| commit | 71a2d79bb61fba46b4466b626596a431a992cfbc | [log] [tgz] |
|---|---|---|
| author | wankunde <wankunde@163.com> | Fri Nov 01 21:56:28 2019 +0800 |
| committer | William Guo <guoyp@apache.org> | Fri Nov 01 21:56:28 2019 +0800 |
| tree | 3730e1332ea5c75a57af47db07f27294ddacc697 | |
| parent | 0119a19c93d0607ecfda2c5e029169e689c2bfd0 [diff] |
[GRIFFIN-295] Limit the memory used by test case The container memory size is 3G in travis, but out test cases always uses more than 3G memory, so `Cannot allocate memory` will be thrown. ``` Java HotSpot(TM) 64-Bit Server VM warning: INFO: os::commit_memory(0x00000000fe980000, 23592960, 0) failed; error='Cannot allocate memory' (errno=12) # # There is insufficient memory for the Java Runtime Environment to continue. # Native memory allocation (mmap) failed to map 23592960 bytes for committing reserved memory. # An error report file with more information is saved as: # /home/travis/build/apache/griffin/measure/hs_err_pid11948.log # [ timer expired, abort... ] ``` There are two kind of programs in our tests, the maven main program and the tests run by maven-surefire-plugin and scalatest-maven-plugin. If the memory is unlimited, test cases will occupy as much memory as possible especially spark jobs. Spark jobs will not free the memory until a full GC occurs , even if we have stopped the spark context .so we need to limit the momery used by test cases. We can limit the maven memory used by set export MAVEN_OPTS=" -Xmx1024m -XX:ReservedCodeCacheSize=128m" , and we can limit the memory used by spark job tests by configuring the maven-surefire-plugin and scalatest-maven-plugin. For example: Before we limit the memory used, maven program occupy 1.5G memory and spark job occupy 1.8G memory. <img width="1153" alt="1" src="https://user-images.githubusercontent.com/3626747/67956554-40108e00-fc2f-11e9-83de-d0840fb42cb7.png"> <img width="1150" alt="2" src="https://user-images.githubusercontent.com/3626747/67956567-46066f00-fc2f-11e9-8a73-6d141be28e70.png"> After we limit the memory used, maven program occupy 1G memory and spark job occupy 1G memory. <img width="1142" alt="3" src="https://user-images.githubusercontent.com/3626747/67956579-4999f600-fc2f-11e9-9cd4-9032966ca923.png"> <img width="1139" alt="4" src="https://user-images.githubusercontent.com/3626747/67956586-4dc61380-fc2f-11e9-800b-1d26d637a479.png"> Author: wankunde <wankunde@163.com> Closes #546 from wankunde/testcase_memory_limit.
The data quality (DQ) is a key criteria for many data consumers like IoT, machine learning etc., however, there is no standard agreement on how to determine “good” data. Apache Griffin is a model-driven data quality service platform where you can examine your data on-demand. It provides a standard process to define data quality measures, executions and reports, allowing those examinations across multiple data systems. When you don't trust your data, or concern that poorly controlled data can negatively impact critical decision, you can utilize Apache Griffin to ensure data quality.
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