Table of Contents

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  1. Preface
  2. Mappings
  3. Mapplets
  4. Mapping Parameters
  5. Where to Assign Parameters
  6. Mapping Outputs
  7. Generate a Mapping from an SQL Query
  8. Dynamic Mappings
  9. How to Develop and Run a Dynamic Mapping
  10. Dynamic Mapping Use Cases
  11. Mapping Administration
  12. Import From PowerCenter
  13. Performance Tuning
  14. Pushdown Optimization
  15. Partitioned Mappings
  16. Developer Tool Naming Conventions

Developer Mapping Guide

Developer Mapping Guide

Partitioned Flat File Targets

Partitioned Flat File Targets

When a mapping that is enabled for partitioning writes to a flat file target, the Data Integration Service can use multiple threads to write to the file target.
The Data Integration Service can create partitions for a flat file or a file in Hadoop Distributed File System (HDFS).
You can configure a flat file data object to have either a file or command output type. When a flat file data object has the file output type, the Data Integration Service writes the target data to a flat file. If multiple threads write to the flat file target, each thread writes the target output to a separate file. Each thread uses the following format to name the file:
<output_file_name><partition_number>.out
For example, three threads might write to files named MyOutput1.out, MyOutput2.out, and MyOutput3.out.
You can configure multiple output file directories to optimize performance, or you can configure the flat file data object to write to a single merge file.
When a flat file data object has the command output type, the Data Integration Services outputs the target data to a command or to a merge command instead of a flat file or a merge file. If multiple partitions write to the flat file target, you can configure a command to process target data for a single partition or to process merge data for all target partitions.

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