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authorSean Zhong <seanzhong@databricks.com>2016-09-06 16:05:50 +0800
committerWenchen Fan <wenchen@databricks.com>2016-09-06 16:05:50 +0800
commit6f13aa7dfee12b1b301bd10a1050549008ecc67e (patch)
tree67f7324e327eabf40d8a0970cd0baaea7994d666
parentc0ae6bc6ea38909730fad36e653d3c7ab0a84b44 (diff)
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[SPARK-17356][SQL] Fix out of memory issue when generating JSON for TreeNode
## 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 #14915 from clockfly/json_oom.
-rw-r--r--sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/TreeNode.scala4
-rw-r--r--sql/core/src/test/scala/org/apache/spark/sql/QueryTest.scala10
2 files changed, 12 insertions, 2 deletions
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/TreeNode.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/TreeNode.scala
index 037f8cb287..893af5146c 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/TreeNode.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/TreeNode.scala
@@ -618,7 +618,9 @@ abstract class TreeNode[BaseType <: TreeNode[BaseType]] extends Product {
case s: String => JString(s)
case u: UUID => JString(u.toString)
case dt: DataType => dt.jsonValue
- case m: Metadata => m.jsonValue
+ // SPARK-17356: In usage of mllib, Metadata may store a huge vector of data, transforming
+ // it to JSON may trigger OutOfMemoryError.
+ case m: Metadata => Metadata.empty.jsonValue
case s: StorageLevel =>
("useDisk" -> s.useDisk) ~ ("useMemory" -> s.useMemory) ~ ("useOffHeap" -> s.useOffHeap) ~
("deserialized" -> s.deserialized) ~ ("replication" -> s.replication)
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/QueryTest.scala b/sql/core/src/test/scala/org/apache/spark/sql/QueryTest.scala
index c7af40227d..d361f61764 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/QueryTest.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/QueryTest.scala
@@ -33,7 +33,7 @@ import org.apache.spark.sql.execution.aggregate.TypedAggregateExpression
import org.apache.spark.sql.execution.columnar.InMemoryRelation
import org.apache.spark.sql.execution.datasources.LogicalRelation
import org.apache.spark.sql.execution.streaming.MemoryPlan
-import org.apache.spark.sql.types.ObjectType
+import org.apache.spark.sql.types.{Metadata, ObjectType}
abstract class QueryTest extends PlanTest {
@@ -274,6 +274,14 @@ abstract class QueryTest extends PlanTest {
val normalized1 = logicalPlan.transformAllExpressions {
case udf: ScalaUDF => udf.copy(function = null)
case gen: UserDefinedGenerator => gen.copy(function = null)
+ // After SPARK-17356: the JSON representation no longer has the Metadata. We need to remove
+ // the Metadata from the normalized plan so that we can compare this plan with the
+ // JSON-deserialzed plan.
+ case a @ Alias(child, name) if a.explicitMetadata.isDefined =>
+ Alias(child, name)(a.exprId, a.qualifier, Some(Metadata.empty), a.isGenerated)
+ case a: AttributeReference if a.metadata != Metadata.empty =>
+ AttributeReference(a.name, a.dataType, a.nullable, Metadata.empty)(a.exprId, a.qualifier,
+ a.isGenerated)
}
// RDDs/data are not serializable to JSON, so we need to collect LogicalPlans that contains