[SPARK-17456][CORE] Utility for parsing Spark versions #15017
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CC: @yanboliang @MLnick Does one of you have time to review this? It should be very quick. Thanks! |
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Would it make sense to replace some of the hacks with this util at the same time? |
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Test build #65115 has finished for PR 15017 at commit
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I like splitting things into separate PRs, but I'll go ahead and make a follow-up task to check for places which can be fixed. |
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Sounds good :) |
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LGTM, merged into master. Thanks! |
Contributor
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We can replace the hacks by the new utility in SPARK-17462. Thanks! |
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Thanks @yanboliang ! |
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Actually, I'd like to backport this to 2.0 since I'd like to put [https://issues.apache.org/jira/browse/SPARK-16240] into 2.0 as well. I'll do the backport. |
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Sep 9, 2016
## What changes were proposed in this pull request? This patch adds methods for extracting major and minor versions as Int types in Scala from a Spark version string. Motivation: There are many hacks within Spark's codebase to identify and compare Spark versions. We should add a simple utility to standardize these code paths, especially since there have been mistakes made in the past. This will let us add unit tests as well. Currently, I want this functionality to check Spark versions to provide backwards compatibility for ML model persistence. ## How was this patch tested? Unit tests Author: Joseph K. Bradley <joseph@databricks.com> Closes #15017 from jkbradley/version-parsing. (cherry picked from commit 65b814b) Signed-off-by: Joseph K. Bradley <joseph@databricks.com>
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OK I did the backport. I checked out branch-2.0 and ran the test locally. |
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What changes were proposed in this pull request?
This patch adds methods for extracting major and minor versions as Int types in Scala from a Spark version string.
Motivation: There are many hacks within Spark's codebase to identify and compare Spark versions. We should add a simple utility to standardize these code paths, especially since there have been mistakes made in the past. This will let us add unit tests as well. Currently, I want this functionality to check Spark versions to provide backwards compatibility for ML model persistence.
How was this patch tested?
Unit tests