ea626b6acf
### What changes were proposed in this pull request? Exclude hive-service-rpc from build. ### Why are the changes needed? hive-service-rpc 2.3.6 and spark sql's thrift server module have duplicate classes. Leaving hive-service-rpc 2.3.6 in the class path means that spark can pick up classes defined in hive instead of its thrift server module, which can cause hard to debug runtime errors due to class loading order and compilation errors for applications depend on spark. If you compare hive-service-rpc 2.3.6's jar (https://search.maven.org/remotecontent?filepath=org/apache/hive/hive-service-rpc/2.3.6/hive-service-rpc-2.3.6.jar) and spark thrift server's jar (e.g. https://repository.apache.org/content/groups/snapshots/org/apache/spark/spark-hive-thriftserver_2.12/3.0.0-SNAPSHOT/spark-hive-thriftserver_2.12-3.0.0-20200207.021914-364.jar), you will see that all of classes provided by hive-service-rpc-2.3.6.jar are covered by spark thrift server's jar. https://issues.apache.org/jira/browse/SPARK-30783 has output of jar tf for both jars. ### Does this PR introduce any user-facing change? No ### How was this patch tested? Existing tests. Closes #27533 from yhuai/SPARK-30783. Authored-by: Yin Huai <yhuai@databricks.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com> |
||
---|---|---|
.. | ||
create-release | ||
deps | ||
sparktestsupport | ||
tests | ||
.gitignore | ||
.rat-excludes | ||
.scalafmt.conf | ||
appveyor-guide.md | ||
appveyor-install-dependencies.ps1 | ||
change-scala-version.sh | ||
check-license | ||
checkstyle-suppressions.xml | ||
checkstyle.xml | ||
github_jira_sync.py | ||
lint-java | ||
lint-python | ||
lint-r | ||
lint-r.R | ||
lint-scala | ||
make-distribution.sh | ||
merge_spark_pr.py | ||
mima | ||
pip-sanity-check.py | ||
README.md | ||
requirements.txt | ||
run-pip-tests | ||
run-tests | ||
run-tests-jenkins | ||
run-tests-jenkins.py | ||
run-tests.py | ||
sbt-checkstyle | ||
scalafmt | ||
scalastyle | ||
test-dependencies.sh | ||
tox.ini |
Spark Developer Scripts
This directory contains scripts useful to developers when packaging, testing, or committing to Spark.
Many of these scripts require Apache credentials to work correctly.