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[SPARK-5068][SQL]fix bug query data when path doesn't exists #3907

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19 changes: 14 additions & 5 deletions core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala
Original file line number Diff line number Diff line change
Expand Up @@ -35,6 +35,7 @@ import org.apache.hadoop.mapred.Reporter
import org.apache.hadoop.mapred.JobID
import org.apache.hadoop.mapred.TaskAttemptID
import org.apache.hadoop.mapred.TaskID
import org.apache.hadoop.mapred.InvalidInputException
import org.apache.hadoop.util.ReflectionUtils

import org.apache.spark._
Expand Down Expand Up @@ -198,12 +199,20 @@ class HadoopRDD[K, V](
if (inputFormat.isInstanceOf[Configurable]) {
inputFormat.asInstanceOf[Configurable].setConf(jobConf)
}
val inputSplits = inputFormat.getSplits(jobConf, minPartitions)
val array = new Array[Partition](inputSplits.size)
for (i <- 0 until inputSplits.size) {
array(i) = new HadoopPartition(id, i, inputSplits(i))
// SPARK-5068:catch the exception when the path is not exists
try {
val inputSplits = inputFormat.getSplits(jobConf, minPartitions)
val array = new Array[Partition](inputSplits.size)
for (i <- 0 until inputSplits.size) {
array(i) = new HadoopPartition(id, i, inputSplits(i))
}
array
} catch {
case e: InvalidInputException => {
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Is there a more direct and reliable way to detect if the path doesn't exist here than catching a general exception? this risks silently swallowing errors

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what about to give a log warning when the path is not found?

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I guess throwing exception is the way how InputFormat handle the non-existed file. I agree with @srowen , we couldn't just ignore the error here. Probably it's better to leave the current implementation unchanged.

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Thanks for review.In my understanding,this method is get the data for specific partition by return Array[Partition].I think get when we pass the wrong path and we return an empty array is OK.

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The HadoopRDD is general API for reading files, I don't think it's acceptable the API just keep silence if the specified path doesn't exist, throwing an exception probably better.

Take the JDK class FileReader for example:
http://docs.oracle.com/javase/7/docs/api/java/io/FileReader.html#FileReader(java.io.File)

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I found Shark is check for the path when the RDD was constructed(a little bit like my last PR),but i agree with @marmbrus that will slow down when constructing RDD especially a lot of partitions.

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Ok, I understand the background now.
You're right, we do need to follow the Hive's behavior, the non-existed partition will returns an empty record iterator, other than throw exception. However, this should be LIMITED within Hive TableReader, not here.

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And of course, or we can add a new parameter for HadoopRDD (e.g. throwExceptionOnError: Boolean = true ?), to support the case you described.

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Agree with @chenghao-intel, we'd better handle this in hive module.

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Thanks for review!I have two questions:
1.How could i limited within hive by catch exption instead of using fs.exists to find out the wrong patition?
2.Could add a new parameter in HadoopRDD affect more code?

logWarning("InvalidInput!", e)
new Array[Partition](0)
}
}
array
}

override def compute(theSplit: Partition, context: TaskContext): InterruptibleIterator[(K, V)] = {
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,66 @@
/*
* 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.sql.hive

import java.io.File

import com.google.common.io.Files
import org.apache.spark.sql.{QueryTest, _}
import org.apache.spark.sql.hive.test.TestHive
/* Implicits */
import org.apache.spark.sql.hive.test.TestHive._


class QueryPartitionSuite extends QueryTest {

test("SPARK-5068: query data when path doesn't exists"){
val testData = TestHive.sparkContext.parallelize(
(1 to 10).map(i => TestData(i, i.toString)))
testData.registerTempTable("testData")

val tmpDir = Files.createTempDir()
//create the table for test
sql(s"CREATE TABLE table_with_partition(key int,value string) PARTITIONED by (ds string) location '${tmpDir.toURI.toString}' ")
sql("INSERT OVERWRITE TABLE table_with_partition partition (ds='1') SELECT key,value FROM testData")
sql("INSERT OVERWRITE TABLE table_with_partition partition (ds='2') SELECT key,value FROM testData")
sql("INSERT OVERWRITE TABLE table_with_partition partition (ds='3') SELECT key,value FROM testData")
sql("INSERT OVERWRITE TABLE table_with_partition partition (ds='4') SELECT key,value FROM testData")
//test for the exist path
checkAnswer(sql("select key,value from table_with_partition"),
testData.collect.toSeq ++ testData.collect.toSeq ++ testData.collect.toSeq ++ testData.collect.toSeq)

//delect the path of one partition
val folders = tmpDir.listFiles.filter(_.isDirectory).toList
def deleteAll(file:File){
if (file.isDirectory()) {
for (f:File <-file.listFiles()) {
deleteAll(f);
}
}
file.delete();
}
deleteAll(folders(0))

//test for the affter delete the path
checkAnswer(sql("select key,value from table_with_partition"),
testData.collect.toSeq ++ testData.collect.toSeq ++ testData.collect.toSeq)

sql("DROP TABLE table_with_partition")
sql("DROP TABLE createAndInsertTest")
}
}