[
https://issues.apache.org/jira/browse/CARBONDATA-1726?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Chetan Bhat updated CARBONDATA-1726:
------------------------------------
Description:
Steps :
// prepare csv file for batch loading
cd /srv/spark2.2Bigdata/install/hadoop/datanode/bin
// generate streamSample.csv
100000001,batch_1,city_1,0.1,school_1:school_11$20
100000002,batch_2,city_2,0.2,school_2:school_22$30
100000003,batch_3,city_3,0.3,school_3:school_33$40
100000004,batch_4,city_4,0.4,school_4:school_44$50
100000005,batch_5,city_5,0.5,school_5:school_55$60
// put to hdfs /tmp/streamSample.csv
./hadoop fs -put streamSample.csv /tmp
// spark-beeline
cd /srv/spark2.2Bigdata/install/spark/sparkJdbc
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/sparkhive/warehouse"
bin/beeline -u jdbc:hive2://10.18.98.34:23040
CREATE TABLE stream_table(
id INT,
name STRING,
city STRING,
salary FLOAT
)
STORED BY 'carbondata'
TBLPROPERTIES('streaming'='true', 'sort_columns'='name');
LOAD DATA LOCAL INPATH 'hdfs://hacluster/chetan/streamSample.csv' INTO TABLE
stream_table OPTIONS('HEADER'='false');
// spark-shell
cd /srv/spark2.2Bigdata/install/spark/sparkJdbc
bin/spark-shell --master yarn-client
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").
config("spark.sql.warehouse.dir",
"hdfs://hacluster/user/sparkhive/warehouse").
config("javax.jdo.option.ConnectionURL",
"jdbc:mysql://10.18.98.34:3306/sparksql?characterEncoding=UTF-8").
config("javax.jdo.option.ConnectionDriverName", "com.mysql.jdbc.Driver").
config("javax.jdo.option.ConnectionPassword", "huawei").
config("javax.jdo.option.ConnectionUserName", "sparksql").
getOrCreateCarbonSession()
carbonSession.sparkContext.setLogLevel("ERROR")
carbonSession.sql("select * from stream_table").show
Issue : Select query from spark-shell does not execute successfully for
streaming table load.
When the executor and driver cores and memory is increased while launching the
spark shell the issue still occurs.
bin/spark-shell --master yarn-client --executor-memory 10G --executor-cores 5
--driver-memory 5G --num-executors 3
scala> import org.apache.carbondata.core.constants.CarbonCommonConstants
import org.apache.carbondata.core.constants.CarbonCommonConstants
scala> import org.apache.carbondata.core.util.CarbonProperties
import org.apache.carbondata.core.util.CarbonProperties
scala> import org.apache.carbondata.core.util.path.{CarbonStorePath,
CarbonTablePath}
import org.apache.carbondata.core.util.path.{CarbonStorePath, CarbonTablePath}
scala>
scala>
CarbonProperties.getInstance().addProperty(CarbonCommonConstants.CARBON_TIMESTAMP_FORMAT,
"yyyy/MM/dd")
res29: org.apache.carbondata.core.util.CarbonProperties =
org.apache.carbondata.core.util.CarbonProperties@67b056e7
scala>
scala> import org.apache.spark.sql.CarbonSession._
import org.apache.spark.sql.CarbonSession._
scala>
scala> val carbonSession = SparkSession.
| builder().
| appName("StreamExample").
| config("spark.sql.warehouse.dir",
"hdfs://hacluster/user/sparkhive/warehouse").
| config("javax.jdo.option.ConnectionURL",
"jdbc:mysql://10.18.98.34:3306/sparksql?characterEncoding=UTF-8").
| config("javax.jdo.option.ConnectionDriverName",
"com.mysql.jdbc.Driver").
| config("javax.jdo.option.ConnectionPassword", "huawei").
| config("javax.jdo.option.ConnectionUserName", "sparksql").
| getOrCreateCarbonSession()
carbonSession: org.apache.spark.sql.SparkSession =
org.apache.spark.sql.CarbonSession@1d0590bc
scala>
| carbonSession.sparkContext.setLogLevel("ERROR")
scala> carbonSession.sql("select * from stream_table").show
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in
stage 25.0 failed 4 times, most recent failure: Lost task 0.3 in stage 25.0
(TID 65, BLR1000014269, executor 8): java.lang.IllegalStateException: unread
block data
at
java.io.ObjectInputStream$BlockDataInputStream.setBlockDataMode(ObjectInputStream.java:2424)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1383)
at
java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
at
org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
at
org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:114)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:258)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at scala.Option.foreach(Option.scala:257)
at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1918)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1931)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:333)
at
org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
at
org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2371)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2765)
at
org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2370)
at
org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2377)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2113)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2112)
at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2795)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2112)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2327)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:248)
at org.apache.spark.sql.Dataset.show(Dataset.scala:636)
at org.apache.spark.sql.Dataset.show(Dataset.scala:595)
at org.apache.spark.sql.Dataset.show(Dataset.scala:604)
... 50 elided
Caused by: java.lang.IllegalStateException: unread block data
at
java.io.ObjectInputStream$BlockDataInputStream.setBlockDataMode(ObjectInputStream.java:2424)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1383)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
at
org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
at
org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:114)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:258)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Expected : Select query from spark-shell should execute successfully for
streaming table load.
was:
Steps :
// prepare csv file for batch loading
cd /srv/spark2.2Bigdata/install/hadoop/datanode/bin
// generate streamSample.csv
100000001,batch_1,city_1,0.1,school_1:school_11$20
100000002,batch_2,city_2,0.2,school_2:school_22$30
100000003,batch_3,city_3,0.3,school_3:school_33$40
100000004,batch_4,city_4,0.4,school_4:school_44$50
100000005,batch_5,city_5,0.5,school_5:school_55$60
// put to hdfs /tmp/streamSample.csv
./hadoop fs -put streamSample.csv /tmp
// spark-beeline
cd /srv/spark2.2Bigdata/install/spark/sparkJdbc
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/sparkhive/warehouse"
bin/beeline -u jdbc:hive2://10.18.98.34:23040
CREATE TABLE stream_table(
id INT,
name STRING,
city STRING,
salary FLOAT
)
STORED BY 'carbondata'
TBLPROPERTIES('streaming'='true', 'sort_columns'='name');
LOAD DATA LOCAL INPATH 'hdfs://hacluster/chetan/streamSample.csv' INTO TABLE
stream_table OPTIONS('HEADER'='false');
// spark-shell
cd /srv/spark2.2Bigdata/install/spark/sparkJdbc
bin/spark-shell --master yarn-client
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").
config("spark.sql.warehouse.dir",
"hdfs://hacluster/user/sparkhive/warehouse").
config("javax.jdo.option.ConnectionURL",
"jdbc:mysql://10.18.98.34:3306/sparksql?characterEncoding=UTF-8").
config("javax.jdo.option.ConnectionDriverName", "com.mysql.jdbc.Driver").
config("javax.jdo.option.ConnectionPassword", "huawei").
config("javax.jdo.option.ConnectionUserName", "sparksql").
getOrCreateCarbonSession()
carbonSession.sparkContext.setLogLevel("ERROR")
carbonSession.sql("select * from stream_table").show
Issue : Select query from spark-shell does not execute successfully for
streaming table load.
When the executor and driver cores and memory is increased while launching the
spark shell the issue still occurs.
bin/spark-shell --master yarn-client --executor-memory 10G --executor-cores 5
--driver-memory 5G --num-executors 3
scala> carbonSession.sql("select * from stream_table").show
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in
stage 25.0 failed 4 times, most recent failure: Lost task 0.3 in stage 25.0
(TID 65, BLR1000014269, executor 8): java.lang.IllegalStateException: unread
block data
at
java.io.ObjectInputStream$BlockDataInputStream.setBlockDataMode(ObjectInputStream.java:2424)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1383)
at
java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
at
org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
at
org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:114)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:258)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at scala.Option.foreach(Option.scala:257)
at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1918)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1931)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:333)
at
org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
at
org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2371)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2765)
at
org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2370)
at
org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2377)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2113)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2112)
at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2795)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2112)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2327)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:248)
at org.apache.spark.sql.Dataset.show(Dataset.scala:636)
at org.apache.spark.sql.Dataset.show(Dataset.scala:595)
at org.apache.spark.sql.Dataset.show(Dataset.scala:604)
... 50 elided
Caused by: java.lang.IllegalStateException: unread block data
at
java.io.ObjectInputStream$BlockDataInputStream.setBlockDataMode(ObjectInputStream.java:2424)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1383)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
at
org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
at
org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:114)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:258)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Expected : Select query from spark-shell should execute successfully for
streaming table load.
> Carbon1.3.0-Streaming - Select query from spark-shell does not execute
> successfully for streaming table load
> ------------------------------------------------------------------------------------------------------------
>
> Key: CARBONDATA-1726
> URL: https://issues.apache.org/jira/browse/CARBONDATA-1726
> Project: CarbonData
> Issue Type: Bug
> Components: data-query
> Affects Versions: 1.3.0
> Environment: 3 node ant cluster SUSE 11 SP4
> Reporter: Chetan Bhat
> Priority: Blocker
> Labels: Functional
>
> Steps :
> // prepare csv file for batch loading
> cd /srv/spark2.2Bigdata/install/hadoop/datanode/bin
> // generate streamSample.csv
> 100000001,batch_1,city_1,0.1,school_1:school_11$20
> 100000002,batch_2,city_2,0.2,school_2:school_22$30
> 100000003,batch_3,city_3,0.3,school_3:school_33$40
> 100000004,batch_4,city_4,0.4,school_4:school_44$50
> 100000005,batch_5,city_5,0.5,school_5:school_55$60
> // put to hdfs /tmp/streamSample.csv
> ./hadoop fs -put streamSample.csv /tmp
> // spark-beeline
> cd /srv/spark2.2Bigdata/install/spark/sparkJdbc
> 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/sparkhive/warehouse"
> bin/beeline -u jdbc:hive2://10.18.98.34:23040
> CREATE TABLE stream_table(
> id INT,
> name STRING,
> city STRING,
> salary FLOAT
> )
> STORED BY 'carbondata'
> TBLPROPERTIES('streaming'='true', 'sort_columns'='name');
> LOAD DATA LOCAL INPATH 'hdfs://hacluster/chetan/streamSample.csv' INTO TABLE
> stream_table OPTIONS('HEADER'='false');
> // spark-shell
> cd /srv/spark2.2Bigdata/install/spark/sparkJdbc
> bin/spark-shell --master yarn-client
> 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").
> config("spark.sql.warehouse.dir",
> "hdfs://hacluster/user/sparkhive/warehouse").
> config("javax.jdo.option.ConnectionURL",
> "jdbc:mysql://10.18.98.34:3306/sparksql?characterEncoding=UTF-8").
> config("javax.jdo.option.ConnectionDriverName", "com.mysql.jdbc.Driver").
> config("javax.jdo.option.ConnectionPassword", "huawei").
> config("javax.jdo.option.ConnectionUserName", "sparksql").
> getOrCreateCarbonSession()
>
> carbonSession.sparkContext.setLogLevel("ERROR")
> carbonSession.sql("select * from stream_table").show
> Issue : Select query from spark-shell does not execute successfully for
> streaming table load.
> When the executor and driver cores and memory is increased while launching
> the spark shell the issue still occurs.
> bin/spark-shell --master yarn-client --executor-memory 10G --executor-cores 5
> --driver-memory 5G --num-executors 3
> scala> import org.apache.carbondata.core.constants.CarbonCommonConstants
> import org.apache.carbondata.core.constants.CarbonCommonConstants
> scala> import org.apache.carbondata.core.util.CarbonProperties
> import org.apache.carbondata.core.util.CarbonProperties
> scala> import org.apache.carbondata.core.util.path.{CarbonStorePath,
> CarbonTablePath}
> import org.apache.carbondata.core.util.path.{CarbonStorePath, CarbonTablePath}
> scala>
> scala>
> CarbonProperties.getInstance().addProperty(CarbonCommonConstants.CARBON_TIMESTAMP_FORMAT,
> "yyyy/MM/dd")
> res29: org.apache.carbondata.core.util.CarbonProperties =
> org.apache.carbondata.core.util.CarbonProperties@67b056e7
> scala>
> scala> import org.apache.spark.sql.CarbonSession._
> import org.apache.spark.sql.CarbonSession._
> scala>
> scala> val carbonSession = SparkSession.
> | builder().
> | appName("StreamExample").
> | config("spark.sql.warehouse.dir",
> "hdfs://hacluster/user/sparkhive/warehouse").
> | config("javax.jdo.option.ConnectionURL",
> "jdbc:mysql://10.18.98.34:3306/sparksql?characterEncoding=UTF-8").
> | config("javax.jdo.option.ConnectionDriverName",
> "com.mysql.jdbc.Driver").
> | config("javax.jdo.option.ConnectionPassword", "huawei").
> | config("javax.jdo.option.ConnectionUserName", "sparksql").
> | getOrCreateCarbonSession()
> carbonSession: org.apache.spark.sql.SparkSession =
> org.apache.spark.sql.CarbonSession@1d0590bc
> scala>
> | carbonSession.sparkContext.setLogLevel("ERROR")
> scala> carbonSession.sql("select * from stream_table").show
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in
> stage 25.0 failed 4 times, most recent failure: Lost task 0.3 in stage 25.0
> (TID 65, BLR1000014269, executor 8): java.lang.IllegalStateException: unread
> block data
> at
> java.io.ObjectInputStream$BlockDataInputStream.setBlockDataMode(ObjectInputStream.java:2424)
> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1383)
> at
> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
> at
> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
> at
> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
> at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
> at
> org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
> at
> org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:114)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:258)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
> at scala.Option.foreach(Option.scala:257)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1918)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1931)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:333)
> at
> org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
> at
> org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2371)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2765)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2370)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2377)
> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2113)
> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2112)
> at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2795)
> at org.apache.spark.sql.Dataset.head(Dataset.scala:2112)
> at org.apache.spark.sql.Dataset.take(Dataset.scala:2327)
> at org.apache.spark.sql.Dataset.showString(Dataset.scala:248)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:636)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:595)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:604)
> ... 50 elided
> Caused by: java.lang.IllegalStateException: unread block data
> at
> java.io.ObjectInputStream$BlockDataInputStream.setBlockDataMode(ObjectInputStream.java:2424)
> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1383)
> at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
> at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
> at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
> at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
> at
> org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
> at
> org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:114)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:258)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Expected : Select query from spark-shell should execute successfully for
> streaming table load.
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