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  1. Abstract
  2. Supported Versions
  3. Performance Tuning and Sizing Guidelines for Informatica® Big Data Management 10.2.2

Performance Tuning and Sizing Guidelines for Informatica® Big Data Management 10.2.2

Performance Tuning and Sizing Guidelines for Informatica® Big Data Management 10.2.2

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Case Study: Sqoop Oracle Export (Writer)

Case Study: Sqoop Oracle Export (Writer)

The following case study uses a simple pass-through mapping that reads data from HDFS and writes to Oracle using Sqoop.

Environment

Chipset
Intel® Xeon® Processor X5675 @ 3.2 GHz
Cores
2 x 6 cores
Memory
256 GB
Operating system
Red Hat Enterprise Linux 7.0
Hadoop distribution
Cloudera Enterprise 5.11.1
Hadoop cluster
7 nodes

Performance Chart

The following chart shows the execution time for Oracle export:

Recommendations

Consider the following recommendations:
  • Design mappings to enable sources and targets to handle requests in parallel.
  • Verify that the cluster has adequate resources to process data in parallel. Passing a large number of mappings does not improve the performance linearly if cluster resources are inadequate.
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