CData Python Connector for Azure Data Lake Storage

Build 22.0.8462

Automatically Caching 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 provider automatically initializes and builds a cache in the background. When AutoCache = true, the provider uses the cache for subsequent query executions, resulting in faster response times.

Configuring Automatic Caching

Caching the Resources Table

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

SELECT FullPath, Permission FROM Resources WHERE Type = 'FILE'

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.

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Build 22.0.8462