Error log from Zeppelin
INFO [2015-09-07 22:47:38,764] ({pool-2-thread-4}
Logging.scala[logInfo]:59) - Registered BlockManager
WARN [2015-09-07 22:47:38,768] ({pool-2-thread-4}
Logging.scala[logWarning]:92) - Multiple running SparkContexts detected in
the same JVM!
org.apache.spark.SparkException: Only one SparkContext may be running in
this JVM (see SPARK-2243). To ignore this error, set
spark.driver.allowMultipleContexts = true. The currently running
SparkContext was created at:
org.apache.spark.SparkContext.<init>(SparkContext.scala:81)
org.apache.zeppelin.spark.SparkInterpreter.createSparkContext(SparkInterpreter.java:301)
org.apache.zeppelin.spark.SparkInterpreter.getSparkContext(SparkInterpreter.java:146)
org.apache.zeppelin.spark.SparkInterpreter.open(SparkInterpreter.java:423)
org.apache.zeppelin.interpreter.ClassloaderInterpreter.open(ClassloaderInterpreter.java:73)
org.apache.zeppelin.interpreter.LazyOpenInterpreter.open(LazyOpenInterpreter.java:68)
org.apache.zeppelin.interpreter.LazyOpenInterpreter.interpret(LazyOpenInterpreter.java:92)
org.apache.zeppelin.interpreter.remote.RemoteInterpreterServer$InterpretJob.jobRun(RemoteInterpreterServer.java:277)
org.apache.zeppelin.scheduler.Job.run(Job.java:170)
org.apache.zeppelin.scheduler.FIFOScheduler$1.run(FIFOScheduler.java:118)
java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
java.util.concurrent.FutureTask.run(FutureTask.java:266)
java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:180)
java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
java.lang.Thread.run(Thread.java:745)
at
org.apache.spark.SparkContext$$anonfun$assertNoOtherContextIsRunning$1.apply(SparkContext.scala:2083)
at
org.apache.spark.SparkContext$$anonfun$assertNoOtherContextIsRunning$1.apply(SparkContext.scala:2065)
at scala.Option.foreach(Option.scala:236)
at
org.apache.spark.SparkContext$.assertNoOtherContextIsRunning(SparkContext.scala:2065)
at org.apache.spark.SparkContext$.setActiveContext(SparkContext.scala:2151)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:2023)
at
org.apache.spark.streaming.StreamingContext$.createNewSparkContext(StreamingContext.scala:834)
at
org.apache.spark.streaming.StreamingContext.<init>(StreamingContext.scala:80)
at
$line32.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:34)
at
$line32.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:39)
at
$line32.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:41)
at
$line32.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:43)
at
$line32.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:45)
at $line32.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:47)
at $line32.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:49)
at $line32.$read$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:51)
at $line32.$read$$iwC$$iwC$$iwC$$iwC.<init>(<console>:53)
at $line32.$read$$iwC$$iwC$$iwC.<init>(<console>:55)
at $line32.$read$$iwC$$iwC.<init>(<console>:57)
at $line32.$read$$iwC.<init>(<console>:59)
at $line32.$read.<init>(<console>:61)
at $line32.$read$.<init>(<console>:65)
at $line32.$read$.<clinit>(<console>)
at $line32.$eval$.<init>(<console>:7)
at $line32.$eval$.<clinit>(<console>)
at $line32.$eval.$print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:483)
at
org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
at
org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1338)
at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
at
org.apache.zeppelin.spark.SparkInterpreter.interpretInput(SparkInterpreter.java:600)
at
org.apache.zeppelin.spark.SparkInterpreter.interpret(SparkInterpreter.java:576)
at
org.apache.zeppelin.spark.SparkInterpreter.interpret(SparkInterpreter.java:569)
at
org.apache.zeppelin.interpreter.ClassloaderInterpreter.interpret(ClassloaderInterpreter.java:57)
at
org.apache.zeppelin.interpreter.LazyOpenInterpreter.interpret(LazyOpenInterpreter.java:93)
at
org.apache.zeppelin.interpreter.remote.RemoteInterpreterServer$InterpretJob.jobRun(RemoteInterpreterServer.java:277)
at org.apache.zeppelin.scheduler.Job.run(Job.java:170)
at org.apache.zeppelin.scheduler.FIFOScheduler$1.run(FIFOScheduler.java:118)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at
java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:180)
at
java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
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)
==> ../logs/zeppelin-anauser-eachsaj.eei.ericsson.se.log <==
On 7 September 2015 at 22:49, Sajeevan Achuthan <[email protected]
> wrote:
> Hi Moon,
> Thanks for the reply, I tried that option too. Unfortunately, I tried
> that option too and I got the error
> data: org.apache.spark.streaming.dstream.DStream[CELL_KPIS] =
> org.apache.spark.streaming.dstream.MappedDStream@5f3ea8bb <console>:49:
> error: value toDF is not a member of org.apache.spark.rdd.RDD[CELL_KPIS]
> accessLogs.toDF.registerTempTable("RAS") ^
> Any idea?
>
> On 7 September 2015 at 17:30, moon soo Lee <[email protected]> wrote:
>
>> Hi,
>>
>> I think you will need to convert RDD to data frame using .toDF(), like
>> accessLogs.toDF.registerTempTable("RAS")
>>
>> Thanks,
>> moon
>>
>> On Mon, Sep 7, 2015 at 3:34 AM Sajeevan Achuthan <
>> [email protected]> wrote:
>>
>>> Zeppelin, an excellent tool. I am trying to implement a streaming
>>> application. I get an error while deploying my application. See my code
>>> below
>>>
>>>
>>> import org.apache.spark.SparkContext
>>> import org.apache.spark.SparkContext._
>>> import org.apache.spark.SparkConf
>>> import org.apache.spark.streaming.StreamingContext
>>> import org.apache.spark.streaming.Seconds
>>> import org.apache.spark.sql.SQLContext
>>> val sparkConf = new
>>> SparkConf().setAppName("PEPA").setMaster("local[*]").set("spark.driver.allowMultipleContexts",
>>> "true")
>>>
>>> import org.apache.spark.streaming.kafka._
>>> val ssc = new StreamingContext(sparkConf, Seconds(2))
>>>
>>> ssc.checkpoint("checkpoint")
>>> val topicMap = Map("incoming"->1)
>>>
>>> val record = KafkaUtils.createStream(ssc, "localhost", "1",
>>> topicMap).map(_._2)
>>> record.print()
>>> case class
>>> CELL_KPIS(ECELL_Name:String,CGI:String,Number_of_Times_Interf:Double,TAOF:Double,PHL:Double,NPCCHL:Double,LRSRP:Double,NC:Double)
>>> val data =
>>> record.map(s=>s.split(",")).filter(s=>s(0)!="\"ECELL_Name\"").map(
>>> s=>CELL_KPIS(s(0), s(1), s(2).toDouble, s(3).toDouble,
>>> s(5).toDouble,s(6).toDouble, s(7).toDouble, s(8).toDouble)
>>> )
>>> data.foreachRDD {accessLogs =>
>>> import sqlContext.implicits._
>>> accessLogs.registerTempTable("RAS")
>>>
>>> }
>>> ssc.start()
>>> ssc.awaitTermination()
>>>
>>> And I get error
>>> import org.apache.spark.SparkContext import
>>> org.apache.spark.SparkContext._ import org.apache.spark.SparkConf import
>>> org.apache.spark.streaming.StreamingContext import
>>> org.apache.spark.streaming.Seconds import org.apache.spark.sql.SQLContext
>>> sparkConf: org.apache.spark.SparkConf = org.apache.spark.SparkConf@2e5779a
>>> import org.apache.spark.streaming.kafka._ ssc:
>>> org.apache.spark.streaming.StreamingContext =
>>> org.apache.spark.streaming.StreamingContext@48621ee1 topicMap:
>>> scala.collection.immutable.Map[String,Int] = Map(incoming -> 1) record:
>>> org.apache.spark.streaming.dstream.DStream[String] =
>>> org.apache.spark.streaming.dstream.MappedDStream@6290e75e defined class
>>> CELL_KPIS data: org.apache.spark.streaming.dstream.DStream[CELL_KPIS] =
>>> org.apache.spark.streaming.dstream.MappedDStream@4bda38c3
>>>
>>> <console>:55: error: value registerTempTable is not a member of
>>> org.apache.spark.rdd.RDD[CELL_KPIS] accessLogs.registerTempTable("RAS")
>>>
>>> *My configuration for Zeppelin*
>>>
>>>
>>> export MASTER=spark://localhost:7077
>>> export JAVA_HOME=/usr/lib/jvm/jdk1.8.0_05
>>> export ZEPPELIN_PORT=9090
>>> export ZEPPELIN_SPARK_CONCURRENTSQL=false
>>> export ZEPPELIN_SPARK_USEHIVECONTEXT=false
>>> #'export MASTER=local[*]
>>> export SPARK_HOME=/home/anauser/spark-1.3/spark-1.3.0-bin-cdh4
>>>
>>> *Interpreter configuration for spark *
>>>
>>> "2AW247KM7": { "id": "2AW247KM7", "name": "spark", "group": "spark",
>>> "properties": { "spark.cores.max": "", "spark.yarn.jar": "", "master":
>>> "local[*]", "zeppelin.spark.maxResult": "1000", "zeppelin.dep.localrepo":
>>> "local-repo", "spark.app.name": "APP3", "spark.executor.memory": "5G",
>>> "zeppelin.spark.useHiveContext": "false",
>>> "spark.driver.allowMultipleContexts": "true", "args": "", "spark.home":
>>> "/home/anauser/spark-1.3/spark-1.3.0-bin-cdh4",
>>> "zeppelin.spark.concurrentSQL": "true", "zeppelin.pyspark.python": "python"
>>> }, "interpreterGroup": [ { "class":
>>> "org.apache.zeppelin.spark.SparkInterpreter", "name": "spark" }, { "class":
>>> "org.apache.zeppelin.spark.PySparkInterpreter", "name": "pyspark" }, {
>>> "class": "org.apache.zeppelin.spark.SparkSqlInterpreter", "name": "sql" },
>>> { "class": "org.apache.zeppelin.spark.DepInterpreter", "name": "dep" } ],
>>> "option": { "remote": true } }
>>> Is there any problem in my code or setup ?
>>> Any help very much appreciated.
>>>
>>
>
