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Posted to issues@carbondata.apache.org by "Jatin (JIRA)" <ji...@apache.org> on 2017/12/21 06:33:00 UTC
[jira] [Comment Edited] (CARBONDATA-1775) (Carbon1.3.0 - Streaming)
Select query fails with java.io.EOFException when data streaming is in
progress
[ https://issues.apache.org/jira/browse/CARBONDATA-1775?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16299617#comment-16299617 ]
Jatin edited comment on CARBONDATA-1775 at 12/21/17 6:32 AM:
-------------------------------------------------------------
[~chetdb] Not able to replicate with the latest jar.
This issue is fixed with PR :
https://github.com/apache/carbondata/pull/1621
was (Author: jatin demla):
[~chetdb] Not able to replicate with the latest jar.
> (Carbon1.3.0 - Streaming) Select query fails with java.io.EOFException when data streaming is in progress
> ----------------------------------------------------------------------------------------------------------
>
> Key: CARBONDATA-1775
> URL: https://issues.apache.org/jira/browse/CARBONDATA-1775
> Project: CarbonData
> Issue Type: Bug
> Components: data-query
> Affects Versions: 1.3.0
> Environment: 3 node ant cluster
> Reporter: Chetan Bhat
> Labels: DFX
>
> Steps :
> User starts the thrift server using the command - bin/spark-submit --master yarn-client --executor-memory 10G --executor-cores 5 --driver-memory 5G --num-executors 3 --class org.apache.carbondata.spark.thriftserver.CarbonThriftServer /srv/spark2.2Bigdata/install/spark/sparkJdbc/carbonlib/carbondata_2.11-1.3.0-SNAPSHOT-shade-hadoop2.7.2.jar "hdfs://hacluster/user/hive/warehouse/carbon.store"
> User connects to spark shell using the command - bin/spark-shell --master yarn-client --executor-memory 10G --executor-cores 5 --driver-memory 5G --num-executors 3 --jars /srv/spark2.2Bigdata/install/spark/sparkJdbc/carbonlib/carbondata_2.11-1.3.0-SNAPSHOT-shade-hadoop2.7.2.jar
> In spark shell User creates a table and does streaming load in the table as per the below socket streaming script.
> import java.io.{File, PrintWriter}
> import java.net.ServerSocket
> import org.apache.spark.sql.{CarbonEnv, SparkSession}
> import org.apache.spark.sql.hive.CarbonRelation
> import org.apache.spark.sql.streaming.{ProcessingTime, StreamingQuery}
> import org.apache.carbondata.core.constants.CarbonCommonConstants
> import org.apache.carbondata.core.util.CarbonProperties
> import org.apache.carbondata.core.util.path.{CarbonStorePath, CarbonTablePath}
> CarbonProperties.getInstance().addProperty(CarbonCommonConstants.CARBON_TIMESTAMP_FORMAT, "yyyy/MM/dd")
> import org.apache.spark.sql.CarbonSession._
> val carbonSession = SparkSession.
> builder().
> appName("StreamExample").
> getOrCreateCarbonSession("hdfs://hacluster/user/hive/warehouse/david")
>
> carbonSession.sparkContext.setLogLevel("INFO")
> def sql(sql: String) = carbonSession.sql(sql)
> def writeSocket(serverSocket: ServerSocket): Thread = {
> val thread = new Thread() {
> override def run(): Unit = {
> // wait for client to connection request and accept
> val clientSocket = serverSocket.accept()
> val socketWriter = new PrintWriter(clientSocket.getOutputStream())
> var index = 0
> for (_ <- 1 to 1000) {
> // write 5 records per iteration
> for (_ <- 0 to 100) {
> index = index + 1
> socketWriter.println(index.toString + ",name_" + index
> + ",city_" + index + "," + (index * 10000.00).toString +
> ",school_" + index + ":school_" + index + index + "$" + index)
> }
> socketWriter.flush()
> Thread.sleep(2000)
> }
> socketWriter.close()
> System.out.println("Socket closed")
> }
> }
> thread.start()
> thread
> }
>
> def startStreaming(spark: SparkSession, tablePath: CarbonTablePath, tableName: String, port: Int): Thread = {
> val thread = new Thread() {
> override def run(): Unit = {
> var qry: StreamingQuery = null
> try {
> val readSocketDF = spark.readStream
> .format("socket")
> .option("host", "10.18.98.34")
> .option("port", port)
> .load()
> qry = readSocketDF.writeStream
> .format("carbondata")
> .trigger(ProcessingTime("5 seconds"))
> .option("checkpointLocation", tablePath.getStreamingCheckpointDir)
> .option("tablePath", tablePath.getPath).option("tableName", tableName)
> .start()
> qry.awaitTermination()
> } catch {
> case ex: Throwable =>
> ex.printStackTrace()
> println("Done reading and writing streaming data")
> } finally {
> qry.stop()
> }
> }
> }
> thread.start()
> thread
> }
> val streamTableName = "stream_table"
> sql(s"CREATE TABLE $streamTableName (id INT,name STRING,city STRING,salary FLOAT) STORED BY 'carbondata' TBLPROPERTIES('streaming'='true', 'sort_columns'='name')")
> sql(s"LOAD DATA LOCAL INPATH 'hdfs://hacluster/tmp/streamSample.csv' INTO TABLE $streamTableName OPTIONS('HEADER'='true')")
> sql(s"select * from $streamTableName").show
> val carbonTable = CarbonEnv.getInstance(carbonSession).carbonMetastore.
> lookupRelation(Some("default"), streamTableName)(carbonSession).asInstanceOf[CarbonRelation].carbonTable
> val tablePath = CarbonStorePath.getCarbonTablePath(carbonTable.getAbsoluteTableIdentifier)
> val port = 7995
> val serverSocket = new ServerSocket(port)
> val socketThread = writeSocket(serverSocket)
> val streamingThread = startStreaming(carbonSession, tablePath, streamTableName, port)
> While load is in progress user executes select query on the streaming table from beeline.
> 0: jdbc:hive2://10.18.98.34:23040> select * from stream_table;
> *Issue : The Select query fails with java.io.EOFException when socket streaming is in progress.*
> 0: jdbc:hive2://10.18.98.34:23040> select * from stream_table;
> Error: org.apache.spark.SparkException: Job aborted due to stage failure: Task 3 in stage 1.0 failed 4 times, most recent failure: Lost task 3.3 in stage 1.0 (TID 38, BLR1000014278, executor 7): java.io.EOFException
> at org.apache.carbondata.hadoop.streaming.StreamBlockletReader.readBytesFromStream(StreamBlockletReader.java:182)
> at org.apache.carbondata.hadoop.streaming.StreamBlockletReader.readBlockletData(StreamBlockletReader.java:116)
> at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.scanBlockletAndFillVector(CarbonStreamRecordReader.java:406)
> at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.nextColumnarBatch(CarbonStreamRecordReader.java:317)
> at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.nextKeyValue(CarbonStreamRecordReader.java:298)
> at org.apache.carbondata.spark.rdd.CarbonScanRDD$$anon$1.hasNext(CarbonScanRDD.scala:298)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.scan_nextBatch$(Unknown Source)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
> at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
> at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:231)
> at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:225)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
> at org.apache.spark.scheduler.Task.run(Task.scala:99)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Driver stacktrace: (state=,code=0)
> *Also when user checks the spark shell terminal there are exceptions thrown.*
> scala> org.apache.spark.sql.streaming.StreamingQueryException: Offsets committed out of order: 100999 followed by 100 scala.sys.package$.error(package.scala:27)
> org.apache.spark.sql.execution.streaming.TextSocketSource.commit(socket.scala:151)
> org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$constructNextBatch$2$$anonfun$apply$mcV$sp$4.apply(StreamExecution.scala:421)
> org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$constructNextBatch$2$$anonfun$apply$mcV$sp$4.apply(StreamExecution.scala:420)
> scala.collection.Iterator$class.foreach(Iterator.scala:893)
> scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
> scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
> org.apache.spark.sql.execution.streaming.StreamProgress.foreach(StreamProgress.scala:25)
> org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$constructNextBatch$2.apply$mcV$sp(StreamExecution.scala:420)
> org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$constructNextBatch$2.apply(StreamExecution.scala:404)
> === Streaming Query ===
> Identifier: [id = d23c5633-e747-457e-a5c0-69ec09bb183f, runId = 2db93553-fe97-4fa6-b425-278128a42f50]
> Current Offsets: {org.apache.spark.sql.execution.streaming.TextSocketSource@750267f5: 100}
> Current State: ACTIVE
> Thread State: RUNNABLE
> Logical Plan:
> org.apache.spark.sql.execution.streaming.TextSocketSource@750267f5
> at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches(StreamExecution.scala:284)
> at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:177)
> Caused by: java.lang.RuntimeException: Offsets committed out of order: 100999 followed by 100
> at scala.sys.package$.error(package.scala:27)
> at org.apache.spark.sql.execution.streaming.TextSocketSource.commit(socket.scala:151)
> at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$constructNextBatch$2$$anonfun$apply$mcV$sp$4.apply(StreamExecution.scala:421)
> at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$constructNextBatch$2$$anonfun$apply$mcV$sp$4.apply(StreamExecution.scala:420)
> at scala.collection.Iterator$class.foreach(Iterator.scala:893)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
> at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
> at org.apache.spark.sql.execution.streaming.StreamProgress.foreach(StreamProgress.scala:25)
> at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$constructNextBatch$2.apply$mcV$sp(StreamExecution.scala:420)
> at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$constructNextBatch$2.apply(StreamExecution.scala:404)
> at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$constructNextBatch$2.apply(StreamExecution.scala:404)
> at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:262)
> at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:46)
> at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$constructNextBatch(StreamExecution.scala:404)
> at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1$$anonfun$1.apply$mcV$sp(StreamExecution.scala:250)
> at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1$$anonfun$1.apply(StreamExecution.scala:244)
> at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1$$anonfun$1.apply(StreamExecution.scala:244)
> at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:262)
> at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:46)
> at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1.apply$mcZ$sp(StreamExecution.scala:244)
> at org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:43)
> at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches(StreamExecution.scala:239)
> ... 1 more
> Done reading and writing streaming data
> *Expected Output : select query should be successful from beeline on the streaming table.*
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