[SPARK-17356][SQL][1.6] Fix out of memory issue when generating JSON for TreeNode #14973
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clockfly
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Dumb question, but aren't we using this in MLLib? |
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@hvanhovell, the meta data is still kept in the plan. MLLib doesn't use toJson directly. |
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Test build #64992 has finished for PR 14973 at commit
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asfgit
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Sep 6, 2016
…for TreeNode This is a backport of PR #14915 to branch 1.6. ## What changes were proposed in this pull request? class `org.apache.spark.sql.types.Metadata` is widely used in mllib to store some ml attributes. `Metadata` is commonly stored in `Alias` expression. ``` case class Alias(child: Expression, name: String)( val exprId: ExprId = NamedExpression.newExprId, val qualifier: Option[String] = None, val explicitMetadata: Option[Metadata] = None, override val isGenerated: java.lang.Boolean = false) ``` The `Metadata` can take a big memory footprint since the number of attributes is big ( in scale of million). When `toJSON` is called on `Alias` expression, the `Metadata` will also be converted to a big JSON string. If a plan contains many such kind of `Alias` expressions, it may trigger out of memory error when `toJSON` is called, since converting all `Metadata` references to JSON will take huge memory. With this PR, we will skip scanning Metadata when doing JSON conversion. For a reproducer of the OOM, and analysis, please look at jira https://issues.apache.org/jira/browse/SPARK-17356. ## How was this patch tested? Existing tests. Author: Sean Zhong <seanzhong@databricks.com> Closes #14973 from clockfly/json_oom_1.6.
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LGTM, merging to 1.6! |
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Thanks! |
zzcclp
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Sep 7, 2016
…for TreeNode This is a backport of PR apache#14915 to branch 1.6. ## What changes were proposed in this pull request? class `org.apache.spark.sql.types.Metadata` is widely used in mllib to store some ml attributes. `Metadata` is commonly stored in `Alias` expression. ``` case class Alias(child: Expression, name: String)( val exprId: ExprId = NamedExpression.newExprId, val qualifier: Option[String] = None, val explicitMetadata: Option[Metadata] = None, override val isGenerated: java.lang.Boolean = false) ``` The `Metadata` can take a big memory footprint since the number of attributes is big ( in scale of million). When `toJSON` is called on `Alias` expression, the `Metadata` will also be converted to a big JSON string. If a plan contains many such kind of `Alias` expressions, it may trigger out of memory error when `toJSON` is called, since converting all `Metadata` references to JSON will take huge memory. With this PR, we will skip scanning Metadata when doing JSON conversion. For a reproducer of the OOM, and analysis, please look at jira https://issues.apache.org/jira/browse/SPARK-17356. ## How was this patch tested? Existing tests. Author: Sean Zhong <seanzhong@databricks.com> Closes apache#14973 from clockfly/json_oom_1.6. (cherry picked from commit e6480a6)
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This is a backport of PR #14915 to branch 1.6.
What changes were proposed in this pull request?
class
org.apache.spark.sql.types.Metadatais widely used in mllib to store some ml attributes.Metadatais commonly stored inAliasexpression.The
Metadatacan take a big memory footprint since the number of attributes is big ( in scale of million). WhentoJSONis called onAliasexpression, theMetadatawill also be converted to a big JSON string.If a plan contains many such kind of
Aliasexpressions, it may trigger out of memory error whentoJSONis called, since converting allMetadatareferences to JSON will take huge memory.With this PR, we will skip scanning Metadata when doing JSON conversion. For a reproducer of the OOM, and analysis, please look at jira https://issues.apache.org/jira/browse/SPARK-17356.
How was this patch tested?
Existing tests.