640f942337
Builds on top of work in SPARK-8425 to update Application Level Blacklisting in the scheduler. ## What changes were proposed in this pull request? Adds a UI to these patches by: - defining new listener events for blacklisting and unblacklisting, nodes and executors; - sending said events at the relevant points in BlacklistTracker; - adding JSON (de)serialization code for these events; - augmenting the Executors UI page to show which, and how many, executors are blacklisted; - adding a unit test to make sure events are being fired; - adding HistoryServerSuite coverage to verify that the SHS reads these events correctly. - updates the Executor UI to show Blacklisted/Active/Dead as a tri-state in Executors Status Updates .rat-excludes to pass tests. username squito ## How was this patch tested? ./dev/run-tests testOnly org.apache.spark.util.JsonProtocolSuite testOnly org.apache.spark.scheduler.BlacklistTrackerSuite testOnly org.apache.spark.deploy.history.HistoryServerSuite https://github.com/jsoltren/jose-utils/blob/master/blacklist/test-blacklist.sh ![blacklist-20161219](https://cloud.githubusercontent.com/assets/1208477/21335321/9eda320a-c623-11e6-8b8c-9c912a73c276.jpg) Author: José Hiram Soltren <jose@cloudera.com> Closes #16346 from jsoltren/SPARK-16654-submit. |
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create-release | ||
deps | ||
sparktestsupport | ||
tests | ||
.gitignore | ||
.rat-excludes | ||
appveyor-guide.md | ||
appveyor-install-dependencies.ps1 | ||
change-scala-version.sh | ||
change-version-to-2.10.sh | ||
change-version-to-2.11.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 | ||
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.