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[SPARK-17356][SQL] Fix out of memory issue when generating JSON for TreeNode #14915

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[SPARK-17356][SQL] Fix out of memory issue when generating JSON for TreeNode #14915

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909f3bb
fix OOM issue when generating JSON
clockfly Sep 1, 2016
39f3c63
log warning if schema doesn't contain column for corrupted record
clockfly Sep 2, 2016
20fa7e3
address comment
clockfly Sep 5, 2016
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4 changes: 3 additions & 1 deletion sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/TreeNode.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -617,7 +617,9 @@ 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
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@clockfly clockfly Sep 1, 2016 •
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Current implementation of toJSON recursively searches the Map and Seq, and try to convert every field to JSON.

It is quite risky, since we don't know what data is stored in unknown Seq and Map, and it may easily trigger OOM if the Seq or Map is a huge object.

Maybe we should disable converting Seq and Map?

// it to JSON may trigger OutOfMemoryError.
case m: Metadata => Metadata.empty.jsonValue
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@cloud-fan cloud-fan Sep 6, 2016

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shall we use JNothing instead of Metadata.empty.jsonValue?

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@clockfly clockfly Sep 6, 2016

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No, we should not. JNothing is to map scala.Option.

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@cloud-fan cloud-fan Sep 6, 2016

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oh sorry, I mean JNull

case s: StorageLevel =>
("useDisk" -> s.useDisk) ~ ("useMemory" -> s.useMemory) ~ ("useOffHeap" -> s.useOffHeap) ~
("deserialized" -> s.deserialized) ~ ("replication" -> s.replication)
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10 changes: 9 additions & 1 deletion sql/core/src/test/scala/org/apache/spark/sql/QueryTest.scala
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Expand Up @@ -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 {
Expand Down Expand Up @@ -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)
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@yhuai yhuai Sep 1, 2016

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If we have https://github.com/apache/spark/pull/14915/files#diff-eac5b02bb450a235fef5e902a2671254R623, do we still need these?

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@yhuai yhuai Sep 1, 2016

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It will be good to have a test. The test can check that the json representation does not have metadata.

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@clockfly clockfly Sep 1, 2016

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@yhuai

It is covered by existing QueryTest. In QueryTest, it will call toJSON and then call fromJSON to convert JSON back to a plan, and do comparison like this:

    if (normalized1 != normalized2) {
      fail(
        s"""
           |== FAIL: the logical plan parsed from json does not match the original one ===
           |${sideBySide(logicalPlan.treeString, normalized2.treeString).mkString("\n")}
          """.stripMargin)
    }

If the Meta data is not empty, the comparison will fail.

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@yhuai yhuai Sep 1, 2016

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OK. Let's explain why we do remove the metadata at here. Basically, I think we need to explain because json string does not have metadata, we remove the metadata from the normalized plan. So, we can do the check.

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@yhuai yhuai Sep 1, 2016

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(just make the comment a little bit more clear)

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@clockfly clockfly Sep 2, 2016

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ok

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@clockfly clockfly Sep 2, 2016

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fixed

}

// RDDs/data are not serializable to JSON, so we need to collect LogicalPlans that contains
Expand Down