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[SPARK-11328][SQL] Improve error message when hitting this issue

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The issue is that the output commiter is not idempotent and retry attempts will
fail because the output file already exists. It is not safe to clean up the file
as this output committer is by design not retryable. Currently, the job fails
with a confusing file exists error. This patch is a stop gap to tell the user
to look at the top of the error log for the proper message.

This is difficult to test locally as Spark is hardcoded not to retry. Manually
verified by upping the retry attempts.

Author: Nong Li <nong@databricks.com>
Author: Nong Li <nongli@gmail.com>

Closes #10080 from nongli/spark-11328.
This commit is contained in:
Nong Li 2015-12-01 15:30:21 -08:00 committed by Yin Huai
parent ef6790fdc3
commit 47a0abc343
2 changed files with 22 additions and 3 deletions
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22
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/WriterContainer.scala
View file

@ -124,6 +124,24 @@ private[sql] abstract class BaseWriterContainer(
}
}
protected def newOutputWriter(path: String): OutputWriter = {
try {
outputWriterFactory.newInstance(path, dataSchema, taskAttemptContext)
} catch {
case e: org.apache.hadoop.fs.FileAlreadyExistsException =>
if (outputCommitter.isInstanceOf[parquet.DirectParquetOutputCommitter]) {
// Spark-11382: DirectParquetOutputCommitter is not idempotent, meaning on retry
// attempts, the task will fail because the output file is created from a prior attempt.
// This often means the most visible error to the user is misleading. Augment the error
// to tell the user to look for the actual error.
throw new SparkException("The output file already exists but this could be due to a " +
"failure from an earlier attempt. Look through the earlier logs or stage page for " +
"the first error.\n File exists error: " + e)
}
throw e
}
}
private def newOutputCommitter(context: TaskAttemptContext): OutputCommitter = {
val defaultOutputCommitter = outputFormatClass.newInstance().getOutputCommitter(context)
@ -234,7 +252,7 @@ private[sql] class DefaultWriterContainer(
executorSideSetup(taskContext)
val configuration = SparkHadoopUtil.get.getConfigurationFromJobContext(taskAttemptContext)
configuration.set("spark.sql.sources.output.path", outputPath)
val writer = outputWriterFactory.newInstance(getWorkPath, dataSchema, taskAttemptContext)
val writer = newOutputWriter(getWorkPath)
writer.initConverter(dataSchema)
var writerClosed = false
@ -403,7 +421,7 @@ private[sql] class DynamicPartitionWriterContainer(
val configuration = SparkHadoopUtil.get.getConfigurationFromJobContext(taskAttemptContext)
configuration.set(
"spark.sql.sources.output.path", new Path(outputPath, partitionPath).toString)
val newWriter = outputWriterFactory.newInstance(path.toString, dataSchema, taskAttemptContext)
val newWriter = super.newOutputWriter(path.toString)
newWriter.initConverter(dataSchema)
newWriter
}

3
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/DirectParquetOutputCommitter.scala
View file

@ -41,7 +41,8 @@ import org.apache.parquet.hadoop.{ParquetFileReader, ParquetFileWriter, ParquetO
* no safe way undo a failed appending job (that's why both `abortTask()` and `abortJob()` are
* left empty).
*/
private[parquet] class DirectParquetOutputCommitter(outputPath: Path, context: TaskAttemptContext)
private[datasources] class DirectParquetOutputCommitter(
outputPath: Path, context: TaskAttemptContext)
extends ParquetOutputCommitter(outputPath, context) {
val LOG = Log.getLog(classOf[ParquetOutputCommitter])