I get an invalid syntax error when I do that.
On Fri, 2016-04-22 at 20:06 -0400, Yong Zhang wrote:
> use "dispute_df.join(comments_df, dispute_df.COMMENTID ===
> comments_df.COMMENTID).first()" instead.
>
> Yong
>
> Date: Fri, 22 Apr 2016 17:42:26 -0400
> From: webe...@aim.com
> To: user@spark.apache.org
> Subject: Java exception when showing join
>
> I am using pyspark with netezza. I am getting a java exception when
> trying to show the first row of a join. I can show the first row for
> of the two dataframes separately but not the result of a join. I get
> the same error for any action I take(first, collect, show). Am I
> doing something wrong?
>
> from pyspark.sql import SQLContext
> sqlContext = SQLContext(sc)
> dispute_df =
> sqlContext.read.format('com.ibm.spark.netezza').options(url='jdbc:net
> ezza://***:5480/db', user='***', password='***', dbtable='table1',
> driver='com.ibm.spark.netezza').load()
> dispute_df.printSchema()
> comments_df =
> sqlContext.read.format('com.ibm.spark.netezza').options(url='jdbc:net
> ezza://***:5480/db', user='***', password='***', dbtable='table2',
> driver='com.ibm.spark.netezza').load()
> comments_df.printSchema()
> dispute_df.join(comments_df, dispute_df.COMMENTID ==
> comments_df.COMMENTID).first()
>
>
> root
> |-- COMMENTID: string (nullable = true)
> |-- EXPORTDATETIME: timestamp (nullable = true)
> |-- ARTAGS: string (nullable = true)
> |-- POTAGS: string (nullable = true)
> |-- INVTAG: string (nullable = true)
> |-- ACTIONTAG: string (nullable = true)
> |-- DISPUTEFLAG: string (nullable = true)
> |-- ACTIONFLAG: string (nullable = true)
> |-- CUSTOMFLAG1: string (nullable = true)
> |-- CUSTOMFLAG2: string (nullable = true)
>
> root
> |-- COUNTRY: string (nullable = true)
> |-- CUSTOMER: string (nullable = true)
> |-- INVNUMBER: string (nullable = true)
> |-- INVSEQNUMBER: string (nullable = true)
> |-- LEDGERCODE: string (nullable = true)
> |-- COMMENTTEXT: string (nullable = true)
> |-- COMMENTTIMESTAMP: timestamp (nullable = true)
> |-- COMMENTLENGTH: long (nullable = true)
> |-- FREEINDEX: long (nullable = true)
> |-- COMPLETEDFLAG: long (nullable = true)
> |-- ACTIONFLAG: long (nullable = true)
> |-- FREETEXT: string (nullable = true)
> |-- USERNAME: string (nullable = true)
> |-- ACTION: string (nullable = true)
> |-- COMMENTID: string (nullable = true)
>
> -------------------------------------------------------------------
> --------
> Py4JJavaError Traceback (most recent call
> last)
> <ipython-input-19-0cb9eb943052> in <module>()
> 5 comments_df =
> sqlContext.read.format('com.ibm.spark.netezza').options(url='jdbc:net
> ezza://dstbld-pda02.bld.dst.ibm.com:5480/BACC_DEV_CSP_NBAAR',
> user='rnahar', password='Sfeb2016',
> dbtable='UK_METRICS.EU_COMMENTS2',
> driver='com.ibm.spark.netezza').load()
> 6 comments_df.printSchema()
> ----> 7 dispute_df.join(comments_df, dispute_df.COMMENTID ==
> comments_df.COMMENTID).first()
>
> /usr/local/src/spark/spark-1.6.1-bin-
> hadoop2.6/python/pyspark/sql/dataframe.pyc in first(self)
> 802 Row(age=2, name=u'Alice')
> 803 """
> --> 804 return self.head()
> 805
> 806 @ignore_unicode_prefix
>
> /usr/local/src/spark/spark-1.6.1-bin-
> hadoop2.6/python/pyspark/sql/dataframe.pyc in head(self, n)
> 790 """
> 791 if n is None:
> --> 792 rs = self.head(1)
> 793 return rs[0] if rs else None
> 794 return self.take(n)
>
> /usr/local/src/spark/spark-1.6.1-bin-
> hadoop2.6/python/pyspark/sql/dataframe.pyc in head(self, n)
> 792 rs = self.head(1)
> 793 return rs[0] if rs else None
> --> 794 return self.take(n)
> 795
> 796 @ignore_unicode_prefix
>
> /usr/local/src/spark/spark-1.6.1-bin-
> hadoop2.6/python/pyspark/sql/dataframe.pyc in take(self, num)
> 304 with SCCallSiteSync(self._sc) as css:
> 305 port =
> self._sc._jvm.org.apache.spark.sql.execution.EvaluatePython.takeAndSe
> rve(
> --> 306 self._jdf, num)
> 307 return list(_load_from_socket(port,
> BatchedSerializer(PickleSerializer())))
> 308
>
> /usr/local/src/spark/spark-1.6.1-bin-hadoop2.6/python/lib/py4j-0.9-
> src.zip/py4j/java_gateway.py in __call__(self, *args)
> 811 answer = self.gateway_client.send_command(command)
> 812 return_value = get_return_value(
> --> 813 answer, self.gateway_client, self.target_id,
> self.name)
> 814
> 815 for temp_arg in temp_args:
>
> /usr/local/src/spark/spark-1.6.1-bin-
> hadoop2.6/python/pyspark/sql/utils.pyc in deco(*a, **kw)
> 43 def deco(*a, **kw):
> 44 try:
> ---> 45 return f(*a, **kw)
> 46 except py4j.protocol.Py4JJavaError as e:
> 47 s = e.java_exception.toString()
>
> /usr/local/src/spark/spark-1.6.1-bin-hadoop2.6/python/lib/py4j-0.9-
> src.zip/py4j/protocol.py in get_return_value(answer, gateway_client,
> target_id, name)
> 306 raise Py4JJavaError(
> 307 "An error occurred while calling
> {0}{1}{2}.\n".
> --> 308 format(target_id, ".", name), value)
> 309 else:
> 310 raise Py4JError(
>
> Py4JJavaError: An error occurred while calling
> z:org.apache.spark.sql.execution.EvaluatePython.takeAndServe.
> : org.apache.spark.SparkException: Job aborted due to stage failure:
> Task 2 in stage 59.0 failed 1 times, most recent failure: Lost task
> 2.0 in stage 59.0 (TID 1406, localhost): java.io.IOException: EOF
> whilst processing escape sequence
> at org.apache.commons.csv.Lexer.readEscape(Lexer.java:346)
> at org.apache.commons.csv.Lexer.parseSimpleToken(Lexer.java:200)
> at org.apache.commons.csv.Lexer.nextToken(Lexer.java:161)
> at
> org.apache.commons.csv.CSVParser.nextRecord(CSVParser.java:498)
> at
> org.apache.commons.csv.CSVParser.getRecords(CSVParser.java:365)
> at
> com.ibm.spark.netezza.NetezzaRecordParser.parse(NetezzaRecordParser.s
> cala:43)
> at
> com.ibm.spark.netezza.NetezzaDataReader.next(NetezzaDataReader.scala:
> 136)
> at
> com.ibm.spark.netezza.NetezzaRDD$$anon$1.getNext(NetezzaRDD.scala:77)
> at
> com.ibm.spark.netezza.NetezzaRDD$$anon$1.hasNext(NetezzaRDD.scala:106
> )
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at
> org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(Bypa
> ssMergeSortShuffleWriter.java:126)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scal
> a:73)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scal
> a:41)
> at org.apache.spark.scheduler.Task.run(Task.scala:89)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.
> java:1143)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor
> .java:618)
> at java.lang.Thread.run(Thread.java:785)
>
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DA
> GScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(D
> AGScheduler.scala:1419)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(D
> AGScheduler.scala:1418)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.
> scala:59)
> at
> scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala
> :1418)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$
> 1.apply(DAGScheduler.scala:799)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$
> 1.apply(DAGScheduler.scala:799)
> at scala.Option.foreach(Option.scala:236)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGSchedu
> ler.scala:799)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(D
> AGScheduler.scala:1640)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAG
> Scheduler.scala:1599)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAG
> Scheduler.scala:1588)
> at
> org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> at java.lang.Thread.getStackTrace(Thread.java:1117)
> at
> org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620
> )
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
> at
> org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:
> 212)
> at
> org.apache.spark.sql.execution.EvaluatePython$$anonfun$takeAndServe$1
> .apply$mcI$sp(python.scala:126)
> at
> org.apache.spark.sql.execution.EvaluatePython$$anonfun$takeAndServe$1
> .apply(python.scala:124)
> at
> org.apache.spark.sql.execution.EvaluatePython$$anonfun$takeAndServe$1
> .apply(python.scala:124)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLEx
> ecution.scala:56)
> at
> org.apache.spark.sql.DataFrame.withNewExecutionId(DataFrame.scala:208
> 6)
> at
> org.apache.spark.sql.execution.EvaluatePython$.takeAndServe(python.sc
> ala:124)
> at
> org.apache.spark.sql.execution.EvaluatePython.takeAndServe(python.sca
> la)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.
> java:95)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAcces
> sorImpl.java:55)
> at java.lang.reflect.Method.invoke(Method.java:507)
> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
> at
> py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
> at py4j.Gateway.invoke(Gateway.java:259)
> at
> py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
> at py4j.commands.CallCommand.execute(CallCommand.java:79)
> at py4j.GatewayConnection.run(GatewayConnection.java:209)
> at java.lang.Thread.run(Thread.java:785)
> Caused by: java.io.IOException: EOF whilst processing escape sequence
> at org.apache.commons.csv.Lexer.readEscape(Lexer.java:346)
> at org.apache.commons.csv.Lexer.parseSimpleToken(Lexer.java:200)
> at org.apache.commons.csv.Lexer.nextToken(Lexer.java:161)
> at
> org.apache.commons.csv.CSVParser.nextRecord(CSVParser.java:498)
> at
> org.apache.commons.csv.CSVParser.getRecords(CSVParser.java:365)
> at
> com.ibm.spark.netezza.NetezzaRecordParser.parse(NetezzaRecordParser.s
> cala:43)
> at
> com.ibm.spark.netezza.NetezzaDataReader.next(NetezzaDataReader.scala:
> 136)
> at
> com.ibm.spark.netezza.NetezzaRDD$$anon$1.getNext(NetezzaRDD.scala:77)
> at
> com.ibm.spark.netezza.NetezzaRDD$$anon$1.hasNext(NetezzaRDD.scala:106
> )
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at
> org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(Bypa
> ssMergeSortShuffleWriter.java:126)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scal
> a:73)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scal
> a:41)
> at org.apache.spark.scheduler.Task.run(Task.scala:89)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.
> java:1143)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor
> .java:618)
> ... 1 more
>
>
> In [ ]:
>
>
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