Azure Data Lake Storage Connector - Mule 4
Anypoint Connector for Azure Data Lake Storage Gen 2 (Azure Data Lake Storage Connector) provides access to standard Azure Data Lake Storage Gen 2 operations using Anypoint Platform.
Azure Data Lake Storage Gen2 is a scalable data storage service built by Microsoft Azure and designed for big data analytics. Azure Data Lake Storage Gen2 is built on top of Azure Blob Storage and provides the data organization and security semantics of Azure Data Lake Gen1 along with the cost and reliability benefits of Azure Blob Storage.
For information about compatibility and fixed issues, see the Azure Data Lake Storage Connector Release Notes.
Before You Begin
To use this connector, you must be familiar with:
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Azure Data Lake Storage Gen2 API
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Anypoint Connectors
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Mule runtime engine (Mule)
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Elements and global elements in a Mule flow
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How to create a Mule app using Anypoint Studio
Before creating an app, you must have access to:
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The Azure Data Lake Storage target resource
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Anypoint Platform
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Anypoint Studio version 7.1 or later
Common Use Cases for the Connector
Common use cases for Azure Data Lake Storage Connector include the following:
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Create, read, update, and delete files in an existing Azure Data Lake Storage file system.
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Create, rename, and delete directories from the Azure Data Lake Storage file system.
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Rename existing files.
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Append the contents of a file and flush the file’s contents.
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Obtain properties and status for a file or directory.
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Obtain the ACL (access control list) of a file or directory.
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Get a list of all the available paths in the Azure Data Lake Storage file system.
For examples of some of these common use cases, see Examples.
Audience
Connection Types
Azure Data Lake Storage Connector connections use the following authentication types:
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Azure Active Directory OAuth 2.0
Delegates user authentication to the service hosting the user account -
Shared Access Signature
Uses information contained in the SAS token to authorize the client request -
Shared Key Connection
Uses a shared access key that is generated by Azure and used for the storage account
Japanese Character Support
Azure Data Lake Storage Connector supports Japanese characters for path names. If you use Japanese characters in path names, you must encode the Japanese characters into valid UTF-8 encoded and escaped URI characters. DataWeave 2.0 provides a function to encode Japanese characters. See encodeURI(String)
File content operation payloads, such as adding content to a file, also support Japanese characters, and do not require any encoding.
This connector does not support Japanese for Azure Data Lake Storage file system names, as this is not supported by Azure Data Lake Storage itself.
Next Step
After you complete the prerequisites, you are ready to create an app and configure the connector using Anypoint Studio.