[SPARK-23050] Structured Streaming with S3 file source duplicates data because of eventual consistency.

• Type: Bug
• Status: Resolved
• Priority: Major
• Resolution: Not A Problem
• Affects Version/s: 2.2.0
• Component/s: Structured Streaming
• Assignee: Unassigned
• Reporter: Yash Sharma
• Created: 11/Jan/18 23:29
• Updated: 07/Nov/18 15:52
• Resolved: 17/Jan/18 23:24

Description

Spark Structured streaming with S3 file source duplicates data because of eventual consistency.

Re producing the scenario -

• Structured streaming reading from S3 source. Writing back to S3.
• Spark tries to commitTask on completion of a task, by verifying if all the files have been written to Filesystem. ManifestFileCommitProtocol.commitTask.
• [Eventual consistency issue] Spark finds that the file is not present and fails the task. org.apache.spark.SparkException: Task failed while writing rows. No such file or directory 's3://path/data/part-00256-65ae782d-e32e-48fb-8652-e1d0defc370b-c000.snappy.parquet'
• By this time S3 eventually gets the file.
• Spark reruns the task and completes the task, but gets a new file name this time. ManifestFileCommitProtocol.newTaskTempFile. part-00256-b62fa7a4-b7e0-43d6-8c38-9705076a7ee1-c000.snappy.parquet.
• Data duplicates in results and the same data is processed twice and written to S3.
• There is no data duplication if spark is able to list presence of all committed files and all tasks succeed.

Code:

query = selected_df.writeStream \
    .format("parquet") \
    .option("compression", "snappy") \
    .option("path", "s3://path/data/") \
    .option("checkpointLocation", "s3://path/checkpoint/") \
    .start()

Same sized duplicate S3 Files:

$ aws s3 ls s3://path/data/ | grep part-00256
2018-01-11 03:37:00      17070 part-00256-65ae782d-e32e-48fb-8652-e1d0defc370b-c000.snappy.parquet
2018-01-11 03:37:10      17070 part-00256-b62fa7a4-b7e0-43d6-8c38-9705076a7ee1-c000.snappy.parquet

Exception on S3 listing and task failure:

[Stage 5:========================>                            (277 + 100) / 597]18/01/11 03:36:59 WARN TaskSetManager: Lost task 256.0 in stage 5.0 (TID  org.apache.spark.SparkException: Task failed while writing rows
 	at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:272)
 	at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1$$anonfun$apply$mcV$sp$1.apply(FileFormatWriter.scala:191)
 	at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1$$anonfun$apply$mcV$sp$1.apply(FileFormatWriter.scala:190)
 	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
 	at org.apache.spark.scheduler.Task.run(Task.scala:108)
 	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
 	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
 	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
 	at java.lang.Thread.run(Thread.java:748)
 Caused by: java.io.FileNotFoundException: No such file or directory 's3://path/data/part-00256-65ae782d-e32e-48fb-8652-e1d0defc370b-c000.snappy.parquet'
 	at com.amazon.ws.emr.hadoop.fs.s3n.S3NativeFileSystem.getFileStatus(S3NativeFileSystem.java:816)
 	at com.amazon.ws.emr.hadoop.fs.EmrFileSystem.getFileStatus(EmrFileSystem.java:509)
 	at org.apache.spark.sql.execution.streaming.ManifestFileCommitProtocol$$anonfun$4.apply(ManifestFileCommitProtocol.scala:109)
 	at org.apache.spark.sql.execution.streaming.ManifestFileCommitProtocol$$anonfun$4.apply(ManifestFileCommitProtocol.scala:109)
 	at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
 	at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
 	at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
 	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
 	at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
 	at scala.collection.AbstractTraversable.map(Traversable.scala:104)
 	at org.apache.spark.sql.execution.streaming.ManifestFileCommitProtocol.commitTask(ManifestFileCommitProtocol.scala:109)
 	at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:260)
 	at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:256)
 	at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1375)
 	at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:261)
 	... 8 more