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What are the different ways to implement parallel processing in Informatica?

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We can implement parallel processing using various types of partition algorithms:

Database partitioning: The Integration Service queries the database system for table partition information. It reads partitioned data from the corresponding nodes in the database.

Round-Robin Partitioning: Using this partitioning algorithm, the Integration service distributes data evenly among all partitions. It makes sense to use round-robin partitioning when you need to distribute rows evenly and do not need to group data among partitions.

Hash Auto-Keys Partitioning: The Powercenter Server uses a hash function to group rows of data among partitions. When the hash auto-key partition is used, the Integration Service uses all grouped or sorted ports as a compound partition key. You can use hash auto-keys partitioning at or before Rank, Sorter, and unsorted Aggregator transformations to ensure that rows are grouped properly before they enter these transformations.

Hash User-Keys Partitioning: Here, the Integration Service uses a hash function to group rows of data among partitions based on a user-defined partition key. You can individually choose the ports that define the partition key.

Key Range Partitioning: With this type of partitioning, you can specify one or more ports to form a compound partition key for a source or target. The Integration Service then passes data to each partition depending on the ranges you specify for each port.

Pass-through Partitioning: In this type of partitioning, the Integration Service passes all rows from one partition point to the next partition point without redistributing them.

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