[jira] [Commented] (SPARK-17356) Out of memory when calling TreeNode.toJSON
[
https://issues.apache.org/jira/browse/SPARK-17356?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15454841#comment-15454841
]
Apache Spark commented on SPARK-17356:
--
User 'clockfly' has created a pull request for this issue:
https://github.com/apache/spark/pull/14915
> Out of memory when calling TreeNode.toJSON
> --
>
> Key: SPARK-17356
> URL: https://issues.apache.org/jira/browse/SPARK-17356
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Reporter: Sean Zhong
> Attachments: jmap.txt, jstack.txt, queryplan.txt
>
>
> When using MLLib, when calling toJSON on a plan with many level of
> sub-queries, it may cause out of memory exception with stack trace like this
> {code}
> java.lang.OutOfMemoryError: GC overhead limit exceeded
> at scala.collection.mutable.AbstractSeq.(Seq.scala:47)
> at scala.collection.mutable.AbstractBuffer.(Buffer.scala:48)
> at scala.collection.mutable.ListBuffer.(ListBuffer.scala:46)
> at scala.collection.immutable.List$.newBuilder(List.scala:396)
> at
> scala.collection.generic.GenericTraversableTemplate$class.newBuilder(GenericTraversableTemplate.scala:64)
> at
> scala.collection.AbstractTraversable.newBuilder(Traversable.scala:105)
> at
> scala.collection.TraversableLike$class.filter(TraversableLike.scala:262)
> at scala.collection.AbstractTraversable.filter(Traversable.scala:105)
> at
> scala.collection.TraversableLike$class.filterNot(TraversableLike.scala:274)
> at scala.collection.AbstractTraversable.filterNot(Traversable.scala:105)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:20)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:20)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:20)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:20)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:7)
> at
> com.fasterxml.jackson.databind.ser.DefaultSerializerProvider.serializeValue(DefaultSerializerProvider.java:128)
> at
> com.fasterxml.jackson.databind.ObjectMapper._configAndWriteValue(ObjectMapper.java:2881)
> at
> com.fasterxml.jackson.databind.ObjectMapper.writeValueAsString(ObjectMapper.java:2338)
> at org.json4s.jackson.JsonMethods$class.compact(JsonMethods.scala:34)
> at org.json4s.jackson.JsonMethods$.compact(JsonMethods.scala:50)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.toJSON(TreeNode.scala:566)
> {code}
> The query plan, stack trace, and jmap distribution is attached.
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[jira] [Commented] (SPARK-17356) Out of memory when calling TreeNode.toJSON
[
https://issues.apache.org/jira/browse/SPARK-17356?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15454553#comment-15454553
]
Sean Zhong commented on SPARK-17356:
Reproducer:
{code}
# Trigger OOM
scala> :paste -raw
// Entering paste mode (ctrl-D to finish)
package org.apache.spark.ml.attribute
import org.apache.spark.ml.attribute._
import org.apache.spark.sql.catalyst.expressions.{Alias, Literal}
import org.apache.spark.sql.catalyst.plans.logical.LocalRelation
import org.apache.spark.sql.catalyst.dsl.plans._
object Test {
def main(args: Array[String]): Unit = {
val rand = new java.util.Random()
val attr: Attribute = new BinaryAttribute(Some("a"),
Some(rand.nextInt(10)), Some(Array("value1", "value2")))
val attributeGroup = new AttributeGroup("group", Array.fill(100)(attr))
val alias = Alias(Literal(0), "alias")(explicitMetadata =
Some(attributeGroup.toMetadata()))
val testRelation = LocalRelation()
val query = testRelation.select((0 to 100).toSeq.map(_ => alias): _*)
System.out.print(query.toJSON.length)
}
}
// Exiting paste mode, now interpreting.
scala> org.apache.spark.ml.attribute.Test.main(null)
{code}
> Out of memory when calling TreeNode.toJSON
> --
>
> Key: SPARK-17356
> URL: https://issues.apache.org/jira/browse/SPARK-17356
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Reporter: Sean Zhong
> Attachments: jmap.txt, jstack.txt, queryplan.txt
>
>
> When using MLLib, when calling toJSON on a plan with many level of
> sub-queries, it may cause out of memory exception with stack trace like this
> {code}
> java.lang.OutOfMemoryError: GC overhead limit exceeded
> at scala.collection.mutable.AbstractSeq.(Seq.scala:47)
> at scala.collection.mutable.AbstractBuffer.(Buffer.scala:48)
> at scala.collection.mutable.ListBuffer.(ListBuffer.scala:46)
> at scala.collection.immutable.List$.newBuilder(List.scala:396)
> at
> scala.collection.generic.GenericTraversableTemplate$class.newBuilder(GenericTraversableTemplate.scala:64)
> at
> scala.collection.AbstractTraversable.newBuilder(Traversable.scala:105)
> at
> scala.collection.TraversableLike$class.filter(TraversableLike.scala:262)
> at scala.collection.AbstractTraversable.filter(Traversable.scala:105)
> at
> scala.collection.TraversableLike$class.filterNot(TraversableLike.scala:274)
> at scala.collection.AbstractTraversable.filterNot(Traversable.scala:105)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:20)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:20)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:20)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:20)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:7)
> at
> com.fasterxml.jackson.databind.ser.DefaultSerializerProvider.serializeValue(DefaultSerializerProvider.java:128)
> at
> com.fasterxml.jackson.databind.ObjectMapper._configAndWriteValue(ObjectMapper.java:2881)
> at
> com.fasterxml.jackson.databind.ObjectMapper.writeValueAsString(ObjectMapper.java:2338)
> at org.json4s.jackson.JsonMethods$class.compact(JsonMethods.scala:34)
> at org.json4s.jackson.JsonMethods$.compact(JsonMethods.scala:50)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.toJSON(TreeNode.scala:566)
> {code}
> The query plan, stack trace, and jmap distribution is attached.
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[jira] [Commented] (SPARK-17356) Out of memory when calling TreeNode.toJSON
[
https://issues.apache.org/jira/browse/SPARK-17356?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15454495#comment-15454495
]
Sean Zhong commented on SPARK-17356:
Root cause:
1. MLLib heavily leverage MetaData to store a lot of attribute information, in
the case here, the metadata may contains tens of thousands of Attribute
information. And the meta data may be stored to Alias expression like this:
{code}
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)
{code}
If we serialize the meta data to JSON, it will take a huge amount of memory.
> Out of memory when calling TreeNode.toJSON
> --
>
> Key: SPARK-17356
> URL: https://issues.apache.org/jira/browse/SPARK-17356
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Reporter: Sean Zhong
> Attachments: jmap.txt, jstack.txt, queryplan.txt
>
>
> When using MLLib, when calling toJSON on a plan with many level of
> sub-queries, it may cause out of memory exception with stack trace like this
> {code}
> java.lang.OutOfMemoryError: GC overhead limit exceeded
> at scala.collection.mutable.AbstractSeq.(Seq.scala:47)
> at scala.collection.mutable.AbstractBuffer.(Buffer.scala:48)
> at scala.collection.mutable.ListBuffer.(ListBuffer.scala:46)
> at scala.collection.immutable.List$.newBuilder(List.scala:396)
> at
> scala.collection.generic.GenericTraversableTemplate$class.newBuilder(GenericTraversableTemplate.scala:64)
> at
> scala.collection.AbstractTraversable.newBuilder(Traversable.scala:105)
> at
> scala.collection.TraversableLike$class.filter(TraversableLike.scala:262)
> at scala.collection.AbstractTraversable.filter(Traversable.scala:105)
> at
> scala.collection.TraversableLike$class.filterNot(TraversableLike.scala:274)
> at scala.collection.AbstractTraversable.filterNot(Traversable.scala:105)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:20)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:20)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:20)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:20)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:7)
> at
> com.fasterxml.jackson.databind.ser.DefaultSerializerProvider.serializeValue(DefaultSerializerProvider.java:128)
> at
> com.fasterxml.jackson.databind.ObjectMapper._configAndWriteValue(ObjectMapper.java:2881)
> at
> com.fasterxml.jackson.databind.ObjectMapper.writeValueAsString(ObjectMapper.java:2338)
> at org.json4s.jackson.JsonMethods$class.compact(JsonMethods.scala:34)
> at org.json4s.jackson.JsonMethods$.compact(JsonMethods.scala:50)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.toJSON(TreeNode.scala:566)
> {code}
> The query plan, stack trace, and jmap distribution is attached.
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[jira] [Commented] (SPARK-17356) Out of memory when calling TreeNode.toJSON
[
https://issues.apache.org/jira/browse/SPARK-17356?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15454488#comment-15454488
]
Sean Zhong commented on SPARK-17356:
*Analysis*
After looking at the mmap, there is a suspicious line
{code}
20: 18388624 [Lorg.apache.spark.ml.attribute.Attribute;
{code}
This means a single Attribute array takes more than 8388624 bytes, and if each
reference takes 8 bytes, it means there are 1 million attributes.
The array probably is used in AttributeGroup, whose signature is:
{code}
class AttributeGroup private (
val name: String,
val numAttributes: Option[Int],
attrs: Option[Array[Attribute]])
{code}
And, in AttributeGroup, there is a toMetaData function which will convert the
Attribute array to Meta data
{code}
def toMetadata(): Metadata = toMetadata(Metadata.empty)
{code}
Finally, the metadata are saved to expression Attribute.
For example, in org.apache.spark.ml.feature.Interaction transform function, the
meta data is set to attribute of Alias expression, when aliasing the udf
function like this:
{code}
override def transform(dataset: Dataset[_]): DataFrame = {
...
// !NOTE!: This is an attribute group
val featureAttrs = getFeatureAttrs(inputFeatures)
def interactFunc = udf { row: Row =>
...
}
val featureCols = inputFeatures.map { f =>
f.dataType match {
case DoubleType => dataset(f.name)
case _: VectorUDT => dataset(f.name)
case _: NumericType | BooleanType => dataset(f.name).cast(DoubleType)
}
}
// !NOTE!: The meta data i stored in Alias expresion by function call
.as(..., featureAttrs.toMetadata())
dataset.select(
col("*"),
interactFunc(struct(featureCols: _*)).as($(outputCol),
featureAttrs.toMetadata()))
}
{code}
And, when calling toJSON, the metaData will be converted to JSON.
> Out of memory when calling TreeNode.toJSON
> --
>
> Key: SPARK-17356
> URL: https://issues.apache.org/jira/browse/SPARK-17356
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Reporter: Sean Zhong
> Attachments: jmap.txt, jstack.txt, queryplan.txt
>
>
> When using MLLib, when calling toJSON on a plan with many level of
> sub-queries, it may cause out of memory exception with stack trace like this
> {code}
> java.lang.OutOfMemoryError: GC overhead limit exceeded
> at scala.collection.mutable.AbstractSeq.(Seq.scala:47)
> at scala.collection.mutable.AbstractBuffer.(Buffer.scala:48)
> at scala.collection.mutable.ListBuffer.(ListBuffer.scala:46)
> at scala.collection.immutable.List$.newBuilder(List.scala:396)
> at
> scala.collection.generic.GenericTraversableTemplate$class.newBuilder(GenericTraversableTemplate.scala:64)
> at
> scala.collection.AbstractTraversable.newBuilder(Traversable.scala:105)
> at
> scala.collection.TraversableLike$class.filter(TraversableLike.scala:262)
> at scala.collection.AbstractTraversable.filter(Traversable.scala:105)
> at
> scala.collection.TraversableLike$class.filterNot(TraversableLike.scala:274)
> at scala.collection.AbstractTraversable.filterNot(Traversable.scala:105)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:20)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:20)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:20)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:25)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:20)
> at
> org.json4s.jackson.JValueSerializer.serialize(JValueSerializer.scala:7)
> at
> com.fasterxml.jackson.databind.ser.DefaultSerializerProvider.serializeValue(DefaultSerializerProvider.java:128)
> at
> com.fasterxml.jackson.databind.ObjectMapper._configAndWriteValue(ObjectMapper.java:2881)
> at
> com.fasterxml.jackson.databind.ObjectMapper.writeValueAsString(ObjectMapper.java:2338)
> at org.json4s.jackson.JsonMethods$class.compact(JsonMethods.scala:34)
> at org.json4s.jackson.JsonMethods$.compact(JsonMethods.scala:50)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.toJSON(TreeNode.scala:566)
> {code}
> The query plan, stack trace, and jmap distribution is attached.
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