You can add an Amazon S3 data object read operation as a lookup in a mapping. You can then configure a lookup condition to look up data from the Amazon S3 table.

When you preview a Lookup transformation based on an Amazon S3 logical data object, the performance might be slow.

You can configure a cached lookup operation to cache the lookup data in a mapping that runs on the Spark engine.

When you enable lookup caching, the Data Integration Service caches the lookup values. The Data Integration Service queries the lookup source once, caches the values, and looks up values in the cache. Caching the lookup values can increase performance on large lookup tables.

When you disable caching, the Data Integration Service does not cache the lookup values. The Data Integration Service queries the lookup source instead of building and querying the lookup cache. Each time a row passes, the Data Integration Service issues a SELECT statement to the lookup source for lookup values.

You can set cached lookup in the run-time properties of the lookup operation in a mapping.

For more information about the cached lookup, see "Lookup Transformation" in the

Developer Transformation Guide

.