Performance Tuning and Partitioning in Informatica Cloud Guide 2024

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Performance tuning is to optimize session performance by eliminating performance bottlenecks., The first step in performance tuning is to identify performance bottlenecks.
Look for performance bottlenecks in the following order:
Target
Source
Mapping
Session
System
Target level –
When you define key constraints or indexes in target tables, you slow the loading of data to those tables.
To improve performance, drop indexes and key constraints.
To increasing Database Checkpoint Intervals
Using Bulk Loads
You can use bulk loading to improve the performance of a session that inserts a large amount of data into a DB2
Source level -
Optimizing the Query If a session joins multiple source tables in one Source Qualifier,
you might be able to improve performance by optimizing the query with optimizing hints.
Using Conditional Filters
Mapping Level-
you reduce the number of transformations in the mapping and delete unnecessary links between transformations to optimize the mapping.
you can use partitions to optimize performance for mapping tasks.
If a mapping task processes large data sets or perform complicated calculations or long time to process.
When you use multiple partitions, the mapping task divides data into partitions and processes the partitions concurrently, which can optimize performance.
None
The mapping task processes all data in a single partition. This is the default option.
Fixed
The mapping task distributes rows of data based on the number of partitions that you specify. You can specify up to 64 partitions.
If the mapping includes multiple sources, specify the same number of partitions for each source.
Key range
The mapping task distributes rows of data based on a field that you define as a partition key.
Dynamic
The mapping task determines the optimal number of partitions to create at runtime based on the source size.
You cannot partition a mapping in the following situations:
The mapping uses a parameterized source or source query.
The mapping includes a Web Services or Hierarchy Parser transformation.
The mapping includes multiple sources that use custom relationships or advanced relationships.
The mapping is a mapping in SQL ELT mode.

Partitioning rules and guidelines
You cannot use in-out parameters for key range values.
For flat file partitioning, session performance is optimal with large source files
Sequence numbers generated by Normalizer and Sequence Generator transformations might not be sequential for a partitioned source, but they are unique.
When a Sorter transformation is in a mapping with partitioning enabled, the task sorts of data in each partition separately