Table of Contents

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  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Aggregator transformation
  6. Cleanse transformation
  7. Data Masking transformation
  8. Deduplicate transformation
  9. Expression transformation
  10. Filter transformation
  11. Hierarchy Builder transformation
  12. Hierarchy Parser transformation
  13. Hierarchy Processor transformation
  14. Input transformation
  15. Java transformation
  16. Java transformation API reference
  17. Joiner transformation
  18. Labeler transformation
  19. Lookup transformation
  20. Mapplet transformation
  21. Normalizer transformation
  22. Output transformation
  23. Parse transformation
  24. Python transformation
  25. Rank transformation
  26. Router transformation
  27. Rule Specification transformation
  28. Sequence Generator transformation
  29. Sorter transformation
  30. SQL transformation
  31. Structure Parser transformation
  32. Transaction Control transformation
  33. Union transformation
  34. Velocity transformation
  35. Verifier transformation
  36. Web Services transformation

Transformations

Transformations

Partitioning examples

Partitioning examples

The following examples show how you can configure partitioning in a mapping.

Partitioning with a Flat File Source

You have a
mapping
task that uses a large, 1GB flat file source. You want to specify two partitions in the Source transformation to optimize performance.
On the
Partitions
tab for the Source transformation, you select fixed partitioning and enter the number of partitions, as shown in the following image:
On the Partitions tab of the Source transformation, the partitioning type is "Fixed" and the number of partitions is set to "2."

Key Range Partitioning with a Relational Database Source

You have customer names, addresses, and purchasing history in a relational database source. You decide to partition the source data into three partitions based on postal codes, using the following ranges:
  • First partition: Minimum value to 30000
  • Second partition: 30001 to 50000
  • Third partition: 50001 to maximum value
On the
Partitions
tab for the Source transformation, you select key range partitioning and choose the BILLINGPOSTALCODE field as the partition key. You add three key ranges to create three partitions, as shown in the following image:
On the Partitions tab for the Source transformation, the partitioning type is "Key Range" and the BILLINGPOSTALCODE column is selected as the partition key. The Start Range and End Range columns for each partition define the range of values for each partition. In the first partition, the start range is blank, so the minimum value is used as the starting value. In the third partition, the end range is blank, so the maximum value is used as the ending value.
Note that for the first partition, you leave the start value blank for the minimum value. In the last partition, you leave the end value blank for the maximum value.
Using these values, records with a postal code of 0 up to 30000 are processed in partition #1, records with a postal code of 30001 to 50000 are processed in partition #2, and records with a postal code of 50001 or higher are processed in partition #3.
After you configure the mapping, you save and run the mapping to validate the partitions.