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From "Chetan Bhat (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (CARBONDATA-1813) Nullpointereception in spark shell when the streaming started with table streaming altered from default(false) to true
Date Wed, 29 Nov 2017 05:47:00 GMT

     [ https://issues.apache.org/jira/browse/CARBONDATA-1813?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Chetan Bhat updated CARBONDATA-1813:
------------------------------------
    Summary: Nullpointereception in spark shell when the streaming started with table streaming
altered from default(false) to true  (was: (Carbon1.3.0 - Streaming) Nullpointereception in
spark shell when the streaming started with table streaming altered from default(false) to
true)

> Nullpointereception in spark shell when the streaming started with table streaming altered
from default(false) to true
> ----------------------------------------------------------------------------------------------------------------------
>
>                 Key: CARBONDATA-1813
>                 URL: https://issues.apache.org/jira/browse/CARBONDATA-1813
>             Project: CarbonData
>          Issue Type: Bug
>          Components: other
>    Affects Versions: 1.3.0
>         Environment: 3 node ant cluster
>            Reporter: Chetan Bhat
>              Labels: Functional
>
> Steps :
> Spark submit thrift server is started.
> User starts 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 tries to start streaming with table streaming property altered from
default(false) to true.
> scala> import java.io.{File, PrintWriter}
> import java.io.{File, PrintWriter}
> scala> import java.net.ServerSocket
> import java.net.ServerSocket
> scala>
> scala> import org.apache.spark.sql.{CarbonEnv, SparkSession}
> import org.apache.spark.sql.{CarbonEnv, SparkSession}
> scala> import org.apache.spark.sql.hive.CarbonRelation
> import org.apache.spark.sql.hive.CarbonRelation
> scala> import org.apache.spark.sql.streaming.{ProcessingTime, StreamingQuery}
> import org.apache.spark.sql.streaming.{ProcessingTime, StreamingQuery}
> scala>
> 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")
> res0: org.apache.carbondata.core.util.CarbonProperties = org.apache.carbondata.core.util.CarbonProperties@69ee0861
> scala>
> scala> import org.apache.spark.sql.CarbonSession._
> import org.apache.spark.sql.CarbonSession._
> scala>
> scala> val carbonSession = SparkSession.
>      |   builder().
>      |   appName("StreamExample").
>      |   getOrCreateCarbonSession("hdfs://hacluster/user/hive/warehouse/carbon.store")
> carbonSession: org.apache.spark.sql.SparkSession = org.apache.spark.sql.CarbonSession@6ce365b7
> scala>
>      | carbonSession.sparkContext.setLogLevel("INFO")
> scala>
> scala> def sql(sql: String) = carbonSession.sql(sql)
> sql: (sql: String)org.apache.spark.sql.DataFrame
> scala>
> scala> 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
>      | }
> writeSocket: (serverSocket: java.net.ServerSocket)Thread
> scala>
>      | 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
>      | }
> startStreaming: (spark: org.apache.spark.sql.SparkSession, tablePath: org.apache.carbondata.core.util.path.CarbonTablePath,
tableName: String, port: Int)Thread
> scala>
> scala> val streamTableName = "all_datatypes_2048"
> streamTableName: String = all_datatypes_2048
> scala>
> scala>
> scala> sql(s"create table all_datatypes_2048 (imei string,deviceInformationId int,MAC
string,deviceColor string,device_backColor string,modelId string,marketName string,AMSize
string,ROMSize string,CUPAudit string,CPIClocked string,series string,productionDate timestamp,bomCode
string,internalModels string, deliveryTime string, channelsId string, channelsName string
, deliveryAreaId string, deliveryCountry string, deliveryProvince string, deliveryCity string,deliveryDistrict
string, deliveryStreet string, oxSingleNumber string, ActiveCheckTime string, ActiveAreaId
string, ActiveCountry string, ActiveProvince string, Activecity string, ActiveDistrict string,
ActiveStreet string, ActiveOperatorId string, Active_releaseId string, Active_EMUIVersion
string, Active_operaSysVersion string, Active_BacVerNumber string, Active_BacFlashVer string,
Active_webUIVersion string, Active_webUITypeCarrVer string,Active_webTypeDataVerNumber string,
Active_operatorsVersion string, Active_phonePADPartitionedVersions string, Latest_YEAR int,
Latest_MONTH int, Latest_DAY Decimal(30,10), Latest_HOUR string, Latest_areaId string, Latest_country
string, Latest_province string, Latest_city string, Latest_district string, Latest_street
string, Latest_releaseId string, Latest_EMUIVersion string, Latest_operaSysVersion string,
Latest_BacVerNumber string, Latest_BacFlashVer string, Latest_webUIVersion string, Latest_webUITypeCarrVer
string, Latest_webTypeDataVerNumber string, Latest_operatorsVersion string, Latest_phonePADPartitionedVersions
string, Latest_operatorId string, gamePointDescription string,gamePointId double,contractNumber
BigInt) STORED BY 'org.apache.carbondata.format' TBLPROPERTIES('table_blocksize'='2048')")
> res4: org.apache.spark.sql.DataFrame = []
> scala>
> scala> sql(s"LOAD DATA INPATH 'hdfs://hacluster/chetan/100_olap_C20.csv' INTO table
all_datatypes_2048 options ('DELIMITER'=',', 'BAD_RECORDS_ACTION'='FORCE','FILEHEADER'='imei,deviceInformationId,MAC,deviceColor,device_backColor,modelId,marketName,AMSize,ROMSize,CUPAudit,CPIClocked,series,productionDate,bomCode,internalModels,deliveryTime,channelsId,channelsName,deliveryAreaId,deliveryCountry,deliveryProvince,deliveryCity,deliveryDistrict,deliveryStreet,oxSingleNumber,contractNumber,ActiveCheckTime,ActiveAreaId,ActiveCountry,ActiveProvince,Activecity,ActiveDistrict,ActiveStreet,ActiveOperatorId,Active_releaseId,Active_EMUIVersion,Active_operaSysVersion,Active_BacVerNumber,Active_BacFlashVer,Active_webUIVersion,Active_webUITypeCarrVer,Active_webTypeDataVerNumber,Active_operatorsVersion,Active_phonePADPartitionedVersions,Latest_YEAR,Latest_MONTH,Latest_DAY,Latest_HOUR,Latest_areaId,Latest_country,Latest_province,Latest_city,Latest_district,Latest_street,Latest_releaseId,Latest_EMUIVersion,Latest_operaSysVersion,Latest_BacVerNumber,Latest_BacFlashVer,Latest_webUIVersion,Latest_webUITypeCarrVer,Latest_webTypeDataVerNumber,Latest_operatorsVersion,Latest_phonePADPartitionedVersions,Latest_operatorId,gamePointId,gamePointDescription')")
> res5: org.apache.spark.sql.DataFrame = []
> scala>
> scala> sql(s"ALTER TABLE all_datatypes_2048 SET TBLPROPERTIES('streaming'='true')")
> res6: org.apache.spark.sql.DataFrame = []
> scala>
> scala>
> scala>
> scala> val carbonTable = CarbonEnv.getInstance(carbonSession).carbonMetastore.
>      |   lookupRelation(Some("default"), streamTableName)(carbonSession).asInstanceOf[CarbonRelation].carbonTable
> carbonTable: org.apache.carbondata.core.metadata.schema.table.CarbonTable = org.apache.carbondata.core.metadata.schema.table.CarbonTable@77648a90
> scala>
> scala> val tablePath = CarbonStorePath.getCarbonTablePath(carbonTable.getAbsoluteTableIdentifier)
> tablePath: org.apache.carbondata.core.util.path.CarbonTablePath = hdfs://hacluster/user/hive/warehouse/carbon.store/default/all_datatypes_2048
> scala>
> scala> val port = 8010
> port: Int = 8010
> scala> val serverSocket = new ServerSocket(port)
> serverSocket: java.net.ServerSocket = ServerSocket[addr=0.0.0.0/0.0.0.0,localport=8010]
> scala> val socketThread = writeSocket(serverSocket)
> socketThread: Thread = Thread[Thread-81,5,main]
> scala> val streamingThread = startStreaming(carbonSession, tablePath, streamTableName,
port)
> Issue : Nullpointereception in spark shell when the streaming started with table streaming
altered from default(false) to true. Streaming fails.
> scala> org.apache.carbondata.streaming.CarbonStreamException: Table default.all_datatypes_2048
is not a streaming table
>         at org.apache.spark.sql.CarbonSource.createSink(CarbonSource.scala:242)
>         at org.apache.spark.sql.execution.datasources.DataSource.createSink(DataSource.scala:274)
>         at org.apache.spark.sql.streaming.DataStreamWriter.start(DataStreamWriter.scala:266)
>         at $line28.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$anon$1.run(<console>:51)
> Done reading and writing streaming data
> Exception in thread "Thread-82" java.lang.NullPointerException
>         at $line28.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$anon$1.run(<console>:59)
> Expected : Streaming should be continued successfully without any failure or exception
after table streaming property altered from default(false) to true.



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