CData Python Connector for IBM Cloud Data Engine

Build 23.0.8839

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 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 Jobs Table

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

SELECT Id, Status FROM [CloudObjectStorage_1].[SampleBucket_1].Jobs WHERE UserId = ''

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.

Copyright (c) 2024 CData Software, Inc. - All rights reserved.
Build 23.0.8839