation on the identified object.
42506	AUTH_FAILED	Owner authorization failure occurred.
42601	SQL_SYNTAX	A character, token, or clause is invalid or missing.

Error Message

The error message provides more detailed reasoning about why the error occurred. It provides an explanation of the issue, and may include steps on how to resolve it.

SELECT Statements

See SELECT Statements for a syntax reference and examples.

See Data Model for information on the capabilities of the Microsoft OneDrive API.

CACHE Statements

CACHE statements allow granular control over the connector's caching functionality. For a syntax reference and examples, see CACHE Statements.

For more information on the caching feature, see Caching Data.

EXECUTE Statements

Use EXECUTE or EXEC statements to execute stored procedures. See EXECUTE Statements for a syntax reference and examples.

Names and Quoting

• Table and column names are considered identifier names; as such, they are restricted to the following characters: [A-Z, a-z, 0-9, _:@].
• To use a table or column name with characters not listed above, the name must be quoted using square brackets ([name]) in any SQL statement.
• Parameter names can optionally start with the @ symbol (e.g., @p1 or @CustomerName) and cannot be quoted.
• Strings must be quoted using single quotes (e.g., 'John Doe').

The connector provides functions that are similar to those that are available with most standard databases. These functions are implemented in the CData provider engine and thus are available across all data sources with the same consistent API. Three categories of functions are available: string, date, and math.

The connector interprets all SQL function inputs as either strings or column identifiers, so you need to escape all literals as strings, with single quotes. For example, contrast the SQL Server syntax and connector syntax for the DATENAME function:

• SQL Server:
  

  SELECT DATENAME(yy,GETDATE())

• connector:
  

  SELECT DATENAME('yy',GETDATE())

String Functions

These functions perform string manipulations and return a string value. See STRING Functions for more details.

Date Functions

These functions perform date and date time manipulations. See DATE Functions for more details.

Math Functions

These functions provide mathematical operations. See MATH Functions for more details.

ASCII(character_expression)

Returns the ASCII code value of the left-most character of the character expression.

• character_expression: The character expression.

                      SELECT ASCII('0');
                      --  Result: 48
                    

BASE64_ENCODE(input_binary)

Returns the Base64-encoded string form of a binary input.

• input_binary: The binary value to encode.

                        SELECT BASE64_ENCODE(BinaryData);
                    -- Result: 'QmFzZTY0RW5jb2RlZA=='
                    

BASE64_DECODE(input_string)

Returns the binary result of decoding a Base64-encoded string.

• input_string: The Base64-encoded string.

                        SELECT BASE64_DECODE('QmFzZTY0RW5jb2RlZA==');
                    -- Result: (binary output)
                    

CHAR(integer_expression)

Converts the integer ASCII code to the corresponding character.

• integer_expression: The integer from 0 through 255.

                      SELECT CHAR(48);
                      -- Result: '0'
                    

CHARINDEX(expressionToFind ,expressionToSearch [,start_location ])

Returns the starting position of the specified expression in the character string.

• expressionToFind: The character expression to find.
• expressionToSearch: The character expression, typically a column, to search.
• start_location: An optional character position to start searching for expressionToFind in expressionToSearch.

                      SELECT CHARINDEX('456', '0123456');
                      -- Result: 4

                      SELECT CHARINDEX('456', '0123456', 5);
                      -- Result: -1
                    

CHAR_LENGTH(character_expression),

Returns the number of UTF-8 characters present in the expression.

• character_expression: The set of characters to be evaluated for length.

				 SELECT CHAR_LENGTH('sample text') FROM Account LIMIT 1
				 -- Result: 11			
				

CONCAT(string_value1, string_value2, ..., string_valueN)

Returns the string that is the concatenation of two or more string values.

• string_value1: The first string to be concatenated.
• string_value2: The second string to be concatenated.
• string_valueN: (optional) Any additional strings to be concatenated.

                      SELECT CONCAT('Hello, ', 'world!');
                      -- Result: 'Hello, world!'
                    

CONTAINS(expressionToSearch, expressionToFind)

Returns 1 if expressionToFind is found within expressionToSearch; otherwise, 0.

• expressionToSearch: The character expression, typically a column, to search.
• expressionToFind: The character expression to find.

                      SELECT CONTAINS('0123456', '456');
                      -- Result: 1

                      SELECT CONTAINS('0123456', 'Not a number');
                      -- Result: 0
                    

ENDSWITH(character_expression, character_suffix)

Returns 1 if character_expression ends with character_suffix; otherwise, 0.

• character_expression: The character expression.
• character_suffix: The character suffix to search for.

                      SELECT ENDSWITH('0123456', '456');
                      -- Result: 1

                      SELECT ENDSWITH('0123456', '012');
                      -- Result: 0
                    

FILESIZE(uri)

Returns the number of bytes present in the file at the specified file path.

• uri: The path of the file from which to read the size.

				SELECT FILESIZE('C:/Users/User1/Desktop/myfile.txt');
				-- Result: 23684
				

FORMAT(value [, parseFormat], format )

Returns the value formatted with the specified format.

• value: The string to format.
• format: The string specifying the output syntax of the date or numeric format.
• parseFormat: The string specifying the input syntax of the date value. Not applicable to numeric types.

                      SELECT FORMAT(12.34, '#');
                      -- Result: 12

                      SELECT FORMAT(12.34, '#.###');
                      -- Result: 12.34

                      SELECT FORMAT(1234, '0.000E0');
                      -- Result: 1.234E3
                      
                      SELECT FORMAT('2019/01/01', 'yyyy-MM-dd');
                      -- Result: 2019-01-01
                      
                      SELECT FORMAT('20190101', 'yyyyMMdd', 'yyyy-MM-dd');
                      -- Result: '2019-01-01'
                    

HASHBYTES(algorithm, value)

Returns the hash of the input value as a byte array using the given algorithm. The supported algorithms are MD5, SHA1, SHA2_256, SHA2_512, SHA3_224, SHA3_256, SHA3_384, and SHA3_512.

• algorithm: The algorithm to use for hashing. Must be one of MD5, SHA1, SHA2_256, SHA2_512, SHA3_224, SHA3_256, SHA3_384, or SHA3_512.
• value: The value to hash. Must be either a string or byte array.

                      SELECT HASHBYTES('MD5', 'Test');
                      -- Result (byte array): 0x0CBC6611F5540BD0809A388DC95A615B
                    

INDEXOF(expressionToSearch, expressionToFind [,start_location ])

Returns the starting position of the specified expression in the character string.

• expressionToSearch: The character expression, typically a column, to search.
• expressionToFind: The character expression to find.
• start_location: An optional character position to start searching for expressionToFind in expressionToSearch.

                      SELECT INDEXOF('0123456', '456');
                      -- Result: 4

                      SELECT INDEXOF('0123456', '456', 5);
                      -- Result: -1
                    

ISALPHABETIC(character_expression)

Returns 1 if the character expression consists only of alphabetic characters; otherwise, 0.

• character_expression: The string expression to evaluate.

                      SELECT ISALPHABETIC('Hello');
                      -- Result: 1

                      SELECT ISALPHABETIC('Hello123');
                      -- Result: 0

                      SELECT ISALPHABETIC('Hello!');
                      -- Result: 0
                    

ISALPHANUMERIC(character_expression)

Returns 1 if the character expression consists only of alphabetic and numeric characters; otherwise, 0.

• character_expression: The string expression to evaluate.

                      SELECT ISALPHANUMERIC('Hello123');
                      -- Result: 1

                      SELECT ISALPHANUMERIC('123');
                      -- Result: 1

                      SELECT ISALPHANUMERIC('Hello.123');
                      -- Result: 0
                    

ISNUMERIC(character_expression)

Returns 1 if the character expression consists only of numeric digits and up to one decimal point; otherwise, 0.

• character_expression: The string expression to evaluate.

                      SELECT ISNUMERIC('123');
                      -- Result: 1

                      SELECT ISNUMERIC('123.45');
                      -- Result: 1

                      SELECT ISNUMERIC('123.45.67');
                      -- Result: 0

                      SELECT ISNUMERIC('12a3');
                      -- Result: 0
                    

JSON_EXTRACT(json, jsonpath)

Selects any value in a JSON array or object. The path to the array is specified in the jsonpath argument. Return value is numeric or null.

• json: The JSON document to extract.
• jsonpath: The XPath used to select the nodes. The JSONPath must be a string constant. The values of the nodes selected will be returned in a token-separated list.

                      SELECT JSON_EXTRACT('{"test": {"data": 1}}', '$.test');
                      -- Result: '{"data":1}'

                      SELECT JSON_EXTRACT('{"test": {"data": 1}}', '$.test.data');
                      -- Result: 1

                      SELECT JSON_EXTRACT('{"test": {"data": [1, 2, 3]}}', '$.test.data[1]');
                      -- Result: 2
                    

LEFT ( character_expression , integer_expression )

Returns the specified number of characters counting from the left of the specified string.

• character_expression: The character expression.
• integer_expression: The positive integer that specifies how many characters will be returned counting from the left of character_expression.

                      SELECT LEFT('1234567890', 3);
                      -- Result: '123'
                    

LEN(string_expression)

Returns the number of characters of the specified string expression.

• string_expression: The string expression.

                      SELECT LEN('12345');
                      -- Result: 5
                    

LOCATE(substring,string)

Returns an integer representing how many characters into the string the substring appears.

• substring: The substring to find inside larger string.
• string: The larger string that is searched for the substring.
• start locations: An optional integer that sets the character position (offset) from which to start searching.

				SELECT LOCATE('sample','XXXXXsampleXXXXX');
				-- Result: 6

                SELECT LOCATE('sample', 'XXXXXsampleXXXXX', 7)
                -- Result: 0
				

LOWER ( character_expression )

Returns the character expression with the uppercase character data converted to lowercase.

• character_expression: The character expression.

                      SELECT LOWER('MIXED case');
                      -- Result: 'mixed case'
                    

LTRIM(character_expression)

Returns the character expression with leading blanks removed.

• character_expression: The character expression.

                      SELECT LTRIM('     trimmed');
                      -- Result: 'trimmed'
                    

MASK(string_expression, mask_character [, start_index [, end_index ]])

Replaces the characters between start_index and end_index with the mask_character within the string.

• string_expression: The string expression to be searched.
• mask_character: The character to mask with.
• start_index: The optional number of characters to leave unmasked at beginning of string. Defaults to 0.
• end_index: The optional number of characters to leave unmasked at end of string. Defaults to 0.

                        SELECT MASK('1234567890','*',);
                        -- Result: '**********'
                        SELECT MASK('1234567890','*', 4);
                        -- Result: '1234******'
                        SELECT MASK('1234567890','*', 4, 2);
                        -- Result: '1234****90'  
                    

NCHAR(integer_expression)

Returns the Unicode character with the specified integer code as defined by the Unicode standard.

• integer_expression: The integer from 0 through 65535 (0 through xFFFF).

OCTET_LENGTH(character_expression),

Returns the number of bytes present in the expression.

• character_expression: The set of characters to be be evaluated.

				 SELECT OCTET_LENGTH('text') FROM Account LIMIT 1
				 -- Result: 4
				

PATINDEX(pattern, expression)

Returns the starting position of the first occurrence of the pattern in the expression. Returns 0 if the pattern is not found.

• pattern: The character expression that contains the sequence to be found. The wild-card character % can be used only at the start or end of the expression.
• expression: The expression, typically a column, to search for the pattern.

                      SELECT PATINDEX('123%', '1234567890');
                      -- Result: 1

                      SELECT PATINDEX('%890', '1234567890');
                      -- Result: 8

                      SELECT PATINDEX('%456%', '1234567890');
                      -- Result: 4
                    

POSITION(expressionToFind IN expressionToSearch)

Returns the starting position of the specified expression in the character string.

• expressionToFind: The character expression to find.
• expressionToSearch: The character expression, typically a column, to search.

                      SELECT POSITION('456' IN '123456');
                      -- Result: 4

                      SELECT POSITION('x' IN '123456');
                      -- Result: 0
                    

QUOTENAME(character_string [, quote_character])

Returns a valid SQL Server-delimited identifier by adding the necessary delimiters to the specified Unicode string.

• character_string: The string of Unicode character data. The string is limited to 128 characters. Inputs greater than 128 characters return null.
• quote_character: An optional single character to be used as the delimiter. These include:
  • a single quotation mark (')
  • a left or right bracket ([])
  • a double quotation mark (")
  • a left or right parenthesis ( () )
  • a greater or less than sign (><)
  • a left or right brace ({})
  • a backtick (`)

  If quote_character is not specified brackets are used. If an unacceptable character is supplied, it returns NULL.

                      SELECT QUOTENAME('table_name');
                      -- Result: '[table_name]'

                      SELECT QUOTENAME('table_name', '"');
                      -- Result: '"table_name"'

                      SELECT QUOTENAME('table_name', '[');
                      -- Result: '[table_name]'
                    

REGEXP_REPLACE(expr, pattern [, replacement [, position [, occurrence [, match_type]]]])

Replaces occurrences of a regular expression pattern in the input string with a specified value and returns the resulting string.

• expr: The string expression to be searched.
• pattern: The regular expression pattern to match.
• replacement: (optional) The string to replace each matched occurrence of pattern with. Supports backreferences \1 through \9 and escape sequences \n, \r, \t, and \\. By default, this argument is an empty string, meaning matched portions are removed from the output string.
• position: (optional) The 1-based starting position used when searching for regular expression matches in expr. The default is 1. All characters prior to the starting position are included in the output string unaltered. Skipped characters are ignored when calculating regular expression matches, even if they match pattern.
• occurrence: (optional) Specifies whether all occurrences of pattern,, or only a specific occurrence of pattern are replaced. The default is 0, which means all occurrences of pattern are replaced with replacement. Set to 1 to only replace the first instance of the pattern; 2 to replace the second; etc.
• match_type: (optional) Modifiers used to customize matching behavior. Supported values are: 'c' (case-sensitive, default), 'i' (case-insensitive), 'm' (multiline), 'n' (dot matches newline), 'x' (extended mode). These can be freely combined by including the letters back to back. For example, 'im' applies the functionality of both 'i' and 'm'. The regular expression syntax used is that of the Extended mode ('x') ignores whitespace and allows inline comments. If the pattern needs to match a literal space, it must be explicitly escaped.

                      SELECT REGEXP_REPLACE('abc123def456', '\d+', 'NUM');
                      -- Result: 'abcNUMdefNUM'

                      SELECT REGEXP_REPLACE('Hello\nHELLO\nhello', '^hello', 'X', 1, 0, 'im');
                      -- Result: 'X\nX\nX'
                    

REPLACE(string_expression, string_pattern, string_replacement)

Replaces all occurrences of a string with another string.

• string_expression: The string expression to be searched. This can be a character or binary data type.
• string_pattern: The substring to be found. Cannot be an empty string.
• string_replacement: The replacement string.

                      SELECT REPLACE('1234567890', '456', '|');
                      -- Result: '123|7890'

                      SELECT REPLACE('123123123', '123', '.');
                      -- Result: '...'

                      SELECT REPLACE('1234567890', 'a', 'b');
                      -- Result: '1234567890'
                    

REPLICATE ( string_expression ,integer_expression )

Repeats the string value the specified number of times.

• string_expression: The string to replicate.
• integer_expression: The repeat count.

                      SELECT REPLACE('x', 5);
                      -- Result: 'xxxxx'
                    

REVERSE ( string_expression )

Returns the reverse order of the string expression.

• string_expression: The string.

                      SELECT REVERSE('1234567890');
                      -- Result: '0987654321'
                    

RIGHT ( character_expression , integer_expression )

Returns the right part of the string with the specified number of characters.

• character_expression: The character expression.
• integer_expression: The positive integer that specifies how many characters of the character expression will be returned.

                      SELECT RIGHT('1234567890', 3);
                      -- Result: '890'
                    

RTRIM(character_expression)

Returns the character expression after it removes trailing blanks.

• character_expression: The character expression.

                      SELECT RTRIM('trimmed     ');
                      -- Result: 'trimmed'
                    

SOUNDEX(character_expression)

Returns the four-character Soundex code, based on how the string sounds when spoken.

• character_expression: The alphanumeric expression of character data.

                      SELECT SOUNDEX('smith');
                      -- Result: 'S530'
                    

SPACE(repeatcount)

Returns the string that consists of repeated spaces.

• repeatcount: The number of spaces.

                      SELECT SPACE(5);
                      -- Result: '     '
                    

SPLIT(string, delimiter, offset)

Returns a section of the string between to delimiters.

• string: The string to split.
• delimiter: The character to split the string with.
• offset: The number of the split to return. Positive numbers are treated as offsets from the left, and negative numbers are treated as offsets from the right.

                      SELECT SPLIT('a/b/c/d', '/', 1);
                      -- Result: 'a'
                      SELECT SPLIT('a/b/c/d', '/', -2);
                      -- Result: 'c'
                    

STARTSWITH(character_expression, character_prefix)

Returns 1 if character_expression starts with character_prefix; otherwise, 0.

• character_expression: The character expression.
• character_prefix: The character prefix to search for.

                      SELECT STARTSWITH('0123456', '012');
                      -- Result: 1

                      SELECT STARTSWITH('0123456', '456');
                      -- Result: 0
                    

STR ( float_expression [ , integer_length [ , integer_decimal ] ] )

Returns the character data converted from the numeric data. For example, STR(123.45, 6, 1) returns 123.5.

• float_expression: The float expression.
• length: The optional total length to return. This includes decimal point, sign, digits, and spaces. The default is 10.
• decimal: The optional number of places to the right of the decimal point. The decimal must be less than or equal to 16.

                      SELECT STR('123.456');
                      -- Result: '123'

                      SELECT STR('123.456', 2);
                      -- Result: '**'

                      SELECT STR('123.456', 10, 2);
                      -- Result: '123.46'
                    

STUFF(character_expression , integer_start , integer_length , replaceWith_expression)

Inserts a string into another string. It deletes the specified length of characters in the first string at the start position and then inserts the second string into the first string at the start position.

• character_expression: The string expression.
• start: The integer value that specifies the location to start deletion and insertion. If start or length is negative, null is returned. If start is longer than the string to be modified, character_expression, null is returned.
• length: The integer that specifies the number of characters to delete. If length is longer than character_expression, deletion occurs up to the last character in replaceWith_expression.
• replaceWith_expression: The expression of character data that will replace length characters of character_expression beginning at the start value.

                      SELECT STUFF('1234567890', 3, 2, 'xx');
                      -- Result: '12xx567890'
                    

SUBSTRING(string_value FROM start FOR length)

Returns the part of the string with the specified length; starts at the specified index.

• string_value: The character string.
• start: The positive integer that specifies the start index of characters to return.
• length: Optional. The positive integer that specifies how many characters will be returned.

                      SELECT SUBSTRING('1234567890' FROM 3 FOR 2);
                      -- Result: '34'

                      SELECT SUBSTRING('1234567890' FROM 3);
                      -- Result: '34567890'
                    

You can also drop the FROM and FOR clauses:

                    SELECT SUBSTRING('1234567890', 3, 2)
                    --Result: '34'
                    SELECT SUBSTRING('1234567890', 3)
                    --Result: '34567890'
                    

TEXT_ENCODE(input_string, charset)

Returns binary output by encoding a string using the specified character set.

• input_string: The plain text string.
• charset: The character set to use, such as 'UTF-8', 'ISO-8859-1'.

                    SELECT TEXT_ENCODE('Café', 'UTF-8');
                    -- Result: (binary output)
                    

TEXT_DECODE(input_binary, charset)

Returns a string decoded from binary data using the specified character set.

• input_binary: The binary value to decode.
• charset: The character set used for decoding.

                    SELECT TEXT_DECODE(BinaryData, 'UTF-8');
                    -- Result: 'Café'
                    

TOSTRING(string_value1)

Converts the value of this instance to its equivalent string representation.

• string_value1: The string to be converted.

                      SELECT TOSTRING(123);
                      -- Result: '123'

                      SELECT TOSTRING(123.456);
                      -- Result: '123.456'

                      SELECT TOSTRING(null);
                      -- Result: ''
                    

TRIM(trimspec trimchar FROM string_value)

Returns the character expression with leading and/or trailing blanks removed.

• trimspec: Optional. If included must be one of the keywords BOTH, LEADING or TRAILING.
• trimchar: Optional. If included should be a one-character string value.
• string_value: The string value to trim.

                      SELECT TRIM('     trimmed     ');
                      -- Result: 'trimmed'

                      SELECT TRIM(LEADING FROM '     trimmed     ');
                      -- Result: 'trimmed     '

                      SELECT TRIM('-' FROM '-----trimmed-----');
                      -- Result: 'trimmed'

                      SELECT TRIM(BOTH '-' FROM '-----trimmed-----');
                      -- Result: 'trimmed'

                      SELECT TRIM(TRAILING '-' FROM '-----trimmed-----');
                      -- Result: '-----trimmed'
                    

UNICODE(ncharacter_expression)

Returns the integer value defined by the Unicode standard of the first character of the input expression.

• ncharacter_expression: The Unicode character expression.

UPPER ( character_expression )

Returns the character expression with lowercase character data converted to uppercase.

• character_expression: The character expression.

                      SELECT UPPER('MIXED case');
                      -- Result: 'MIXED CASE'
                    

XML_EXTRACT(xml, xpath [, separator])

Extracts an XML document using the specified XPath to flatten the XML. A comma is used to separate the outputs by default, but this can be changed by specifying the third parameter.

• xml: The XML document to extract.
• xpath: The XPath used to select the nodes. The nodes selected will be returned in a token-separated list.
• separator: The optional token used to separate the items in the flattened response. If this is not specified, the separator will be a comma.

                      SELECT XML_EXTRACT('<vowels><ch>a</ch><ch>e</ch><ch>i</ch><ch>o</ch><ch>u</ch></vowels>', '/vowels/ch');
                      -- Result: 'a,e,i,o,u'

                      SELECT XML_EXTRACT('<vowels><ch>a</ch><ch>e</ch><ch>i</ch><ch>o</ch><ch>u</ch></vowels>', '/vowels/ch', ';');
                      -- Result: 'a;e;i;o;u'
                    

ABS ( numeric_expression )

Returns the absolute (positive) value of the specified numeric expression.

• numeric_expression: The expression of an indeterminate numeric data type except for the bit data type.

                      SELECT ABS(15);
                      -- Result: 15

                      SELECT ABS(-15);
                      -- Result: 15
                    

ACOS ( float_expression )

Returns the arc cosine, the angle in radians whose cosine is the specified float expression.

• float_expression: The float expression that specifies the cosine of the angle to be returned. Values outside the range from -1 to 1 return null.

                      SELECT ACOS(0.5);
                      -- Result: 1.0471975511966
                    

ASIN ( float_expression )

Returns the arc sine, the angle in radians whose sine is the specified float expression.

• float_expression: The float expression that specifies the sine of the angle to be returned. Values outside the range from -1 to 1 return null.

                      SELECT ASIN(0.5);
                      -- Result: 0.523598775598299
                    

ATAN ( float_expression )

Returns the arc tangent, the angle in radians whose tangent is the specified float expression.

• float_expression: The float expression that specifies the tangent of the angle to be returned.

                      SELECT ATAN(10);
                      -- Result: 1.47112767430373
                    

ATN2 ( float_expression1 , float_expression2 )

Returns the angle in radians between the positive x-axis and the ray from the origin to the point (y, x) where x and y are the values of the two specified float expressions.

• float_expression1: The float expression that is the y-coordinate.
• float_expression2: The float expression that is the x-coordinate.

                      SELECT ATN2(1, 1);
                      -- Result: 0.785398163397448
                    

CEILING ( numeric_expression ) or CEIL( numeric_expression )

Returns the smallest integer greater than or equal to the specified numeric expression.

• numeric_expression: The expression of an indeterminate numeric data type except for the bit data type.

                      SELECT CEILING(1.3);
                      -- Result: 2

                      SELECT CEILING(1.5);
                      -- Result: 2

                      SELECT CEILING(1.7);
                      -- Result: 2
                    

COS ( float_expression )

Returns the trigonometric cosine of the specified angle in radians in the specified expression.

• float_expression: The float expression of the specified angle in radians.

                      SELECT COS(1);
                      -- Result: 0.54030230586814
                    

COT ( float_expression )

Returns the trigonometric cotangent of the angle in radians specified by float_expression.

• float_expression: The float expression of the angle in radians.

                      SELECT COT(1);
                      -- Result: 0.642092615934331
                    

DEGREES ( numeric_expression )

Returns the angle in degrees for the angle specified in radians.

• numeric_expression: The angle in radians, an expression of an indeterminate numeric data type except for the bit data type.

                      SELECT DEGREES(3.1415926);
                      -- Result: 179.999996929531
                    

EXP ( float_expression )

Returns the exponential value of the specified float expression. For example, EXP(LOG(20)) is 20.

• float_expression: The float expression.

                      SELECT EXP(2);
                      -- Result: 7.38905609893065
                    

EXPR ( expression )

Evaluates the expression.

• expression: The expression. Operators allowed are +, -, *, /, ==, !=, >, <, >=, and <=.

                      SELECT EXPR('1 + 2 * 3');
                      -- Result: 7

                      SELECT EXPR('1 + 2 * 3 == 7');
                      -- Result: true
                    

FLOOR ( numeric_expression )

Returns the largest integer less than or equal to the numeric expression.

• numeric_expression: The expression of an indeterminate numeric data type except for the bit data type.

                      SELECT FLOOR(1.3);
                      -- Result: 1

                      SELECT FLOOR(1.5);
                      -- Result: 1

                      SELECT FLOOR(1.7);
                      -- Result: 1
                    

GREATEST(int1,int2,....)

Returns the greatest of the supplied integers.

				SELECT GREATEST(3,5,8,10,1)
				-- Result: 10			
				

HEX(value)

Returns a the equivalent hex for the input value.

• value: A string or numerical value to be converted into hex.

				SELECT HEX(866849198);
				-- Result: 33AB11AE
				
				SELECT HEX('Sample Text');
				-- Result: 53616D706C652054657874
				

JSON_AVG(json, jsonpath)

Computes the average value of a JSON array within a JSON object. The path to the array is specified in the jsonpath argument. Return value is numeric or null.

• json: The JSON document to compute.
• jsonpath: The JSONPath used to select the nodes. [x], [2..], [..8], or [1..12] are accepted. [x] selects all nodes.

                      SELECT JSON_AVG('[1,2,3,4,5]', '$[x]');
                      -- Result: 3

                      SELECT JSON_AVG('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[x]');
                      -- Result: 3

                      SELECT JSON_AVG('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[3..]');
                      -- Result: 4.5
                    

JSON_COUNT(json, jsonpath)

Returns the number of elements in a JSON array within a JSON object. The path to the array is specified in the jsonpath argument. Return value is numeric or null.

• json: The JSON document to compute.
• jsonpath: The JSONPath used to select the nodes. [x], [2..], [..8], or [1..12] are accepted. [x] selects all nodes.

                      SELECT JSON_COUNT('[1,2,3,4,5]', '$[x]');
                      -- Result: 5

                      SELECT JSON_COUNT('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[x]');
                      -- Result: 5

                      SELECT JSON_COUNT('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[3..]');
                      -- Result: 2
                    

JSON_MAX(json, jsonpath)

Gets the maximum value in a JSON array within a JSON object. The path to the array is specified in the jsonpath argument. Return value is numeric or null.

• json: The JSON document to compute.
• jsonpath: The JSONPath used to select the nodes. [x], [2..], [..8], or [1..12] are accepted. [x] selects all nodes.

                      SELECT JSON_MAX('[1,2,3,4,5]', '$[x]');
                      -- Result: 5

                      SELECT JSON_MAX('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[x]');
                      -- Result: 5

                      SELECT JSON_MAX('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[..3]');
                      -- Result: 4
                    

JSON_MIN(json, jsonpath)

Gets the minimum value in a JSON array within a JSON object. The path to the array is specified in the jsonpath argument. Return value is numeric or null.

• json: The JSON document to compute.
• jsonpath: The JSONPath used to select the nodes. [x], [2..], [..8], or [1..12] are accepted. [x] selects all nodes.

                      SELECT JSON_MIN('[1,2,3,4,5]', '$[x]');
                      -- Result: 1

                      SELECT JSON_MIN('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[x]');
                      -- Result: 1

                      SELECT JSON_MIN('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[3..]');
                      -- Result: 4
                    

JSON_SUM(json, jsonpath)

Computes the summary value in JSON according to the JSONPath expression. Return value is numeric or null.

• json: The JSON document to compute.
• jsonpath: The JSONPath used to select the nodes. [x], [2..], [..8], or [1..12] are accepted. [x] selects all nodes.

                      SELECT JSON_SUM('[1,2,3,4,5]', '$[x]');
                      -- Result: 15

                      SELECT JSON_SUM('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[x]');
                      -- Result: 15

                      SELECT JSON_SUM('{"test": {"data": [1,2,3,4,5]}}', '$.test.data[3..]');
                      -- Result: 9
                    

LEAST(int1,int2,....)

Returns the least of the supplied integers.

				SELECT LEAST(3,5,8,10,1)
				-- Result: 1			
				

LOG ( float_expression [, base ] )

Returns the natural logarithm of the specified float expression.

• float_expression: The float expression.
• base: The optional integer argument that sets the base for the logarithm.

                      SELECT LOG(7.3890560);
                      -- Result: 1.99999998661119
                    

LOG10 ( float_expression )

Returns the base-10 logarithm of the specified float expression.

• float_expression: The expression of type float.

                      SELECT LOG10(10000);
                      -- Result: 4
                    

MOD(dividend,divisor)

Returns the integer value associated with the remainder when dividing the dividend by the divisor.

• dividend: The number to take the modulus of.
• divisor: The number to divide the dividend by when determining the modulus.

				SELECT MOD(10,3);
				-- Result: 1
				

NEGATE(real_number)

Returns the opposite to the real number input.

• real_number: The real number to find the opposite of.

				SELECT NEGATE(10);
				-- Result: -10
				
				SELECT NEGATE(-12.4)
				--Result: 12.4
				

PI ( )

Returns the constant value of pi.

                  SELECT PI()
                  -- Result: 3.14159265358979 
                

POWER ( float_expression , y )

Returns the value of the specified expression raised to the specified power.

• float_expression: The float expression.
• y: The power to raise float_expression to.

                      SELECT POWER(2, 10);
                      -- Result: 1024

                      SELECT POWER(2, -2);
                      -- Result: 0.25
                    

RADIANS ( float_expression )

Returns the angle in radians of the angle in degrees.

• float_expression: The degrees of the angle as a float expression.

                      SELECT RADIANS(180);
                      -- Result: 3.14159265358979
                    

RAND ( [ integer_seed ] )

Returns a pseudorandom float value from 0 through 1, exclusive.

• seed: The optional integer expression that specifies the seed value. If seed is not specified, a seed value at random will be assigned.

                      SELECT RAND();
                      -- This result may be different, since the seed is randomized
                      -- Result: 0.873159630165044

                      SELECT RAND(1);
                      -- This result will always be the same, since the seed is constant
                      -- Result: 0.248668584157093
                    

ROUND ( numeric_expression [ ,integer_length] [ ,function ] )

Returns the numeric value rounded to the specified length or precision.

• numeric_expression: The expression of a numeric data type.
• length: The optional precision to round the numeric expression to. When this is omitted, the default behavior will be to round to the nearest whole number.
• function: The optional type of operation to perform. When the function parameter is omitted or has a value of 0 (default), numeric_expression is rounded. When a value other than 0 is specified, numeric_expression is truncated.

                      SELECT ROUND(1.3, 0);
                      -- Result: 1

                      SELECT ROUND(1.55, 1);
                      -- Result: 1.6

                      SELECT ROUND(1.7, 0, 0);
                      -- Result: 2

                      SELECT ROUND(1.7, 0, 1);
                      -- Result: 1
                      
                      SELECT ROUND (1.24);
                      -- Result: 1.0
                    

SIGN ( numeric_expression )

Returns the positive sign (1), 0, or negative sign (-1) of the specified expression.

• numeric_expression: The expression of an indeterminate data type except for the bit data type.

                      SELECT SIGN(0);
                      -- Result: 0

                      SELECT SIGN(10);
                      -- Result: 1

                      SELECT SIGN(-10);
                      -- Result: -1
                    

SIN ( float_expression )

Returns the trigonometric sine of the angle in radians.

• float_expression: The float expression specifying the angle in radians.

                     SELECT SIN(1);
                     -- Result: 0.841470984807897
                    

SQRT ( float_expression )

Returns the square root of the specified float value.

• float_expression: The expression of type float.

                      SELECT SQRT(100);
                      -- Result: 10
                    

SQUARE ( float_expression )

Returns the square of the specified float value.

• float_expression: The expression of type float.

                      SELECT SQUARE(10);
                      -- Result: 100

                      SELECT SQUARE(-10);
                      -- Result: 100
                    

TAN ( float_expression )

Returns the tangent of the input expression.

• float_expression: The expression of type float.

                      SELECT TAN(1);
                      -- Result: 1.5574077246549
                    

TRUNC(decimal_number,precision)

Returns the supplied decimal number truncated to have the supplied decimal precision.

• decimal_number: The decimal value to truncate.
• precision: The number of decimal places to truncate the decimal number to.

				SELECT TRUNC(10.3423,2);
				-- Result: 10.34
				

_ROW_NUMBER_()

Returns a row index as an additional column.

				SELECT ColumnName, _ROW_NUMBER_() FROM TableName
				-- Result: ColumnData, 0
				ColumnData2, 1
				ColumnData3, 2
				

CURRENT_DATE()

Returns the current date value.

                  SELECT CURRENT_DATE();
                  -- Result: 2018-02-01
                

CURRENT_TIMESTAMP()

Returns the current time stamp of the database system as a datetime value. This value is equal to GETDATE and SYSDATETIME, and is always in the local timezone.

                  SELECT CURRENT_TIMESTAMP();
                  -- Result: 2018-02-01 03:04:05
                

DATEADD (datepart , integer_number , date [, dateformat])

Returns the datetime value that results from adding the specified number (a signed integer) to the specified date part of the date.

• datepart: The part of the date to add the specified number to. The valid values and abbreviations are
  • year (yy, yyyy)
  • quarter (qq, q)
  • month (mm, m)
  • week (wk, ww)
  • weekday (dw)
  • dayofyear (dy, y)
  • day (dd, d)
  • hour (hh)
  • minute (mi, n)
  • second (ss, s)
  • millisecond (ms)
• number: The number to be added.
• date: The expression of the datetime data type.
• dateformat: The optional output date format.

                  SELECT DATEADD('d', 5, '2018-02-01');
                  -- Result: 2018-02-06

                  SELECT DATEADD('hh', 5, '2018-02-01 00:00:00');
                  -- Result: 2018-02-01 05:00:00
                

DATEDIFF ( datepart , startdate , enddate )

Returns the difference (a signed integer) of the specified time interval between the specified start date and end date.

• datepart: The part of the date that is the time interval of the difference between the start date and end date. The valid values and abbreviations are:
  • Year (year, yyyy, yy)
  • Quarter (quarter, qq, q)
  • Month (month, mm, m)
  • Week (week, wk, ww)
  • Weekday (weekday, dw)
  • Dayofyear (dayofyear, dy, y)
  • Day (day, dd, d)
  • Hour (hour, hh)
  • Minute (minute, mi, n)
  • Second (second, ss, s)
  • Millisecond (millisecond, ms)
• startdate: The datetime expression of the start date.
• enddate: The datetime expression of the end date.

                  SELECT DATEDIFF('d', '2018-02-01', '2018-02-10');
                  -- Result: 9

                  SELECT DATEDIFF('hh', '2018-02-01 00:00:00', '2018-02-01 12:00:00');
                  -- Result: 12
                

DATE_FORMAT(date,format)

Returns the date or timestamp in the format specified. This function mirrors the MySQL DATE_FORMAT function.

• date: A date or timestamp string.
• format: The specifier string of the desired output format. The list of supported format specifiers comes from the MySQL DATE_FORMAT function (see link to MySQL documentation above).

					SELECT DATE_FORMAT('9/4/2021 3:11:53 AM','%h')
					-- Result: 03
				  

DATEFROMPARTS(integer_year, integer_month, integer_day)

Returns the datetime value for the specified year, month, and day.

• year: The integer expression specifying the year.
• month: The integer expression specifying the month.
• day: The integer expression specifying the day.

                    SELECT DATEFROMPARTS(2018, 2, 1);
                    -- Result: 2018-02-01
                  

DATENAME(datepart , date)

Returns the character string that represents the specified date part of the specified date.

• datepart: The part of the date to return. The valid values and abbreviations are year (yy, yyyy), quarter (qq, q), month (mm, m), dayofyear (dy, y), day (dd, d), week (wk, ww), weekday (dw), hour (hh), minute (mi, n), second (ss, s), millisecond (ms), microsecond (mcs), and nanosecond (ns).
• date: The datetime expression.

                     SELECT DATENAME('yy', '2018-02-01');
                     -- Result: '2018'

                     SELECT DATENAME('dw', '2018-02-01');
                     -- Result: 'Thursday'
                   

DATEPART(datepart, date [,integer_datefirst])

Returns a character string that represents the specified date part of the specified date.

• datepart: The part of the date to return. The valid values and abbreviations are year (yy, yyyy), quarter (qq, q), month (mm, m), dayofyear (dy, y), day (dd, d), week (wk, ww), weekday (dw), hour (hh), minute (mi, n), second (ss, s), millisecond (ms), microsecond (mcs), nanosecond (ns), ISODOW, ISO_WEEK (isoweek, isowk,isoww), and ISOYEAR.
• date: The datetime string.
• datefirst: The optional integer representing the first day of the week. The default is 7, Sunday.

                    SELECT DATEPART('yy', '2018-02-01');
                    -- Result: 2018

                    SELECT DATEPART('dw', '2018-02-01');
                    -- Result: 5
                  

DATETIMEFROMPARTS(integer_year, integer_month, integer_day, integer_hour, integer_minute, integer_seconds, integer_milliseconds)

Returns the datetime value for the specified date parts.

• year: The integer expression specifying the year.
• month: The integer expression specifying the month.
• day: The integer expression specifying the day.
• hour: The integer expression specifying the hour.
• minute: The integer expression specifying the minute.
• seconds: The integer expression specifying the seconds.
• milliseconds: The integer expression specifying the milliseconds.

                    SELECT DATETIMEFROMPARTS(2018, 2, 1, 1, 2, 3, 456);
                    -- Result: 2018-02-01 01:02:03.456
                  

DATETIME2FROMPARTS(integer_year, integer_month, integer_day, integer_hour, integer_minute, integer_seconds, integer_fractions, integer_precision)

Returns the datetime value for the specified date parts.

• year: The integer expression specifying the year.
• month: The integer expression specifying the month.
• day: The integer expression specifying the day.
• hour: The integer expression specifying the hour.
• minute: The integer expression specifying the minute.
• seconds: The integer expression specifying the seconds.
• fractions: The integer expression specifying the fractions of the second.
• precision: The integer expression specifying the precision of the fraction.

				    SELECT DATETIME2FROMPARTS(2018, 2, 1, 1, 2, 3, 456, 3);
                    -- Result: 2018-02-01 01:02:03.456
                  

DATE_TRUNC(date, datepart)

Truncates the date to the precision of the given date part. Modeled after the Oracle TRUNC function.

• date: The datetime string that specifies the date.
• datepart: Refer to the Oracle documentation for valid datepart syntax.

				    SELECT DATE_TRUNC('05-04-2005', 'YY');
                    -- Result: '1/1/2005'
					
                    SELECT DATE_TRUNC('05-04-2005', 'MM');
                    -- Result: '5/1/2005'                    
                  

DATE_TRUNC2(datepart, date, [weekday])

Truncates the date to the precision of the given date part. Modeled after the PostgreSQL date_trunc function.

• datepart: One of 'millennium', 'century', 'decade', 'year', 'quarter', 'month', 'week', 'day', 'hour', 'minute' or 'second'.
• date: The datetime string that specifies the date.
• weekday: The optional day of the week to use as the first day for 'week'. One of 'sunday', 'monday', etc.

                    SELECT DATE_TRUNC2('year', '2020-02-04');
                    -- Result: '2020-01-01'

                    SELECT DATE_TRUNC2('week', '2020-02-04', 'monday');
                    -- Result: '2020-02-02', which is the previous Monday
                  

DAY(date)

Returns the integer that specifies the day component of the specified date.

• date: The datetime string that specifies the date.

                    SELECT DAY('2018-02-01');
                    -- Result: 1
                  

DAYNAME(date)

Returns the name of the day of the week of the specified date.

• date: The datetime string that specifies the date.

                    SELECT DAYNAME('8/18/2021');
                    -- Result: Wednesday
                  

DAYOFMONTH(date)

Returns the day of the month of the given date part.

• date: The datetime string that specifies the date.

				  SELECT DAYOFMONTH('04/15/2000');
				  -- Result: 15
				  

DAYOFWEEK(date)

Returns the day of the week of the given date part.

• date: The datetime string that specifies the date.

				  SELECT DAYOFWEEK('04/15/2000');
				  -- Result: 7
				  

DAYOFYEAR(date)

Returns the day of the year of the given date part.

• date: The datetime string that specifies the date.

				  SELECT DAYOFYEAR('04/15/2000');
				  -- Result: 106
				  

EOMONTH(date [, integer_month_to_add ]) or LAST_DAY(date)

Returns the last day of the month that contains the specified date with an optional offset.

• date: The datetime expression specifying the date for which to return the last day of the month.
• integer_month_to_add: The optional integer expression specifying the number of months to add to the date before calculating the end of the month.

                  SELECT EOMONTH('2018-02-01');
                  -- Result: 2018-02-28
                  
                  SELECT LAST_DAY('2018-02-01');
                  -- Result: 2018-02-28

                  SELECT EOMONTH('2018-02-01', 2);
                  -- Result: 2018-04-30
                

EXTRACT(date_part FROM date_column_name)

Returns the last day of the month that contains the specified date with an optional offset.

• date_part: One of the following date components: YEAR, MONTH, DAY, HOUR, MINUTE, SECOND.
• date_column_name: The name of a date column in a table.

                  SELECT EXTRACT(YEAR FROM DateColumn)
                  -- Result: 2021
                

FDWEEK(date)

Returns the first day of the week of the given date part.

• date: The datetime string that specifies the date.
• weeks to add: An optional integer expression specifying the number of months to add to the date before calculating the first day of the week.

				  SELECT FDWEEK('02-08-2018');
				  -- Result: 2/4/2018

          SELECT FDWEEK('02-08-2018', 1)
          --Result: 02/11/2018
				  

FDMONTH(date)

Returns the first day of the month of the given date part.

• date: The datetime string that specifies the date.
• month to add: An optional integer expression specifying the number of months to add to the date before calculating the first day of the month.

				  SELECT FDMONTH('02-08-2018');
				  -- Result: 2/1/2018

          SELECT FDMONTH('02-08-2018', 1) 
          --Result: 03/01/2018
				  

FDQUARTER(date)

Returns the first day of the quarter of the given date part.

• date: The datetime string that specifies the date.
• quarters to add: An optional integer expression specifying the number of months to add to the date before calculating the first day of the quarter.

				  SELECT FDQUARTER('05-08-2018');
				  -- Result: 4/1/2018

          SELECT FDQUARTER('05-08-2018',1)
          --Result: 07/01/2018
				  

FILEMODIFIEDTIME(uri)

Returns the time stamp associated with the Date Modified of the relevant file.

• uri: An absolute path pointing to a file on the local file system.

				 SELECT FILEMODIFIEDTIME('C:/Documents/myfile.txt');
				 -- Result: 6/25/2019 10:06:58 AM
				 

FROM_DAYS(datevalue)

Returns a date derived from the number of days after 1582-10-15 (based upon the Gregorian calendar). This will be equivalent to the MYSQL FROM_DAYS function.

• datevalue: A integer value representing the number of days since 1582-10-15.

				SELECT FROM_DAYS(736000);
				-- Result: 2/6/2015
				

FROM_UNIXTIME(time, issecond)

Returns a representation of the unix_timestamp argument as a value in YYYY-MM-DD HH:MM:SS expressed in the current time zone.

• time: The time stamp value from epoch time. Milliseconds are accepted.
• issecond: Indicates the time stamp value is milliseconds to epoch time.

                      SELECT FROM_UNIXTIME(1540495231, 1);
                      -- Result: 2018-10-25 19:20:31

                      SELECT FROM_UNIXTIME(1540495357385, 0);
                      -- Result: 2018-10-25 19:22:37
                    

GETDATE()

Returns the current time stamp of the database system as a datetime value. This value is equal to CURRENT_TIMESTAMP and SYSDATETIME, and is always in the local timezone.

                  SELECT GETDATE();
                  -- Result: 2018-02-01 03:04:05
                

GETUTCDATE()

Returns the current time stamp of the database system formatted as a UTC datetime value. This value is equal to SYSUTCDATETIME.

In addition, GETUTCDATE can take an optional second parameter, a date and time that are converted to UTC.

                  SELECT GETUTCDATE();
                  -- For example, if the local timezone is Eastern European Time (GMT+2)
                  -- Result: 2018-02-01 05:04:05

                  SELECT GETUTCDATE('2020/08/31 13:56:00')
                  --Result: '2020-08-31 17:56:00'
                

HOUR(date)

Returns the hour component from the provided datetime.

• date: The datetime string that specifies the date.

				SELECT HOUR('02-02-2020 11:30:00');
				-- Result: 11
				

ISDATE(date, [date_format])

Returns 1 if the value is a valid date, time, or datetime value; otherwise, 0.

• date: The datetime string.
• date_format: The optional datetime format.

                      SELECT ISDATE('2018-02-01', 'yyyy-MM-dd');
                      -- Result: 1

                      SELECT ISDATE('Not a date');
                      -- Result: 0
                    

LAST_WEEK()

Returns a time stamp equivalent to exactly one week before the current date.

				SELECT LAST_WEEK();	//Assume the date is 3/17/2020	
			 -- Result: 3/10/2020 00:00:00
				

LAST_MONTH()

Returns a time stamp equivalent to exactly one month before the current date.

	
				SELECT LAST_MONTH(); //Assume the date is 3/17/2020
				-- Result: 2/17/2020 00:00:00
				

LAST_YEAR()

Returns a time stamp equivalent to exactly one year before the current date.

				SELECT LAST_YEAR();	//Assume the date is 3/17/2020	
				-- Result: 3/10/2019 00:00:00
				

LDWEEK(date)

Returns the last day of the provided week.

• date: The datetime string.
• weeks to add: An optional integer expression specifying the number of months to add to the date before calculating the last day of the week.

				SELECT LDWEEK('02-02-2020');
				-- Result: 2/8/2020
				

LDMONTH(date)

Returns the last day of the provided month.

• date: The datetime string.
• months to add: An optional integer expression specifying the number of months to add to the date before calculating the last day of the month.

				SELECT LDMONTH('02-02-2020');
				-- Result: 2/29/2020

        SELECT LDMONTH('02-08-2020', 1)
        --Result: 03/31/2020
				

LDQUARTER(date)

Returns the last day of the provided quarter.

• date: The datetime string.
• quarters to add: An optional integer expression specifying the number of months to add to the date before calculating the last day of the quarter.

				SELECT LDQUARTER('02-02-2020');
				-- Result: 3/31/2020

        SELECT LDQUARTER('02-02-2020',1)
        --Result: 06/30/2020
				

MAKEDATE(year, days)

Returns a date value from a year and a number of days.

• year: The year
• days: The number of days into the year. Value must be greater than 0.

          SELECT MAKEDATE(2020, 1);
          -- Result: 2020-01-01
        

MINUTE(date)

Returns the minute component from the provided datetime.

• date: The datetime string that specifies the date.

				SELECT MINUTE('02-02-2020 11:15:00');
				-- Result: 15
				

MONTH(date)

Returns the month component from the provided datetime.

• date: The datetime string that specifies the date.

				SELECT MONTH('02-02-2020');
				-- Result: 2
				

QUARTER(date)

Returns the quarter associated with the provided datetime.

• date: The datetime string that specifies the date.

				SELECT QUARTER('02-02-2020');
				-- Result: 1
				

SECOND(date)

Returns the second component from the provided datetime.

• date: The datetime string that specifies the date.

				SELECT SECOND('02-02-2020 11:15:23');
				-- Result: 23
				

SMALLDATETIMEFROMPARTS(integer_year, integer_month, integer_day, integer_hour, integer_minute)

Returns the datetime value for the specified date and time.

• year: The integer expression specifying the year.
• month: The integer expression specifying the month.
• day: The integer expression specifying the day.
• hour: The integer expression specifying the hour.
• minute: The integer expression specifying the minute.

                      SELECT SMALLDATETIMEFROMPARTS(2018, 2, 1, 1, 2);
                      -- Result: 2018-02-01 01:02:00
                    

STRTODATE(string,format)

Parses the provided string value and returns the corresponding datetime.

• string: The string value to be converted to datetime format.
• format: A format string which describes how to interpret the first string input. A few special formats are available as well, including UNIX, UNIXMILIS, TICKS, and FILETICKS.

				SELECT STRTODATE('03*04*2020','dd*MM*yyyy');
				-- Result: 4/3/2020
				

SYSDATETIME()

Returns the current time stamp as a datetime value of the database system. It is equal to GETDATE and CURRENT_TIMESTAMP, and is always in the local timezone.

                  SELECT SYSDATETIME();
                  -- Result: 2018-02-01 03:04:05
                

SYSUTCDATETIME()

Returns the current system date and time as a UTC datetime value. It is equal to GETUTCDATE.

                  SELECT SYSUTCDATETIME();
                  -- For example, if the local timezone is Eastern European Time (GMT+2)
                  -- Result: 2018-02-01 05:04:05
                

TIMEFROMPARTS(integer_hour, integer_minute, integer_seconds, integer_fractions, integer_precision)

Returns the time value for the specified time and with the specified precision.

• hour: The integer expression specifying the hour.
• minute: The integer expression specifying the minute.
• seconds: The integer expression specifying the seconds.
• fractions: The integer expression specifying the fractions of the second.
• precision : The integer expression specifying the precision of the fraction.

                      SELECT TIMEFROMPARTS(1, 2, 3, 456, 3);
                      -- Result: 01:02:03.456
                    

TO_DAYS(date)

Returns the number of days since 0000-00-01. This will only return a value for dates on or after 1582-10-15 (based upon the Gregorian calendar). This will be equivalent to the MYSQL TO_DAYS function.

• date: The datetime string that specifies the date.

				SELECT TO_DAYS('02-06-2015');
				-- Result: 736000
				

WEEK(date)

Returns the week (of the year) associated with the provided datetime.

• date: The datetime string that specifies the date.

				SELECT WEEK('02-17-2020 11:15:23');
				-- Result: 8
				

YEAR(date)

Returns the integer that specifies the year of the specified date.

• date: The datetime string.

                      SELECT YEAR('2018-02-01');
                      -- Result: 2018
                    

The following date literal functions can be used to filter date fields using relative intervals. Note that while the <, >, and = operators are supported for these functions, <= and >= are not.

L_TODAY()

The current day.

  SELECT * FROM MyTable WHERE MyDateField = L_TODAY()

L_YESTERDAY()

The previous day.

  SELECT * FROM MyTable WHERE MyDateField = L_YESTERDAY()

L_TOMORROW()

The following day.

  SELECT * FROM MyTable WHERE MyDateField = L_TOMORROW()

L_LAST_WEEK()

Every day in the preceding week.

  SELECT * FROM MyTable WHERE MyDateField = L_LAST_WEEK()

L_THIS_WEEK()

Every day in the current week.

  SELECT * FROM MyTable WHERE MyDateField = L_THIS_WEEK()

L_NEXT_WEEK()

Every day in the following week.

  SELECT * FROM MyTable WHERE MyDateField = L_NEXT_WEEK()

Also available:

• L_LAST/L_THIS/L_NEXT MONTH
• L_LAST/L_THIS/L_NEXT QUARTER
• L_LAST/L_THIS/L_NEXT YEAR

L_LAST_N_DAYS(n)

The previous n days, excluding the current day.

  SELECT * FROM MyTable WHERE MyDateField = L_LAST_N_DAYS(3)

L_NEXT_N_DAYS(n)

The following n days, including the current day.

  SELECT * FROM MyTable WHERE MyDateField = L_NEXT_N_DAYS(3)

Also available:

• L_LAST/L_NEXT_90_DAYS

L_LAST_N_WEEKS(n)

Every day in every week, starting n weeks before current week, and ending in the previous week.

  SELECT * FROM MyTable WHERE MyDateField = L_LAST_N_WEEKS(3)

L_NEXT_N_WEEKS(n)

Every day in every week, starting the following week, and ending n weeks in the future.

  SELECT * FROM MyTable WHERE MyDateField = L_NEXT_N_WEEKS(3)

Also available:

• L_LAST/L_NEXT_N_MONTHS(n)
• L_LAST/L_NEXT_N_QUARTERS(n)
• L_LAST/L_NEXT_N_YEARS(n)

A SELECT statement can consist of the following basic clauses.

• SELECT
• INTO
• FROM
• JOIN
• WHERE
• GROUP BY
• HAVING
• UNION
• ORDER BY
• LIMIT

SELECT Syntax

The following syntax diagram outlines the syntax supported by the SQL engine of the connector:

SELECT {
  [ TOP <numeric_literal> | DISTINCT ]
  { 
    * 
    | { 
        <expression> [ [ AS ] <column_reference> ] 
        | { <table_name> | <correlation_name> } .* 
      } [ , ... ] 
  }
  { 
    FROM <table_reference> [ [ AS ] <identifier> ] 
  } [ , ... ]
  [ [  
      INNER | { { LEFT | RIGHT | FULL } [ OUTER ] } 
    ] JOIN <table_reference> [ ON <search_condition> ] [ [ AS ] <identifier> ] 
  ] [ ... ] 
  [ WHERE <search_condition> ]
  [ GROUP BY <column_reference> [ , ... ]
  [ HAVING <search_condition> ]
  [ UNION [ ALL ] <select_statement> ]
  [ 
    ORDER BY 
    <column_reference> [ ASC | DESC ] [ NULLS FIRST | NULLS LAST ]
  ]
  [ 
    LIMIT <expression>
    [ 
      { OFFSET | , }
      <expression> 
    ]
  ] 
}

<expression> ::=
  | <column_reference>
  | @ <parameter> 
  | ?
  | COUNT( * | { [ DISTINCT ] <expression> } )
  | { AVG | MAX | MIN | SUM | COUNT } ( <expression> ) 
  | NULLIF ( <expression> , <expression> ) 
  | COALESCE ( <expression> , ... ) 
  | CASE <expression>
      WHEN { <expression> | <search_condition> } THEN { <expression> | NULL } [ ... ]
    [ ELSE { <expression> | NULL } ]
    END 
  | {RANK() | DENSE_RANK()} OVER ([PARTITION BY <column_reference>] {ORDER BY <column_reference>})
  | <literal>
  | <sql_function> 

<search_condition> ::= 
  {
    <expression> { = | > | < | >= | <= | <> | != | LIKE | NOT LIKE | IN | NOT IN | IS NULL | IS NOT NULL | AND | OR | CONTAINS | BETWEEN | IS DISTINCT FROM | IS NOT DISTINCT FROM } [ <expression> ]
  } [ { AND | OR } ... ] 

Examples

1. Return all columns:
   

   SELECT * FROM Files

2. Rename a column:
   

   SELECT [Name] AS MY_Name FROM Files

3. Cast a column's data as a different data type:
   

   SELECT CAST(Size AS VARCHAR) AS Str_Size FROM Files

4. Search data:
   

   SELECT * FROM Files WHERE Id = 'Jq74mCczmFXk1tC10GB'

5. Return the number of items matching the query criteria:
   

   SELECT COUNT(*) AS MyCount FROM Files 

6. Return the number of unique items matching the query criteria:
   

   SELECT COUNT(DISTINCT Name) FROM Files 

7. Return the unique items matching the query criteria:
   

   SELECT DISTINCT Name FROM Files 

8. Sort a result set in ascending order:
   

   SELECT Id, Name FROM Files  ORDER BY Name ASC

9. Restrict a result set to the specified number of rows:
   

   SELECT Id, Name FROM Files LIMIT 10 

10. Parameterize a query to pass in inputs at execution time. This enables you to create prepared statements and mitigate SQL injection attacks.
    

    SELECT * FROM Files WHERE Id = @param

See Explicitly Caching Data for information on using the SELECT statement in offline mode.

Pseudo Columns

Some input-only fields are available in SELECT statements. These fields, called pseudo columns, do not appear as regular columns in the results, yet may be specified as part of the WHERE clause. You can use pseudo columns to access additional features from Microsoft OneDrive.

    SELECT * FROM Files WHERE Pseudo = '@Pseudo'
    

Aggregate Functions

For SELECT examples using aggregate functions, see Aggregate Functions.

JOIN Queries

See JOIN Queries for SELECT query examples using JOINs.

Date Literal Functions

Date Literal Functions contains SELECT examples with date literal functions.

Window Functions

See Window Functions for SELECT examples containing window functions.

Table-Valued Functions

See Table-Valued Functions for SELECT examples with table-valued functions.

COUNT

Returns the number of rows matching the query criteria.

SELECT COUNT(*) FROM Files WHERE Id = 'Jq74mCczmFXk1tC10GB'

COUNT(DISTINCT)

Returns the number of distinct, non-null field values matching the query criteria.

SELECT COUNT(DISTINCT Id) AS DistinctValues FROM Files WHERE Id = 'Jq74mCczmFXk1tC10GB'

AVG

Returns the average of the column values.

SELECT Name, AVG(Size) FROM Files WHERE Id = 'Jq74mCczmFXk1tC10GB'  GROUP BY Name

MIN

Returns the minimum column value.

SELECT MIN(Size), Name FROM Files WHERE Id = 'Jq74mCczmFXk1tC10GB' GROUP BY Name

MAX

Returns the maximum column value.

SELECT Name, MAX(Size) FROM Files WHERE Id = 'Jq74mCczmFXk1tC10GB' GROUP BY Name

SUM

Returns the total sum of the column values.

SELECT SUM(Size) FROM Files WHERE Id = 'Jq74mCczmFXk1tC10GB'

The CData Python Connector for Microsoft OneDrive supports standard SQL joins like the following examples.

Inner Join

An inner join selects only rows from both tables that match the join condition:

SELECT Files.name, SharedResources.shared_scope FROM Files, SharedResources WHERE Files.id=SharedResources.id

Left Join

A left join selects all rows in the FROM table and only matching rows in the JOIN table:

SELECT Files.name, SharedResources.shared_scope FROM Files LEFT OUTER JOIN SharedResources ON Files.id=SharedResources.id

Window functions allow you to create computed fields from a group of rows (a window) that return a result for each row, as opposed to one computed result for a set of rows, as is the case with aggregate functions. The connector supports the following window function syntax.

Note: Window function support is an experimental feature of the connector. This functionality extends beyond the connector's core scope of being SQL-92 compliant. As such, performance with window functions may not be optimal.

Window Function Clauses

OVER

The OVER clause defines the window over which window functions are performed.

SELECT A, B, <window function> OVER (<window frame>) FROM TableName

The <window function> refers to any supported window function clause, and the <window frame> refers to one or more clauses that specify the logic by which the window is defined.

PARTITION BY

The PARTITION BY clause subdivides a window into sub-windows called partitions. For each unique value in the column specified in the PARTITION BY clause, every record with that value collectively forms an individual partition.

SELECT A, B, <window function> OVER (PARTITION BY A ORDER BY B) From Files

The <window function> refers to any supported window function clause.

Window Functions

The connector supports math, ranking, and analytic window functions.

Math

These window functions perform mathematical operations on the records within the window.

COUNT()

Calculates the number of records in each partition. The calculated column is of the data type "int".

In each partition, every record will display the total number of records in that partition.

SELECT Name, Role, Earnings, COUNT() OVER (PARTITION BY Role) FROM Employees

COUNT_BIG()

Calculates the number of records in each partition. The calculated column is of the data type "bigint".

In each partition, every record will display the total number of records in that partition.

SELECT Name, Role, Earnings, COUNT_BIG() OVER (PARTITION BY Role) FROM Employees

MIN(numeric_column)

Calculates the minimum value of a numerical column per partition.

In each partition, every record will display the minimum value of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, MIN(Earnings) OVER (PARTITION BY Role) FROM Employees

MAX(numeric_column)

Calculates the maximum value of a numerical column per partition.

In each partition, every record will display the maximum value of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, MAX(Earnings) OVER (PARTITION BY Role) FROM Employees

SUM(numeric_column)

Calculates the sum of a numerical column per partition.

In each partition, every record will display the sum of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, SUM(Earnings) OVER (PARTITION BY Role) FROM Employees

AVG(numeric_column)

Calculates the average value of a numerical column per partition.

In each partition, every record will display the average value of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, AVG(Earnings) OVER (PARTITION BY Role) FROM Employees

MEDIAN(numeric_column)

Calculates the median value of a numerical column per partition.

In each partition, every record will display the median value of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, MEDIAN(Earnings) OVER (PARTITION BY Role) FROM Employees

STDEV(numeric_column)

Calculates the standard deviation of a numerical column per partition.

In each partition, every record will display the standard deviation of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, STDEV(Earnings) OVER (PARTITION BY Role) FROM Employees

STDEVP(numeric_column)

Calculates the population standard deviation of a numerical column per partition.

In each partition, every record will display the population standard deviation of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, STDEVP(Earnings) OVER (PARTITION BY Role) FROM Employees

VAR(numeric_column)

Calculates the statistical standard variance of a numerical column per partition.

In each partition, every record will display the statistical standard variance of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, VAR(Earnings) OVER (PARTITION BY Role) FROM Employees

VARP(numeric_column)

Calculates the variance population of a numerical column per partition.

In each partition, every record will display the variance population of numeric_column across the records in that partition.

SELECT Name, Role, Earnings, VARP(Earnings) OVER (PARTITION BY Role) FROM Employees

Ranking

These window functions rank records that fall within the window and its partitions.

RANK()

Assigns a rank number to each record in a window based on the value of the column specified in the required ORDER BY clause.

If two or more records have an equal value in the in ranked column, they all receive the same rank number and the rank count increments internally, skipping ahead one rank number for each record with a duplicate value in the ORDER BY column.

SELECT Id, Name, RANK() OVER (ORDER BY Name) AS Rank FROM Files

If you add a PARTITION BY clause, a separate set of ranks is calculated for each partition.

SELECT Id, Name, RANK() OVER (PARTITION BY Id ORDER BY Name) AS Rank FROM Files

DENSE_RANK()

Operates like the RANK() function, but it doesn't increment the internal rank counter for each record with a duplicate value in the ranked column.

This means that, while records with identical values in the ORDER BY column still share a rank number, the function never skips a rank number.

SELECT Id, Name, DENSE_RANK() OVER (PARTITION BY Id ORDER BY Name) AS Rank FROM Files

If you add a PARTITION BY clause, a separate set of ranks is calculated for each partition.

SELECT Id, Name, DENSE_RANK() OVER (PARTITION BY Id ORDER BY Name) AS Rank FROM Files

ROW_NUMBER()

Calculates a row number for each record. An ORDER BY clause in the OVER clause is required.

SELECT Name, Role, Earnings, ROW_NUMBER() OVER (ORDER BY Role) FROM Employees

If you define multiple partitions with PARTITION BY, a new set of row numbers are calculated for each partition.

SELECT Name, Role, Earnings, ROW_NUMBER() OVER (PARTITION BY Role ORDER BY Earnings) FROM Employees

NTILE()

Distributes rows of an ordered partition into a specified number of approximately equal groups, or buckets. It assigns each group a bucket number starting from one. For each row in a group, the NTILE() function assigns a bucket number representing the group to which the row belongs.

The syntax of NTILE() is:

NTILE(buckets) OVER (
    [PARTITION BY partition_expression, ... ]
    ORDER BY sort_expression [ASC | DESC], ...
)

The following are paramaters that NTILE() supports:

• buckets: The number of buckets into which the rows are divided. The buckets can be an expression or subquery that evaluates to a positive integer. It cannot be a window function.
• PARTITION BY: distributes rows of a result set into partitions to which the NTILE() function is applied.
• ORDER BY is clause that specifies the logical order of rows in each partition to which the NTILE() is applied.

If the number of rows is not divisible by the buckets, the NTILE() function returns groups of two sizes with the difference by one. The larger groups always precede the smaller group in the order set by ORDER BY in the OVER() clause.

If the total of rows is divisible by the number of buckets, the function divides the rows evenly among buckets. The following statement creates a new table named ntile_demo that stores 10 integers:

CREATE TABLE sales.ntile_demo (
	v INT NOT NULL
);
	
INSERT INTO sales.ntile_demo(v) 
VALUES(1),(2),(3),(4),(5),(6),(7),(8),(9),(10);	
	
SELECT * FROM sales.ntile_demo;

This statement uses the NTILE() function to divide ten rows into three groups:

SELECT 
	v, 
	NTILE (3) OVER (
		ORDER BY v
	) buckets
FROM 
	sales.ntile_demo;

Analytical

These window functions perform analytical operations on the records within the window.

PERCENT_RANK()

Calculates the relative rank SQL Percentile of each row. It returns values greater than zero, but the maximum value is one. It does not count any NULL values. This function is nondeterministic.

The syntax of PERCENT_RANK() is:

PERCENT_RANK() OVER (
      [PARTITION BY partition_expression, ... ]
      ORDER BY sort_expression [ASC | DESC], ...
  )
  

This syntax uses the following parameters.

• PARTITION BY: By default, SQL Server treats the whole data set as a single set. You can specify the PARTITION BY clause to divide data into multiple sets. The Percent_Rank function performs the analytical calculations on each set. This parameter is optional.
• ORDER BY: Sorts the data in either ascending or descending order. This parameter is required.

Table-valued functions are functions that return a table (rowset).

Note: Table-valued function support is an experimental feature of the connector. This functionality extends beyond the connector's core scope of being SQL-92 compliant. As such, performance with these functions may not be optimal.

Table-Valued Function Clauses

CROSS APPLY

The CROSS APPLY operator is used to perform a subquery on each row of a table or resultset produced by a preceding table expression.

<table_expression_1> CROSS APPLY <table_expression_2>

The second table expression can reference results from the first table expression to create derived columns or an altered recordset via a table-valued function.

Each resulting record is an instance of the record it's splitting, with all the same column values, except for the column(s) containing the value split by the function.

WITH

The WITH clause is used alongside certain table-valued functions to match against constructs within the structure being split (keys, element names, attribute names, etc.) and/or to specify metadata for the columns generated from the function.

SELECT A.ColumnName, X.DerivedColumnName FROM TableName A CROSS APPLY <table-valued function> WITH (DerivedColumnName varchar(255)) AS X

Table-Valued Functions

STRING_SPLIT(input_text,delimiter)

Takes each record in the recordset of the preceding table expression, splits the column containing delimiters (input_text) into substrings separated by the delimiter, and returns one record per substring.

• input_text: A column whose value you want to parse.
• delimiter: The character used to split the value of the column specified in input_text.

Suppose there is a column called "SplitColumn" with the following content:

One-Two-Three

To unpack this value across multiple records:

SELECT A.ID, X.Value FROM [TableWithDelimitedStringField] A CROSS APPLY STRING_SPLIT(A.SplitColumn,'-') WITH (Value VARCHAR(255)) AS X

-- Results:
-----------
|ID|Value|
|1|One|
|1|Two|
|1|Three|

JSONTABLE(json_content,[jsonpath])

For each record in the recordset of the preceding table expression, returns one record for each instance of a key in a JSON array (json_content) that matches the key(s) specified in the WITH clause, at the scope specified by the "jsonpath" input.

• json_content: A JSON "table" (array of objects). The contents can nest, but this must be a single JSON array, not any other JSON structure, at the root level.
  • The values of every instance of the key(s) provided in the WITH clause are retrievable only for substructures which are immediate children of the root-level JSON array.
• jsonpath: An optional JSONPath query defining the scope, within the json_content array, that you want to pull content from. The JSON key(s) identified in the WITH clause must exist at the scope defined in this parameter. This defaults to the JSON root ($).

Consider a sample table with a single record, including an ID column and column with JSON content called "JSONColumn" with the following content:

[
	{
		"name": "Samuel",
		"email": "sam@gmail.com",
		"extrainfo": {
			"city": "Seattle"
		}
	},
	{
		"name": "Katherine",
		"email": "kat@gmail.com",
	},
	{
		"name": "George",
		"email": "george23@gmail.com",
	},
	{
		"name": "Carlos",
		"email": "carlos32@gmail.com",
	}
]

To extract all values for a certain key, specify the scope in the JSONTABLE function and provide the desired key(s) in the WITH clause.

SELECT A.ID, X.name FROM [TableWithJSONField] A CROSS APPLY JSONTABLE(A.JSONColumn) WITH (name VARCHAR(255)) AS X

-- Results: 
|ID|name|
---------
|1 |Samuel|
|1 |Katherine|
|1 |George|
|1 |Carlos|

XMLTABLE(xml_content,[xpath,child_type])

For each record in the resultset of the preceding table expression, returns one record for each of the elements and/or attributes in an XML structure (xml_content) that match the tag name(s) and/or attribute name(s) specified in the WITH clause, at the scope specified in the "xpath" input.

• xml_content: A column containing an XML structure.
• xpath: An optional XPath that specifies the scope within the XML structure at which the connector extracts content matching the tag/attribute name(s) specified in the WITH clause.
  • When extracting the content of sub-elements, the connector can retrieve all content from tags at the root level, (depth 0) immediate children of the root (depth 1), and children of those children (depth 2).
  • When extracting element attribute content, the connector can retrieve all content from tags containing the specified attribute at the root level (depth 0) and from immediate children of root-level elements (depth 1).
• child_type: An optional parameter that specifies the part(s) of the parent element (specified in the xpath input) that the column(s) provided in the WITH clause are checked against to identify content.
  • You can supply the following values:
    • 0: The column(s) in the WITH clause are checked for matches against the parent element's attribute names and sub-element tag names.
    • 1: The column(s) in the WITH clause are checked for matches against the parent element's attribute names.
    • 2: The column(s) in the WITH clause are checked for matches against the parent element's sub-element tag names.
  • When not supplied, this defaults to 0.

Extracting Sub-Element Values

Consider a sample table with a single record, including an ID column and a column with XML content called "XMLContent" with the following content:

<shoppingList>
    <item>
        <name>Apples</name>
        <quantity>3</quantity>
        <unit>Kg</unit>
    </item>
    <item>
        <name>Bread</name>
        <quantity>2</quantity>
        <unit>Loaf</unit>
		<extrainfo>
			<Type>Whole-Grain</Type>
		</extrainfo>
    </item>
    <item>
        <name>Milk</name>
        <quantity>1</quantity>
        <unit>Carton</unit>
    </item>
    <item>
        <name>Eggs</name>
        <quantity>12</quantity>
        <unit></unit>
    </item>
</shoppingList>

To extract sub-element content, specify the scope in the XMLTABLE function and provide the desired element name(s) in the WITH clause. Note that this will not work if the XMLTABLE function's child_type input is set to 1.

SELECT A.ID, X.name FROM [TableWithXMLField] A CROSS APPLY XMLTABLE(A.XMLContent,'//*/item') WITH (name VARCHAR(255)) AS X

-- Results: 
|ID|name|
---------
|1|Apples|
|1|Bread|
|1|Milk|
|1|Eggs|

Extracting Values Using Element Tag Attributes

Suppose you have this sample table with a single record, including an ID column and a column with XML content called "XMLContent" with the following content:

<restaurant>
  <dish type="appetizer">
    <name lang="en">Caprese Salad</name>
    <chef>Chef Giovanni</chef>
    <price currency="USD">9.99</price>
  </dish>
  <dish type="main-course">
    <name lang="fr">Boeuf Bourguignon</name>
    <chef>Chef Marie</chef>
    <price currency="EUR">19.99</price>
  </dish>
  <dish type="dessert">
    <name lang="es">Tres Leches Cake</name>
    <chef>Chef Alejandro</chef>
    <price currency="MXN">89.99</price>
  </dish>
</restaurant>

To extract attribute content, specify the scope in the XMLTABLE function and provide the desired attribute name(s) in the WITH clause. Note that this will not work if the XMLTABLE function's child_type input is set to 2.

SELECT A.ID, X.type FROM [TableWithXMLField] A CROSS APPLY XMLTABLE(A.XMLContent,'//*/dish') WITH (type VARCHAR(255)) AS X

-- Results: 
|ID|type|
---------
|1|appetizer|
|1|main-course|
|1|dessert|

CSVTABLE(csv_content,[delimiter])

For each record in the resultset of the preceding table expression, reads from a column that contains a CSV table (csv_content) and for each record in that CSV table, returns one record containing the value of the CSV column(s) specified in the WITH clause.

• csv_content: A column containing a CSV table.
• delimiter: An optional custom delimiter (instead of a comma) which splits the CSV content contained in the csv_content input.

Consider a sample table with a single record, including an ID column and a column containing CSV table called "CSVContent" with the following content:

Name;Category;Price
Apple;Fruit;0.99
Spaghetti;Pasta;5.49
Chicken Breast;Meat;8.99
Broccoli;Vegetable;2.49

To select every value in the "Name" column and account for the custom delimiter (;):

SELECT A.ID, X.Name FROM [TableWithCSVField] A CROSS APPLY CSVTABLE(A.CSVContent,';') WITH (Name VARCHAR(255)) AS X

-- Results:
|ID|Name|
-----------
|1|Apple|
|1|Spaghetti|
|1|Chicken Breast|
|1|Broccoli|

When caching is enabled, CACHE statements provide complete control over the data that is cached and the table to which it is cached. The CACHE statement executes the SELECT statement specified and caches its results to a table with the same name in the cache database or to table specified in <cached_table_name>. The connector updates or inserts rows to the cache depending on whether or not they already exist in the cache, so the primary key, which is used to identify existing rows, must be included in the selected columns.

See Caching Data for more information on different caching strategies.

CACHE Statement Syntax

The cache statement may include the following options that alter its behavior:

CACHE [ <cached_table_name> ] [ WITH TRUNCATE | AUTOCOMMIT | SCHEMA ONLY | DROP EXISTING | ALTER SCHEMA ] <select_statement> 

WITH TRUNCATE

If this option is set, the connector removes existing rows in the cache table before adding the selected rows. Use this option if you want to refresh the entire cache table but keep its existing schema.

AUTOCOMMIT

If this option is set, the connector commits each row individually. Use this option if you want to ignore the rows that could not be cached due to some reason. By default, the entire result set is cached as a single transaction.

DROP EXISTING

If this option is set, the connector drops the existing cache table before caching the new results. Use this option if you want to refresh the entire cache table, including its schema.

SCHEMA ONLY

If this option is set, the connector creates the cache table based on the SELECT statement without executing the query.

ALTER SCHEMA

If this option is set, the connector alters the schema of the existing table in the cache if it does not match the schema of the SELECT statement. This option results in new columns or dropped columns, if the schema of the SELECT statement does not match the cached table.

Common Queries

Use the following cache statement to cache all rows of a table:

CACHE SELECT * FROM Files

Use the following cache statement to cache all rows of a table into the cache table CachedFiles:

CACHE CachedFiles SELECT * FROM Files

Use the following cache statement for incremental caching. The DateModified column may not exist in all tables. The cache statement shows how incremental caching would work if there were such a column. Also, notice that, in this case, the WITH TRUNCATE and DROP EXISTING options are specifically omitted, which would have deleted all existing rows.

CACHE CachedFiles SELECT * FROM Files WHERE DateModified > '2013-04-04'

Use the following cache statements to create a table with all available columns that will then cache only a few of them. The sequence of statements cache only Id and Name even though the cache table CachedFiles has all the columns in Files.

CACHE CachedFiles SCHEMA ONLY SELECT * FROM Files
CACHE CachedFiles SELECT Id, Name FROM Files

To execute stored procedures, you can use EXECUTE or EXEC statements.

EXEC and EXECUTE assign stored procedure inputs, referenced by name, to values or parameter names.

Stored Procedure Syntax

To execute a stored procedure as an SQL statement, use the following syntax:

 
{ EXECUTE | EXEC } <stored_proc_name> 
{
  [ @ ] <input_name> = <expression>
} [ , ... ]

<expression> ::=
  | @ <parameter> 
  | ?
  | <literal>

Example Statements

Reference stored procedure inputs by name:

EXECUTE my_proc @second = 2, @first = 1, @third = 3;

Execute a parameterized stored procedure statement:

EXECUTE my_proc second = @p1, first = @p2, third = @p3; 

PIVOT and UNPIVOT can be used to change a table-valued expression into another table.

PIVOT

PIVOT rotates a table-value expression by turning unique values from one column into multiple columns in the output. PIVOT can run aggregations where required on any column value.

PIVOT Synax

 
"SELECT 'AverageCost' AS Cost_Sorted_By_Production_Days, [0], [1], [2], [3], [4]
FROM
(
SELECT DaysToManufacture, StandardCost
FROM Production.Product
) AS SourceTable
PIVOT
(
AVG(StandardCost)
FOR DaysToManufacture IN ([0], [1], [2], [3], [4])
) AS PivotTable;"

UNPIVOT

UNPIVOT carries out nearly the opposite to PIVOT by rotating columns of a table-valued expressions into column values.

UNPIVOT Sytax

 
"SELECT VendorID, Employee, Orders
FROM
(SELECT VendorID, Emp1, Emp2, Emp3, Emp4, Emp5
FROM pvt) p
UNPIVOT
(Orders FOR Employee IN
(Emp1, Emp2, Emp3, Emp4, Emp5)
)AS unpvt;"

For further information on PIVOT and UNPIVOT, see FROM clause plus JOIN, APPLY, PIVOT (Transact-SQL)

The CData Python Connector for Microsoft OneDrive models Microsoft OneDrive objects as an easy-to-use SQL database, using views and stored procedures. These are defined in schema files, which are simple, easy-to-read text files that define the structure and organization of data. Because the table definitions are dynamically retrieved, any changes to the remote data are immediately reflected in your queries.

Views

The Views section, which lists read-only SQL tables, contains samples from an example OneDrive site. Your data model is obtained dynamically based on your user credentials and OneDrive site.

The sample site includes the following views:

View	Description
Drives	Displays all OneDrive drives accessible to the current user, including personal and shared drives
Files	Provides detailed information about individual files stored in OneDrive drives, including name, size, and metadata.
FileVersions	Tracks the version history of each file in OneDrive, allowing review or rollback of previous file states.
Folders	Lists all folders within a OneDrive drive, useful for navigation and hierarchical organization analysis.
GroupMembers	Displays a list of users assigned to each group, helping manage team or access group memberships.
Groups	Shows all security and distribution groups within the connected Microsoft 365 tenant, enabling administrative oversight.
Permissions	Details sharing and access permissions for files and folders within a OneDrive drive, identifying owners and collaborators.
SharedResources	Identifies all files and folders that have been shared from OneDrive, along with recipients and access levels.
Users	Lists users with OneDrive accounts in the organization, including user identifiers and profile details.

Stored Procedures

Stored Procedures are SQL scripts that extend beyond standard CRUD operations. They can be used to search, update, and modify information in OneDrive.

Views are similar to tables in the way that data is represented; however, views are read-only.

Queries can be executed against a view as if it were a normal table.

CData Python Connector for Microsoft OneDrive Views

Name	Description
Drives	Displays all OneDrive drives accessible to the current user, including personal and shared drives.
Files	Provides detailed information about individual files stored in OneDrive drives, including name, size, and metadata.
FileVersions	Tracks the version history of each file in OneDrive, allowing review or rollback of previous file states.
Folders	Lists all folders within a OneDrive drive, useful for navigation and hierarchical organization analysis.
GroupMembers	Lists the members of the group.
Groups	Shows all security and distribution groups within the connected Microsoft 365 tenant, enabling administrative oversight.
Permissions	Details sharing and access permissions for files and folders within a OneDrive drive, identifying owners and collaborators.
SensitivityLabels	Lists available sensitivity labels in the Azure environment.
SharedResources	Identifies all files and folders that have been shared from OneDrive, along with recipients and access levels.
Users	Lists users with OneDrive accounts in the organization, including user identifiers and profile details.

Displays all OneDrive drives accessible to the current user, including personal and shared drives.

View-Specific Information

UserId and GroupId connection properties can also be used to filter records. If both are included in the connection string, UserId takes precedence over GroupId.

To filter drives for a specific user:

SELECT * FROM Drives WHERE UserId = 'a9920804-3212-4f9d-aac7-f55c697fa2bc'

To filter drives for a specific group:

SELECT * FROM Drives WHERE GroupId = '0a98c469-e041-4d3b-91b5-0966e5200081'

Due to API limitations, all operators on this view are executed client-side. This means the connector retrieves all available records from the API before applying any filters, which may impact performance for large datasets.

Columns

Name	Type	References	Description
driveType	String		Specifies the classification of the OneDrive drive, such as personal, business, or documentLibrary.
owner_application_displayName	String		The human-readable name of the application that owns or created the drive.
owner_application_id	String		The unique ID assigned to the application that owns or manages the drive.
quota_deleted	Long		The total number of bytes used by deleted items that are still retained in the recycle bin or recovery folder.
quota_remaining	Long		The total number of bytes still available for use in the drive's allocated storage limit.
quota_state	String		The current status of the drive's storage capacity, such as normal, nearing, or exceeded.
quota_storagePlanInformation_upgradeAvailable	Bool		Specifies whether the user is eligible to upgrade their current storage plan based on available tiers.
quota_total	Long		The maximum number of bytes allocated to the drive under the user's current storage plan.
quota_used	Long		The total number of bytes currently used in the drive, including active and deleted content.
sharePointIds_listId	String		The identifier of the SharePoint list associated with the current item, if applicable.
sharePointIds_listItemId	String		The unique numeric identifier of a specific item within a SharePoint list.
sharePointIds_listItemUniqueId	String		The globally unique identifier assigned to the list item within the SharePoint environment.
sharePointIds_siteId	String		The identifier of the SharePoint site that contains the list or library associated with the current item.
sharePointIds_siteUrl	String		The full URL of the SharePoint site that hosts the associated list or document library.
sharePointIds_tenantId	String		The Microsoft 365 tenant identifier that owns the SharePoint site where the list or item is stored.
sharePointIds_webId	String		The identifier of the SharePoint web (subsite) that contains the associated list or item.
Linkedfollowing	String		A hyperlink to items or folders in OneDrive that the user is actively following for updates or collaboration.
Linkeditems	String		A hyperlink to the child items contained within a folder or parent item in OneDrive.
Linkedlist	String		A hyperlink that navigates to the SharePoint list which contains the current item.
Linkedroot	String		A hyperlink to the root directory of the drive, representing the top-level folder or entry point.
Linkedspecial	String		A hyperlink to system-defined special folders including Documents, Photos, Camera Roll, or similar.
ParentReference	String		A reference object containing metadata about the immediate parent item or folder of the current item.
Id [KEY]	String		A system-generated unique string that identifies the item within the drive.
Name	String		The file or folder name as it appears in OneDrive, including its original casing and formatting.
Description	String		A user-defined or system-generated description that provides context about the item's contents or purpose.
owner_user_id	String		The unique identifier of the OneDrive user who owns or created the drive instance.

Provides detailed information about individual files stored in OneDrive drives, including name, size, and metadata.

View-Specific Information

Select

SQL projection is performed server-side. In addition, queries that use the primary key Id with an IN filter are also executed server-side. For example:

SELECT Id, Name, audio_album, audio_title FROM Files WHERE Id IN ('B1E6BJ084A9133KB1!101', 'APF9D2K6WFA524Y') 

Include ParentReference_DriveId and ParentReference_Id in the WHERE clause to get the result for a particular folder. For example:

 SELECT * FROM Files WHERE  ParentReference_DriveId = 'b!3Yqza-5FJ0usfhyH-2QafkQpf0OC0jlNh8LAETWPK6dNROPDScevTKbV-drnCFHV' And ParentReference_id = '01QFG2V52Z62HOXS5F6RHIHVT36T3Q5GKH' 

Server-side filtering using ParentReference_Id is supported on the root drive when the AuthScheme property is set to AzureAD. However, it is not available for client-credential authentication. For example:

 SELECT * FROM Files WHERE ParentReference_id = '01QFG2V52Z62HOXS5F6RHIHVT36T3Q5GKH' 

For server-side filtering using ParentReference_Id with client-credential authentication, such as AzureServicePrincipal or AzureServicePrincipalCert, the createdBy_user_id column is required. For example:

 SELECT * FROM Files WHERE ParentReference_id = '01QFG2V52Z62HOXS5F6RHIHVT36T3Q5GKH' AND createdBy_user_id = '1c67f23f-8681-4c67-9c19-253e628442d5' 

UserId and GroupId connection properties can also be used to filter records. If both are included in the connection string, UserId takes precedence over GroupId.

To filter files for a specific user:

SELECT * FROM Files WHERE UserId = 'a9920804-3212-4f9d-aac7-f55c697fa2bc'

To filter files for a specific group:

SELECT * FROM Files WHERE GroupId = '0a98c469-e041-4d3b-91b5-0966e5200081'

File Listing

File listing is performed recursively based on the DirectoryRetrievalDepth property. By default, this property is set to 5, which means the connector retrieves data only for the first six levels of the selected drive. This is because level 1 corresponds to a DirectoryRetrievalDepth of 0. You can set the value to -1 to retrieve all the files in the drive, regardless of their depth.

Files can be listed in this view, and their contents can be accessed using stored procedures such as:

• CopyResource: Copies a file/folder from one directory in your drive to another.
• DeleteResource: Deletes a file/folder from your drive.
• DownloadFile: Downloads an existing file from your drive.
• MoveResource: Moves a file/folder from one directory in your drive to another.
• UploadFile: Uploads a new file or update content to an existing file.

Columns

Name	Type	References	Description
id [KEY]	String		Unique identifier of the file item within the OneDrive drive.
Etag	String		Entity tag for tracking changes to the file; used for concurrency control.
createdBy_user_id	String		Identifier of the user who originally created the file.
createdBy_user_displayName	String		Display name of the user who created the file.
lastModifiedBy_user_id	String		Identifier of the user who last modified the file.
lastModifiedBy_user_displayName	String		Display name of the user who last modified the file.
ResourceType	String		Specifies the type of resource represented, such as file or folder.
createdBy_user_email	String		Email of the user who created the file.
lastModifiedBy_user_email	String		Email of the user who last modified the file.
createdBy_application_displayName	String		Name of the application that created the file.
createdBy_application_id	String		Unique ID of the application that created the file.
createdDateTime	Datetime		Timestamp when the file was initially created.
description	String		User-defined or system-generated description of the file's purpose or contents.
lastModifiedBy_application_displayName	String		Name of the application that last modified the file.
lastModifiedBy_application_id	String		Unique ID of the application that last modified the file.
lastModifiedDateTime	Datetime		Timestamp of the most recent modification to the file.
name	String		The file's name as it appears in OneDrive.
parentReference_driveId	String		ID of the parent drive containing the file.
parentReference_driveType	String		Type of the parent drive, such as personal or documentLibrary.
parentReference_id	String		Unique ID of the parent folder or item.
parentReference_name	String		Name of the parent folder or item.
parentReference_path	String		File system path of the parent item within OneDrive.
webUrl	String		Direct URL to access the file via a web browser.
audio_album	String		Name of the album the audio file belongs to.
audio_albumArtist	String		Name of the album artist associated with the audio file.
audio_artist	String		Primary artist of the audio file.
audio_bitrate	Long		Bitrate of the audio file in bits per second.
audio_composers	String		Comma-separated list of composers (for example, John Williams, Hans Zimmer, or Ennio Morricone).
audio_copyright	String		Copyright information associated with the audio file.
audio_disc	Int		Disc number the track is from, if part of a multi-disc album.
audio_discCount	Int		Total number of discs in the audio collection.
audio_duration	Long		Duration of the audio file in milliseconds.
audio_genre	String		Genre of the audio file content, such as Rock, Jazz, or Classical.
audio_hasDrm	Bool		Indicates whether the audio file is protected by digital rights management.
audio_isVariableBitrate	Bool		Specifies whether the audio file uses variable bitrate encoding.
audio_title	String		Title of the audio track.
audio_track	Int		Track number of the audio file on the disc.
audio_trackCount	Int		Total number of tracks in the audio collection or album.
audio_year	Int		Year the audio file was published or recorded.
cTag	String		Change tag used to detect updates to the file or folder.
file_hashes_crc32Hash	String		CRC32 checksum used for data validation of the file.
file_hashes_quickXorHash	String		QuickXor hash for efficient change detection in Office files.
file_hashes_sha1Hash	String		SHA-1 cryptographic hash of the file.
file_hashes_sha256Hash	String		SHA-256 cryptographic hash of the file.
file_mimeType	String		MIME type of the file.
fileSystemInfo_createdDateTime	Datetime		Filesystem timestamp indicating when the file was created.
fileSystemInfo_lastModifiedDateTime	Datetime		Filesystem timestamp of the last time the file was modified.
folder_childCount	Int		Number of items directly within the folder, if the item is a folder.
image_height	Int		Height of the image in pixels.
image_width	Int		Width of the image in pixels.
location_altitude	Double		Altitude at which the photo or file was captured, in meters.
location_latitude	Double		Latitude coordinate of where the photo or file was captured.
location_longitude	Double		Longitude coordinate of where the photo or file was captured.
photo_cameraMake	String		Manufacturer of the camera used to take the photo.
photo_cameraModel	String		Model of the camera used to capture the photo.
photo_exposureDenominator	Double		Denominator of the exposure time ratio used to capture the photo.
photo_exposureNumerator	Double		Numerator of the exposure time ratio used to capture the photo.
photo_fNumber	Double		Aperture setting (f-number) used when the photo was taken.
photo_focalLength	Double		Focal length of the lens in millimeters.
photo_iso	Int		ISO sensitivity setting used when the photo was taken.
photo_orientation	Int		Numeric value representing the photo's orientation (for example, 1 for normal, 3 for rotated 180).
photo_takenDateTime	Datetime		Date and time when the photo was captured.
publication_checkedOutBy_application_displayName	String		Display name of the user who checked out the file.
publication_checkedOutBy_application_id	String		Identifier of the user who checked out the file.
publication_level	String		The publication visibility level, such as checkout or published.
publication_versionId	String		Identifier for the published version of the file.
size	Long		Total size of the item in bytes, including metadata and content.
video_audioBitsPerSample	Int		Bits per audio sample in the video file.
video_audioChannels	Int		Number of audio channels in the video, typically 1 for mono or 2 for stereo.
video_audioFormat	String		Encoding format used for the audio stream in the video file.
video_audioSamplesPerSecond	Int		Sample rate for the video's audio stream, in hertz.
video_bitrate	Int		Total data rate of the video stream, measured in bits per second.
video_duration	Long		Playback duration of the video in milliseconds.
video_fourCC	String		Four-character code (FourCC) identifying the video codec (such as H264 or XVID).
video_frameRate	Double		Number of frames displayed per second in the video.
video_height	Int		Height of the video in pixels.
video_width	Int		Width of the video in pixels.

Tracks the version history of each file in OneDrive, allowing review or rollback of previous file states.

View-Specific Information

Select

The connector uses the Microsoft OneDrive API to process WHERE clause conditions built with the following columns and operator.

• FileId supports the = operator.
• DriveId supports the = operator.
• UserId supports the = operator.
• createdBy_user_id supports the = operator.

Note that the filter labeled 'createdBy_user_id' is required to execute the query successfully. For example:

SELECT * FROM FileVersions WHERE FileId = '01CYQN2MFPR6NIWVZNMNFL3SL4E3KF7IHY' AND DriveId = 'b!GrEGWax2VE-ssnJNr1E8llqoLptvK-BGjFRpceFzFg5Nwp9Bw2xbR62J0NAouP6z' AND createdBy_user_id = '472df319-2978-49d4-9445-9e7019def16f'

SELECT * FROM FileVersions WHERE FileId = '01CYQN2MFPR6NIWVZNMNFL3SL4E3KF7IHY' AND createdBy_user_id = '472df319-2978-49d4-9445-9e7019def16f'

SELECT * FROM FileVersions WHERE createdBy_user_id = '472df319-2978-49d4-9445-9e7019def16f'

Columns

Name	Type	References	Description
FileId [KEY]	String		Identifier of the original file to which this version belongs.
lastModifiedBy_user_displayName	String		Display name of the user who made the most recent modification to this file version.
lastModifiedBy_user_id	String		Unique identifier of the user who last modified this file version.
lastModifiedDateTime	Datetime		Timestamp indicating when this file version was last modified.
size	Long		Size of the file version in bytes.
id	String		Unique identifier assigned to this specific version of the file.
lastModifiedBy_user_email	String		Email address of the user who last modified this file version.
DriveId	String		Identifier of the OneDrive or SharePoint drive where the file version is stored.
publication_level	String		The publication state of the version, such as draft or published.
createdBy_user_id	String		Unique identifier of the user who originally created this version of the file.

Lists all folders within a OneDrive drive, useful for navigation and hierarchical organization analysis.

View-Specific Information

Select

Note: Use the CreateFolder stored procedure to create a new folder.

SQL projection is performed server-side. In addition, queries that use the primary key Id with an IN filter are also executed server-side. For example:

SELECT Id, Name, Size, Description FROM Folders WHERE Id IN ('B1E6BJ084A9133KB1!122', 'APF9D2K6WFAAPX9') 

Include ParentReference_DriveId and ParentReference_Id in the WHERE clause to get the result for a particular folder. For example:

 SELECT * FROM Folders WHERE  ParentReference_DriveId = 'b!3Yqza-5FJ0usfhyH-2QafkQpf0OC0jlNh8LAETWPK6dNROPDScevTKbV-drnCFHV' And ParentReference_id = '01QFG2V52Z62HOXS5F6RHIHVT36T3Q5GKH' 

Server-side filtering using ParentReference_Id is supported on the root drive when the AuthScheme property is set to AzureAD. However, it is not available for client-credential authentication. For example:

 SELECT * FROM Folders WHERE ParentReference_id = '01QFG2V52Z62HOXS5F6RHIHVT36T3Q5GKH' 

For server-side filtering using ParentReference_Id with client-credential authentication (such as AzureServicePrincipal or AzureServicePrincipalCert), the createdBy_user_id column is required. For example:

 SELECT * FROM Folders WHERE ParentReference_id = '01QFG2V52Z62HOXS5F6RHIHVT36T3Q5GKH' AND createdBy_user_id = '1c67f23f-8681-4c67-9c19-253e628442d5' 

UserId and GroupId connection properties can also be used to filter records. If both are included in the connection string, UserId takes precedence over GroupId.

To filter folders for a specific user:

SELECT * FROM Folder WHERE UserId = 'a9920804-3212-4f9d-aac7-f55c697fa2bc'

To filter folders for a specific group:

SELECT * FROM Folder WHERE GroupId = '0a98c469-e041-4d3b-91b5-0966e5200081'

Folder Listing

Folder listing is performed recursively using the DirectoryRetrievalDepth property. By default, this property is set to 5, which means it retrieves data for the first six levels of the selected drive. This is because the first level corresponds to a DirectoryRetrievalDepth of 0. You can set the value to -1 to retrieve all the folders in the drive, regardless of their depth.

Folders can be listed in this view, and their contents can be accessed using stored procedures such as:

• CopyResource: Copies a file/folder from one directory in your drive to another.
• DeleteResource: Deletes a file/folder from your drive.
• MoveResource: Moves a file/folder from one directory in your drive to another.

Columns

Name	Type	References	Description
id [KEY]	String		Unique identifier for the item.
Etag	String		Entity tag for the item used for concurrency control.
createdBy_user_id	String		ID of the user who created the item.
createdBy_user_displayName	String		Display name of the user who created the item.
lastModifiedBy_user_id	String		ID of the user who last modified the item.
lastModifiedBy_user_displayName	String		Display name of the user who last modified the item.
createdBy_application_displayName	String		Name of the application that created the item.
createdBy_application_id	String		ID of the application that created the item.
createdDateTime	Datetime		Timestamp when the item was created.
description	String		User-provided description of the item.
lastModifiedBy_application_displayName	String		Name of the application that last modified the item.
lastModifiedBy_application_id	String		ID of the application that last modified the item.
lastModifiedDateTime	Datetime		Timestamp of the last modification to the item.
name	String		Name of the item (file or folder).
parentReference_driveId	String		ID of the drive containing the parent item.
parentReference_driveType	String		Type of the drive (for example, personal, or business).
parentReference_id	String		ID of the parent item.
parentReference_name	String		Name of the parent item.
parentReference_path	String		Path to the parent item.
parentReference_shareId	String		Sharing ID associated with the parent item.
parentReference_sharepointIds_listId	String		SharePoint list ID associated with the parent item.
parentReference_sharepointIds_listItemId	String		SharePoint list item ID for the parent item.
parentReference_sharepointIds_listItemUniqueId	String		Unique SharePoint list item ID.
parentReference_sharepointIds_siteId	String		ID of the SharePoint site.
parentReference_sharepointIds_siteUrl	String		URL of the SharePoint site.
parentReference_sharepointIds_tenantId	String		Tenant ID for the SharePoint organization.
parentReference_sharepointIds_webId	String		Web ID of the SharePoint site.
parentReference_siteId	String		ID of the parent site (OneDrive/SharePoint).
webUrl	String		URL to access the item in a web browser.
LinkedcreatedByUser	String		Link to the user entity that created the item.
LinkedlastModifiedByUser	String		Link to the user entity that last modified the item.
audio_album	String		Album title of the audio file.
audio_albumArtist	String		Primary artist of the album.
audio_artist	String		Performer of the audio content.
audio_bitrate	Long		Bitrate of the audio in bits per second.
audio_composers	String		Composer(s) of the audio content.
audio_copyright	String		Copyright statement for the audio file.
audio_disc	Int		Disc number of the audio track.
audio_discCount	Int		Total number of discs in the album.
audio_duration	Long		Duration of the audio file in milliseconds.
audio_genre	String		Genre of the audio content.
audio_hasDrm	Bool		Indicates whether the audio file has digital rights management (DRM).
audio_isVariableBitrate	Bool		Indicates whether the audio uses variable bitrate encoding.
audio_title	String		Title of the audio track.
audio_track	Int		Track number on the album.
audio_trackCount	Int		Total number of tracks in the album.
audio_year	Int		Year the audio was released.
content	String		Base64 or encoded content of the item.
cTag	String		Change tag used for item versioning and sync detection.
deleted_state	String		The deletion status (for example, 'deleted', 'restored').
file_hashes_crc32Hash	String		CRC32 hash of the file content.
file_hashes_quickXorHash	String		QuickXor hash of the file content used by OneDrive.
file_hashes_sha1Hash	String		SHA-1 hash of the file content.
file_hashes_sha256Hash	String		SHA-256 hash of the file content.
file_mimeType	String		MIME type of the file (for example, 'application/pdf').
file_processingMetadata	Bool		Indicates whether the file has additional processing metadata (for example, indexing).
fileSystemInfo_createdDateTime	Datetime		Timestamp when the file was created in the file system.
fileSystemInfo_lastAccessedDateTime	Datetime		Timestamp of the last access to the file.
fileSystemInfo_lastModifiedDateTime	Datetime		Timestamp when the file was last modified.
folder_childCount	Int		Number of items (files/folders) in the folder.
folder_view_sortBy	String		Default sort field for viewing folder contents.
folder_view_sortOrder	String		Default sort order (ascending/descending) for folder contents.
folder_view_viewType	String		Type of view used to display the folder contents (for example, thumbnails).
image_height	Int		Height of the image in pixels.
image_width	Int		Width of the image in pixels.
location_altitude	Double		Altitude (in meters) where the file (typically a photo) was created.
location_latitude	Double		Latitude coordinate for the file's location.
location_longitude	Double		Longitude coordinate for the file's location.
package_type	String		Type of package (for example, OneNote, ZIP).
pendingOperations_pendingContentUpdate_queuedDateTime	Datetime		Timestamp when a pending update was queued.
photo_cameraMake	String		Camera manufacturer used to take the photo.
photo_cameraModel	String		Camera model used to take the photo.
photo_exposureDenominator	Double		Denominator of the exposure time (for example, 1/60s = 60).
photo_exposureNumerator	Double		Numerator of the exposure time.
photo_fNumber	Double		F-number (aperture) used to take the photo.
photo_focalLength	Double		Focal length of the lens used in millimeters.
photo_iso	Int		ISO sensitivity used when taking the photo.
photo_orientation	Int		Orientation of the photo (for example, 1 = normal, 3 = upside down).
photo_takenDateTime	Datetime		Timestamp when the photo was taken.
publication_level	String		The publication level for the folder, which can define sharing or access visibility.
publication_versionId	String		Identifier representing the specific publication version of the folder.
remoteItem_createdBy_application_displayName	String		Display name of the application that created the remote item.
remoteItem_createdBy_application_id	String		Unique identifier of the application that created the remote item.
remoteItem_createdDateTime	Datetime		Timestamp when the remote item was initially created.
remoteItem_file_hashes_crc32Hash	String		CRC32 checksum used for file integrity verification.
remoteItem_file_hashes_quickXorHash	String		QuickXor hash used by OneDrive to track file content changes.
remoteItem_file_hashes_sha1Hash	String		SHA-1 hash of the file used for content validation.
remoteItem_file_hashes_sha256Hash	String		SHA-256 hash of the file used for secure integrity checking.
remoteItem_file_mimeType	String		MIME type of the file, such as application/pdf or image/jpeg.
remoteItem_file_processingMetadata	Bool		Indicates whether the file contains processing metadata such as indexing or tagging.
remoteItem_fileSystemInfo_createdDateTime	Datetime		Date and time when the file was created in the filesystem.
remoteItem_fileSystemInfo_lastAccessedDateTime	Datetime		Date and time the file was last accessed in the filesystem.
remoteItem_fileSystemInfo_lastModifiedDateTime	Datetime		Last modification timestamp of the file within the filesystem.
remoteItem_folder_childCount	Int		Number of child items contained in the folder.
remoteItem_folder_view_sortBy	String		Default attribute used to sort items in the folder view.
remoteItem_folder_view_sortOrder	String		Sorting order (ascending or descending) used in the folder view.
remoteItem_folder_view_viewType	String		Type of view used for displaying the folder, such as list or thumbnails.
remoteItem_id	String		Unique identifier of the remote item.
remoteItem_image_height	Int		Height of the image in pixels.
remoteItem_image_width	Int		Width of the image in pixels.
remoteItem_lastModifiedDateTime	Datetime		Timestamp of the last change made to the remote item.
remoteItem_name	String		Name of the remote item (file or folder).
remoteItem_package_type	String		Type of package the item belongs to, such as OneNote or ZIP.
remoteItem_parentReference_driveId	String		Drive ID of the item's parent directory.
remoteItem_parentReference_driveType	String		Type of drive hosting the item, such as personal or business.
remoteItem_parentReference_id	String		Identifier of the parent folder or item.
remoteItem_parentReference_name	String		Name of the parent folder or item.
remoteItem_parentReference_path	String		Full path to the parent item in the drive.
remoteItem_parentReference_shareId	String		ID associated with shared access to the parent item.
remoteItem_parentReference_sharepointIds_listId	String		SharePoint list ID related to the parent item.
remoteItem_parentReference_sharepointIds_listItemId	String		Item ID within a SharePoint list.
remoteItem_parentReference_sharepointIds_listItemUniqueId	String		Globally unique identifier (GUID) for the SharePoint list item.
remoteItem_parentReference_sharepointIds_siteId	String		SharePoint site ID where the item is located.
remoteItem_parentReference_sharepointIds_siteUrl	String		URL of the SharePoint site hosting the item.
remoteItem_parentReference_sharepointIds_tenantId	String		Tenant ID of the SharePoint organization.
remoteItem_parentReference_sharepointIds_webId	String		Web ID for the SharePoint subsite.
remoteItem_parentReference_siteId	String		Site ID associated with the parent folder or item.
remoteItem_shared_scope	String		The scope of the shared item, such as organization or anonymous.
remoteItem_shared_sharedDateTime	Datetime		Date and time when the item was shared.
remoteItem_size	Long		Size of the item in bytes.
remoteItem_specialFolder_name	String		Indicates whether the folder is special, such as Documents or Photos.
remoteItem_video_audioBitsPerSample	Int		Number of audio bits per sample in the video file.
remoteItem_video_audioChannels	Int		Number of audio channels (for example, mono, stereo) in the video.
remoteItem_video_audioFormat	String		Format of the audio encoding in the video.
remoteItem_video_audioSamplesPerSecond	Int		Sample rate of audio in the video, measured in Hz.
remoteItem_video_bitrate	Int		Bitrate of the video file in bits per second.
remoteItem_video_duration	Long		Duration of the video in milliseconds.
remoteItem_video_fourCC	String		Four-character code (FourCC) identifying the video codec.
remoteItem_video_frameRate	Double		Frame rate of the video in frames per second.
remoteItem_video_height	Int		Video height in pixels.
remoteItem_video_width	Int		Video width in pixels.
remoteItem_webDavUrl	String		WebDAV-compliant URL to access the remote item programmatically.
remoteItem_webUrl	String		Web URL to view the remote item in a browser.
searchResult_onClickTelemetryUrl	String		URL used for telemetry tracking when a search result is clicked.
shared_owner_application_displayName	String		Display name of the application that owns the shared item.
shared_owner_application_id	String		ID of the application that owns the shared item.
shared_scope	String		Scope of sharing for the item, such as users, organization, or anonymous.
shared_sharedDateTime	Datetime		Date and time when the item was shared by the owner.
sharepointIds_listId	String		Identifier for the SharePoint list.
sharepointIds_listItemId	String		Item ID in the associated SharePoint list.
sharepointIds_listItemUniqueId	String		GUID for the SharePoint list item.
sharepointIds_siteId	String		SharePoint site ID where the item resides.
sharepointIds_siteUrl	String		URL of the SharePoint site.
sharepointIds_tenantId	String		ID of the SharePoint tenant.
sharepointIds_webId	String		Identifier of the SharePoint web object.
size	Long		Size of the item in bytes.
specialFolder_name	String		Type of special folder, such as Documents, Music, or Photos.
video_audioBitsPerSample	Int		Audio depth per sample in the video file.
video_audioChannels	Int		Number of audio channels in the video (for example, 2 for stereo).
video_audioFormat	String		Audio codec format used in the video.
video_audioSamplesPerSecond	Int		Audio sample rate in Hz.
video_bitrate	Int		Total bitrate of the video file.
video_duration	Long		Length of the video in milliseconds.
video_fourCC	String		Codec identifier (FourCC) used for the video stream.
video_frameRate	Double		Video frame rate in frames per second.
video_height	Int		Height resolution of the video.
video_width	Int		Width resolution of the video.
webDavUrl	String		WebDAV URL for accessing the item via file system protocols.
Linkedanalytics	String		Link to analytics data related to the folder or item.
Linkedchildren	String		Link to the child items contained within the folder.
LinkedlistItem	String		Link to the associated SharePoint list item.
Linkedpermissions	String		Link to the permissions set on the item.
Linkedsubscriptions	String		Link to any active subscriptions (for example, webhooks) on the item.
Linkedthumbnails	String		Link to thumbnail previews for the item.
Linkedversions	String		Link to version history for the file.
Linkedworkbook	String		Link to the Excel workbook interface if the file is an Excel document.

Lists the members of the group.

Columns

Name	Type	References	Description
GroupId [KEY]	String	Groups.Id	Id of the Group.
MemberId [KEY]	String	Users.Id	Id of the Member
DisplayName	String		Display Name of the member.
UserPrincipalName	String		Principal Name of the member.

Shows all security and distribution groups within the connected Microsoft 365 tenant, enabling administrative oversight.

Columns

Name	Type	References	Description
Id [KEY]	String		Unique identifier for the group object within the directory.
assignedLabels	String		List of sensitivity labels assigned to the group, used for compliance or classification.
assignedLicenses	String		Details of licenses that have been assigned to the group members, including service plans.
classification	String		Custom string used to classify the group, such as Confidential or Internal.
createdDateTime	Datetime		Date and time when the group was created in the directory.
description	String		Free-form description of the group, typically used for administrative context.
displayName	String		Display name of the group as it appears in the address book or directory listings.
expirationDateTime	Datetime		The date and time when the group is scheduled to expire, if applicable.
groupTypes	String		List of types associated with the group, such as Unified or DynamicMembership.
hasMembersWithLicenseErrors	Bool		Indicates whether any group members have license assignment errors.
isAssignableToRole	Bool		Specifies if the group can be assigned to Azure AD roles for role-based access control.
isManagementRestricted	Bool		Indicates whether group management is restricted to designated owners or admins.
licenseProcessingState_state	String		Current state of license processing for the group (for example, 'Enabled', 'Error').
mail	String		Email address of the group if mail-enabled, used for communication or notifications.
mailEnabled	Bool		Indicates whether the group is enabled to send or receive email messages.
mailNickname	String		Mail alias (nickname) for the group, used in email addresses and directory services.
membershipRule	String		Rule used to dynamically assign members to the group based on directory attributes.
membershipRuleProcessingState	String		Current processing state of the dynamic membership rule (for example, 'InProgress', 'UpdateComplete').
onPremisesDomainName	String		Domain name from the on-premises directory if synced from Active Directory.
onPremisesLastSyncDateTime	Datetime		Last date and time the group was synced from the on-premises directory.
onPremisesNetBiosName	String		NetBIOS name of the domain from which the group was synced.
onPremisesProvisioningErrors	String		List of any provisioning errors that occurred during on-premises sync.
onPremisesSamAccountName	String		Security Accounts Manager (SAM) account name for the group, if synced from on-premises.
onPremisesSecurityIdentifier	String		Security identifier (SID) for the group, used in access control for Windows systems.
onPremisesSyncEnabled	Bool		Indicates whether directory sync is enabled for the group from the on-premises environment.
preferredDataLocation	String		Preferred geographic location for storing data related to the group, such as 'North America'.
preferredLanguage	String		Preferred language for the group interface, emails, and other localized experiences.
proxyAddresses	String		List of email addresses associated with the group, including primary and aliases. Each address is separated by a comma and can include smtp, SMTP, or x500.
renewedDateTime	Datetime		The last time the group was renewed or updated in the directory.
securityEnabled	Bool		Indicates whether the group is security-enabled and can be used for access control.
securityIdentifier	String		SID for the group, used for security and identity operations.
serviceProvisioningErrors	String		Any errors encountered while provisioning services for the group, such as SharePoint or Teams.
theme	String		Custom UI theme assigned to the group for services like Microsoft Teams.
uniqueName	String		Globally unique name for the group, used for internal referencing and identification.
unseenCount	Int		Number of unseen items or notifications associated with the group (for example, in Teams or Outlook).
visibility	String		Defines group visibility level, such as Public, Private, or HiddenMembership.

Details sharing and access permissions for files and folders within a OneDrive drive, identifying owners and collaborators.

View-Specific Information

UserId and GroupId connection properties can also be used to filter records. If both are included in the connection string, UserId takes precedence over GroupId.

To filter permissions for a specific user:

SELECT * FROM Permissions WHERE UserId = 'a9920804-3212-4f9d-aac7-f55c697fa2bc'

To filter permissions for a specific group:

SELECT * FROM Permissions WHERE GroupId = '0a98c469-e041-4d3b-91b5-0966e5200081'

Due to API limitations, all operators on this view are executed client-side. This means the connector retrieves all available records from the API before applying any filters, which may impact performance for large datasets.

Columns

Name	Type	References	Description
id [KEY]	String		Unique identifier for the permission record.
Etag	String		Entity tag used for concurrency control to track updates to the permission.
ResourceId [KEY]	String		Identifier of the resource (file or folder) the permission applies to.
grantedTo_user_displayName	String		Display name of the user who has been granted access to the resource.
grantedTo_user_email	String		Email address of the user who has been granted access.
grantedTo_user_id	String		Unique identifier of the user granted access.
expirationDateTime	Datetime		Timestamp indicating when the permission will expire, if set.
grantedTo_application_displayName	String		Name of the application granted access to the resource.
grantedTo_application_id	String		Unique identifier of the application granted access.
grantedToIdentities	String		List of user or group identities that the permission has been granted to, separated by commas.
hasPassword	Bool		Indicates whether the shared link is protected by a password.
inheritedFrom_driveId	String		ID of the drive where the original permission was inherited from.
inheritedFrom_driveType	String		Type of the originating drive, such as personal or business.
inheritedFrom_id	String		ID of the resource from which the permission is inherited.
inheritedFrom_name	String		Name of the resource from which the permission is inherited.
inheritedFrom_path	String		Path to the source resource from which the permission is inherited.
inheritedFrom_shareId	String		ID of the sharing link associated with the inherited permission.
inheritedFrom_sharepointIds_listId	String		SharePoint list ID from which the permission is inherited.
inheritedFrom_sharepointIds_listItemId	String		ID of the SharePoint list item the permission is derived from.
inheritedFrom_sharepointIds_listItemUniqueId	String		Globally unique identifier (GUID) of the SharePoint list item.
inheritedFrom_sharepointIds_siteId	String		SharePoint site ID from which the permission originates.
inheritedFrom_sharepointIds_siteUrl	String		URL of the SharePoint site associated with the inherited permission.
inheritedFrom_sharepointIds_tenantId	String		Tenant ID associated with the originating SharePoint environment.
inheritedFrom_sharepointIds_webId	String		Web ID for the SharePoint subsite containing the original resource.
inheritedFrom_siteId	String		Site ID of the location from which the permission is inherited.
invitation_email	String		Email address of the person invited to access the resource.
invitation_invitedBy_application_displayName	String		Display name of the application that sent the sharing invitation.
invitation_invitedBy_application_id	String		ID of the application that issued the sharing invitation.
invitation_redeemedBy	String		Email or identifier of the person who accepted and redeemed the sharing invitation.
invitation_signInRequired	Bool		Indicates whether the recipient must sign in to access the resource.
link_application_displayName	String		Display name of the application that created the sharing link.
link_application_id	String		Unique identifier of the application that created the sharing link.
link_preventsDownload	Bool		Indicates whether downloading the shared content is restricted for viewers.
link_scope	String		Defines the access scope of the sharing link, such as anonymous, organization, or specific people.
link_type	String		Type of sharing link created (for example, view, edit, embed).
link_webHtml	String		HTML-formatted snippet that renders the sharing link for embedding in web pages.
link_webUrl	String		Direct web URL to access the shared item.
roles	String		Comma-separated list of roles granted by the permission, such as read, write, owner.
shareId	String		Unique identifier for the sharing instance, used to reference and manage shared access.