Table of Contents

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  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Mappings in the Hadoop Environment
  4. Mapping Sources in the Hadoop Environment
  5. Mapping Targets in the Hadoop Environment
  6. Mapping Transformations in the Hadoop Environment
  7. Processing Hierarchical Data on the Spark Engine
  8. Configuring Transformations to Process Hierarchical Data
  9. Processing Unstructured and Semi-structured Data with an Intelligent Structure Model
  10. Stateful Computing on the Spark Engine
  11. Monitoring Mappings in the Hadoop Environment
  12. Mappings in the Native Environment
  13. Profiles
  14. Native Environment Optimization
  15. Cluster Workflows
  16. Connections
  17. Data Type Reference
  18. Function Reference
  19. Parameter Reference

Enabling Data Compression on Temporary Staging Tables

Enabling Data Compression on Temporary Staging Tables

To optimize performance when you run a mapping in the Hadoop environment, you can enable data compression on temporary staging tables. When you enable data compression on temporary staging tables, mapping performance might increase.
To enable data compression on temporary staging tables, complete the following steps:
  1. Configure the Hive connection to use the codec class name that the Hadoop cluster uses to enable compression on temporary staging tables.
  2. Configure the Hadoop cluster to enable compression on temporary staging tables.
Hadoop provides following compression libraries for the following compression codec class names:
Compression Library
Codec Class Name
Performance Recommendation
Zlib
org.apache.hadoop.io.compress.DefaultCodec
n/a
Gzip
org.apache.hadoop.io.compress.GzipCodec
n/a
Snappy
org.apache.hadoop.io.compress.SnappyCodec
Recommended for best performance.
Bz2
org.apache.hadoop.io.compress.BZip2Codec
Not recommended. Degrades performance.
LZO
com.hadoop.compression.lzo.LzoCodec
n/a


Updated October 23, 2019