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[SPARK-3237][SQL] Fix parquet filters with UDFs #2153

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[SPARK-3237][SQL] Fix parquet filters with UDFs #2153

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1e83f80
Clean udf functions.
marmbrus Aug 27, 2014
712731a
Use closure serializer for sending filters.
marmbrus Aug 27, 2014
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4 changes: 4 additions & 0 deletions sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUdf.scala
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Expand Up @@ -18,10 +18,14 @@
package org.apache.spark.sql.catalyst.expressions

import org.apache.spark.sql.catalyst.types.DataType
import org.apache.spark.util.ClosureCleaner

case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expression])
extends Expression {

// Clean function when not called with default no-arg constructor.
if (function != null) { ClosureCleaner.clean(function) }

type EvaluatedType = Any

def references = children.flatMap(_.references).toSet
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8 changes: 6 additions & 2 deletions sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetFilters.scala
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Expand Up @@ -17,6 +17,8 @@

package org.apache.spark.sql.parquet

import java.nio.ByteBuffer

import org.apache.hadoop.conf.Configuration

import parquet.filter._
Expand All @@ -25,6 +27,7 @@ import parquet.column.ColumnReader

import com.google.common.io.BaseEncoding

import org.apache.spark.SparkEnv
import org.apache.spark.sql.catalyst.types._
import org.apache.spark.sql.catalyst.expressions.{Predicate => CatalystPredicate}
import org.apache.spark.sql.catalyst.expressions._
Expand Down Expand Up @@ -237,7 +240,8 @@ object ParquetFilters {
*/
def serializeFilterExpressions(filters: Seq[Expression], conf: Configuration): Unit = {
if (filters.length > 0) {
val serialized: Array[Byte] = SparkSqlSerializer.serialize(filters)
val serialized: Array[Byte] =
SparkEnv.get.closureSerializer.newInstance().serialize(filters).array()
val encoded: String = BaseEncoding.base64().encode(serialized)
conf.set(PARQUET_FILTER_DATA, encoded)
}
Expand All @@ -252,7 +256,7 @@ object ParquetFilters {
val data = conf.get(PARQUET_FILTER_DATA)
if (data != null) {
val decoded: Array[Byte] = BaseEncoding.base64().decode(data)
SparkSqlSerializer.deserialize(decoded)
SparkEnv.get.closureSerializer.newInstance().deserialize(ByteBuffer.wrap(decoded))
} else {
Seq()
}
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