sorry I didn't pay attention you are using pyspark, so ignore my reply, as I only use Scala version. Yong
From: java8...@hotmail.com To: webe...@aim.com; user@spark.apache.org Subject: RE: Java exception when showing join Date: Mon, 25 Apr 2016 09:41:18 -0400 dispute_df.join(comments_df, $"dispute_df.COMMENTID" === $"comments_df.COMMENTID").first() If you are using DataFrame API, and some of them are trick for first time user, my suggestion is to always referring the unit tests. That is in fact the way I tried to find out how to do it for lots of cases. https://github.com/apache/spark/blob/master/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala Yong > Subject: Re: Java exception when showing join > From: webe...@aim.com > To: java8...@hotmail.com; user@spark.apache.org > Date: Mon, 25 Apr 2016 07:45:12 -0500 > > 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 [ ]: > > > > >
