[jira] [Updated] (CARBONDATA-1781) (Carbon1.3.0 - Streaming) Select * & select column fails but select count(*) is success when .streaming file is removed from HDFS or thrift server is killed when streaming in progress

[Akash R Nilugal (Jira)]

     [ https://issues.apache.org/jira/browse/CARBONDATA-1781?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Chetan Bhat updated CARBONDATA-1781:
------------------------------------
    Description:
*Steps :*
Thrift server is started 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"

Spark shell is opened 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

From spark shell the below code is executed -
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/carbon.store")
   
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 = "brinjal"

sql(s"drop table brinjal").show

sql(s"create table brinjal (imei string,AMSize string,channelsId string,ActiveCountry string, Activecity string,gamePointId double,deviceInformationId double,productionDate Timestamp,deliveryDate timestamp,deliverycharge double) STORED BY 'org.apache.carbondata.format' TBLPROPERTIES('streaming'='true','table_blocksize'='1')")

sql(s"LOAD DATA INPATH 'hdfs://hacluster/chetan/vardhandaterestruct.csv' INTO TABLE brinjal OPTIONS('DELIMITER'=',', 'QUOTECHAR'= '','BAD_RECORDS_ACTION'='FORCE','FILEHEADER'= 'imei,deviceInformationId,AMSize,channelsId,ActiveCountry,Activecity,gamePointId,productionDate,deliveryDate,deliverycharge')")


val carbonTable = CarbonEnv.getInstance(carbonSession).carbonMetastore.
  lookupRelation(Some("default"), streamTableName)(carbonSession).asInstanceOf[CarbonRelation].carbonTable

val tablePath = CarbonStorePath.getCarbonTablePath(carbonTable.getAbsoluteTableIdentifier)

val port = 8002
val serverSocket = new ServerSocket(port)
val socketThread = writeSocket(serverSocket)
val streamingThread = startStreaming(carbonSession, tablePath, streamTableName, port)

From other terminal user deletes the .streaming file - BLR1000014307:/srv/spark2.2Bigdata/install/hadoop/datanode # bin/hadoop fs -rm -r /user/hive/warehouse/carbon.store/default/brinjal/.streaming
17/11/20 19:02:11 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Deleted /user/hive/warehouse/carbon.store/default/brinjal/.streaming

Also the thrift server spark submit process is killed when streaming is in progress.

From beeline session user executes the select * , select column and select count queries.

*Issue : Select * and select column queries fail and throw exception while select count(*) displays result set.*. Same issue occurs when the thrift server spark submit process is killed when streaming is in progress.

0: jdbc:hive2://10.18.98.34:23040> select * from brinjal;
Error: org.apache.spark.SparkException: Job aborted due to stage failure: Task 4 in stage 17.0 failed 4 times, most recent failure: Lost task 4.3 in stage 17.0 (TID 120, BLR1000014307, executor 12): 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)
0: jdbc:hive2://10.18.98.34:23040> select imei from brinjal;
Error: org.apache.spark.SparkException: Job aborted due to stage failure: Task 5 in stage 18.0 failed 4 times, most recent failure: Lost task 5.3 in stage 18.0 (TID 136, BLR1000014307, executor 13): 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)

0: jdbc:hive2://10.18.98.34:23040> select count(*) from brinjal;
+-----------+--+
| count(1)  |
+-----------+--+
| 11916     |
+-----------+--+
1 row selected (0.545 seconds)


*Expected : The behavior of select * and select column should be consistent with the select count(*) behavior for streaming query.*





  was:
*Steps :*
Thrift server is started 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"

Spark shell is opened 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

From spark shell the below code is executed -
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/carbon.store")
   
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 = "brinjal"

sql(s"drop table brinjal").show

sql(s"create table brinjal (imei string,AMSize string,channelsId string,ActiveCountry string, Activecity string,gamePointId double,deviceInformationId double,productionDate Timestamp,deliveryDate timestamp,deliverycharge double) STORED BY 'org.apache.carbondata.format' TBLPROPERTIES('streaming'='true','table_blocksize'='1')")

sql(s"LOAD DATA INPATH 'hdfs://hacluster/chetan/vardhandaterestruct.csv' INTO TABLE brinjal OPTIONS('DELIMITER'=',', 'QUOTECHAR'= '','BAD_RECORDS_ACTION'='FORCE','FILEHEADER'= 'imei,deviceInformationId,AMSize,channelsId,ActiveCountry,Activecity,gamePointId,productionDate,deliveryDate,deliverycharge')")


val carbonTable = CarbonEnv.getInstance(carbonSession).carbonMetastore.
  lookupRelation(Some("default"), streamTableName)(carbonSession).asInstanceOf[CarbonRelation].carbonTable

val tablePath = CarbonStorePath.getCarbonTablePath(carbonTable.getAbsoluteTableIdentifier)

val port = 8002
val serverSocket = new ServerSocket(port)
val socketThread = writeSocket(serverSocket)
val streamingThread = startStreaming(carbonSession, tablePath, streamTableName, port)

From other terminal user deletes the .streaming file - BLR1000014307:/srv/spark2.2Bigdata/install/hadoop/datanode # bin/hadoop fs -rm -r /user/hive/warehouse/carbon.store/default/brinjal/.streaming
17/11/20 19:02:11 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Deleted /user/hive/warehouse/carbon.store/default/brinjal/.streaming

From beeline session user executes the select * , select column and select count queries.

*Issue : Select * and select column queries fail and throw exception while select count(*) displays result set.*

0: jdbc:hive2://10.18.98.34:23040> select * from brinjal;
Error: org.apache.spark.SparkException: Job aborted due to stage failure: Task 4 in stage 17.0 failed 4 times, most recent failure: Lost task 4.3 in stage 17.0 (TID 120, BLR1000014307, executor 12): 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)
0: jdbc:hive2://10.18.98.34:23040> select imei from brinjal;
Error: org.apache.spark.SparkException: Job aborted due to stage failure: Task 5 in stage 18.0 failed 4 times, most recent failure: Lost task 5.3 in stage 18.0 (TID 136, BLR1000014307, executor 13): 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)

0: jdbc:hive2://10.18.98.34:23040> select count(*) from brinjal;
+-----------+--+
| count(1)  |
+-----------+--+
| 11916     |
+-----------+--+
1 row selected (0.545 seconds)


*Expected : The behavior of select * and select column should be consistent with the select count(*) behavior for streaming query.*

> (Carbon1.3.0 - Streaming) Select * & select column fails but select count(*) is success when .streaming file is removed from HDFS or thrift server is killed when streaming in progress
> ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
>
>                 Key: CARBONDATA-1781
>                 URL: https://issues.apache.org/jira/browse/CARBONDATA-1781
>             Project: CarbonData
>          Issue Type: Bug
>          Components: data-query
>    Affects Versions: 1.3.0
>         Environment: 3 node ant cluster
>            Reporter: Chetan Bhat
>              Labels: DFX
>
> *Steps :*
> Thrift server is started 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"
> Spark shell is opened 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
> From spark shell the below code is executed -
> 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/carbon.store")
>    
> 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 = "brinjal"
> sql(s"drop table brinjal").show
> sql(s"create table brinjal (imei string,AMSize string,channelsId string,ActiveCountry string, Activecity string,gamePointId double,deviceInformationId double,productionDate Timestamp,deliveryDate timestamp,deliverycharge double) STORED BY 'org.apache.carbondata.format' TBLPROPERTIES('streaming'='true','table_blocksize'='1')")
> sql(s"LOAD DATA INPATH 'hdfs://hacluster/chetan/vardhandaterestruct.csv' INTO TABLE brinjal OPTIONS('DELIMITER'=',', 'QUOTECHAR'= '','BAD_RECORDS_ACTION'='FORCE','FILEHEADER'= 'imei,deviceInformationId,AMSize,channelsId,ActiveCountry,Activecity,gamePointId,productionDate,deliveryDate,deliverycharge')")
> val carbonTable = CarbonEnv.getInstance(carbonSession).carbonMetastore.
>   lookupRelation(Some("default"), streamTableName)(carbonSession).asInstanceOf[CarbonRelation].carbonTable
> val tablePath = CarbonStorePath.getCarbonTablePath(carbonTable.getAbsoluteTableIdentifier)
> val port = 8002
> val serverSocket = new ServerSocket(port)
> val socketThread = writeSocket(serverSocket)
> val streamingThread = startStreaming(carbonSession, tablePath, streamTableName, port)
> From other terminal user deletes the .streaming file - BLR1000014307:/srv/spark2.2Bigdata/install/hadoop/datanode # bin/hadoop fs -rm -r /user/hive/warehouse/carbon.store/default/brinjal/.streaming
> 17/11/20 19:02:11 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
> Deleted /user/hive/warehouse/carbon.store/default/brinjal/.streaming
> Also the thrift server spark submit process is killed when streaming is in progress.
> From beeline session user executes the select * , select column and select count queries.
> *Issue : Select * and select column queries fail and throw exception while select count(*) displays result set.*. Same issue occurs when the thrift server spark submit process is killed when streaming is in progress.
> 0: jdbc:hive2://10.18.98.34:23040> select * from brinjal;
> Error: org.apache.spark.SparkException: Job aborted due to stage failure: Task 4 in stage 17.0 failed 4 times, most recent failure: Lost task 4.3 in stage 17.0 (TID 120, BLR1000014307, executor 12): 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$$anonfun$apply$25.apply(RDD.scala:826)
>         at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>         at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
>         at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
>         at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
>         at org.apache.spark.scheduler.Task.run(Task.scala:99)
>         at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
>         at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
>         at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
>         at java.lang.Thread.run(Thread.java:745)
> Driver stacktrace: (state=,code=0)
> 0: jdbc:hive2://10.18.98.34:23040> select imei from brinjal;
> Error: org.apache.spark.SparkException: Job aborted due to stage failure: Task 5 in stage 18.0 failed 4 times, most recent failure: Lost task 5.3 in stage 18.0 (TID 136, BLR1000014307, executor 13): java.io.EOFException
>         at org.apache.carbondata.hadoop.streaming.StreamBlockletReader.readBytesFromStream(StreamBlockletReader.java:182)
>         at org.apache.carbondata.hadoop.streaming.StreamBlockletReader.readBlockletData(StreamBlockletReader.java:116)
>         at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.scanBlockletAndFillVector(CarbonStreamRecordReader.java:406)
>         at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.nextColumnarBatch(CarbonStreamRecordReader.java:317)
>         at org.apache.carbondata.hadoop.streaming.CarbonStreamRecordReader.nextKeyValue(CarbonStreamRecordReader.java:298)
>         at org.apache.carbondata.spark.rdd.CarbonScanRDD$$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)
> 0: jdbc:hive2://10.18.98.34:23040> select count(*) from brinjal;
> +-----------+--+
> | count(1)  |
> +-----------+--+
> | 11916     |
> +-----------+--+
> 1 row selected (0.545 seconds)
> *Expected : The behavior of select * and select column should be consistent with the select count(*) behavior for streaming query.*

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