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[SPARK-28203][Core][Python] PythonRDD should respect SparkContext's hadoop configuration #25002

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[SPARK-28203][Core][Python] PythonRDD should respect SparkContext's hadoop configuration #25002

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[SPARK-28203][Core][Python] PythonRDD should respect SparkContext's h…
advancedxy Jun 28, 2019
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Add integration test for PythonRDD's job conf merge and move test of
advancedxy Jul 24, 2019
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2 changes: 1 addition & 1 deletion core/src/main/scala/org/apache/spark/api/python/PythonHadoopUtil.scala
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Expand Up @@ -156,7 +156,7 @@ private[python] object PythonHadoopUtil {
* Convert a [[java.util.Map]] of properties to a [[org.apache.hadoop.conf.Configuration]]
*/
def mapToConf(map: java.util.Map[String, String]): Configuration = {
val conf = new Configuration()
val conf = new Configuration(false)

@dongjoon-hyun dongjoon-hyun Jul 3, 2019 •
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I'm wondering if this doesn't break anything. Did you run the UT locally?

@advancedxy advancedxy Jul 3, 2019

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Internally this is only called in PythonRDD and I have replaced all the invocations with merged SparkContext's hadoop conf. So it shouldn't break things in spark side. I ran the UTs of Scala side, haven't run python unit tests though.

map.asScala.foreach { case (k, v) => conf.set(k, v) }
conf
}
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6 changes: 3 additions & 3 deletions core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
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Expand Up @@ -333,7 +333,7 @@ private[spark] object PythonRDD extends Logging {
valueConverterClass: String,
confAsMap: java.util.HashMap[String, String],
batchSize: Int): JavaRDD[Array[Byte]] = {
val conf = PythonHadoopUtil.mapToConf(confAsMap)
val conf = getMergedConf(confAsMap, sc.hadoopConfiguration())
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val rdd =
newAPIHadoopRDDFromClassNames[K, V, F](sc,
None, inputFormatClass, keyClass, valueClass, conf)
Expand Down Expand Up @@ -402,7 +402,7 @@ private[spark] object PythonRDD extends Logging {
valueConverterClass: String,
confAsMap: java.util.HashMap[String, String],
batchSize: Int): JavaRDD[Array[Byte]] = {
val conf = PythonHadoopUtil.mapToConf(confAsMap)
val conf = getMergedConf(confAsMap, sc.hadoopConfiguration())
val rdd =
hadoopRDDFromClassNames[K, V, F](sc,
None, inputFormatClass, keyClass, valueClass, conf)
Expand Down Expand Up @@ -618,7 +618,7 @@ private[spark] object PythonRDD extends Logging {
keyConverterClass: String,
valueConverterClass: String,
useNewAPI: Boolean): Unit = {
val conf = PythonHadoopUtil.mapToConf(confAsMap)
val conf = getMergedConf(confAsMap, pyRDD.context.hadoopConfiguration)
val converted = convertRDD(SerDeUtil.pythonToPairRDD(pyRDD, batchSerialized),
keyConverterClass, valueConverterClass, new JavaToWritableConverter)
if (useNewAPI) {
Expand Down
33 changes: 33 additions & 0 deletions core/src/test/scala/org/apache/spark/api/python/PythonHadoopUtilSuite.scala
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@@ -0,0 +1,33 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

package org.apache.spark.api.python

import scala.collection.JavaConverters._

import org.apache.spark.SparkFunSuite

class PythonHadoopUtilSuite extends SparkFunSuite {

test("mapToConf should not load defaults") {
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val map = Map("key" -> "value")
val conf = PythonHadoopUtil.mapToConf(map.asJava)
assert(conf.size() === map.size)
assert(conf.get("key") === map("key"))
}
}