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  • Data Engineering Integration H2L
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  1. Abstract
  2. Supported Versions
  3. Tuning and Sizing Guidelines for Data Engineering Integration (10.4.x)

Tuning and Sizing Guidelines for Data Engineering Integration (10.4.x)

Tuning and Sizing Guidelines for Data Engineering Integration (10.4.x)

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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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