Developer Mapping Guide

10.2.1
- 10.5.6
- 10.5.4
- 10.5
- 10.4.1
- 10.4.0
- 10.2.2

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Cache Partitioning for Transformations

Cache partitioning creates a separate cache for each partition that processes an Aggregator, Joiner, Rank, Lookup, or Sorter transformation. During cache partitioning, each partition stores different data in a separate cache. Each cache contains the rows needed by that partition.

Cache partitioning optimizes mapping performance because each thread queries a separate cache in parallel. When the Data Integration Service creates partitions for a mapping, the Data Integration Service always uses cache partitioning for partitioned Aggregator, Joiner, Rank, and Sorter transformations. The Data Integration Service might use cache partitioning for partitioned Lookup transformations.

The Data Integration Service uses cache partitioning for connected Lookup transformations under the following conditions:

The lookup condition contains only equality operators.

When the connected Lookup transformation looks up data in a relational table, the database is configured for case-sensitive comparison.

For example, if the lookup condition contains a string port and the database is not configured for case-sensitive comparison, the Data Integration Service does not use cache partitioning.

When the Data Integration Service does not use cache partitioning for a Lookup transformation, all threads that run the Lookup transformation share the same cache. Each thread queries the same cache serially.

The Data Integration Service does not use cache partitioning for unconnected Lookup transformations because the service uses one thread to run unconnected Lookup transformations.

Partitioned Transformations

Cache Size for Partitioned Caches

Optimize Cache Directories for Partitioning

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