I’ve created an issue in jira https://issues.apache.org/jira/browse/ZEPPELIN-648
From: Benjamin Kim [mailto:bbuil...@gmail.com] Sent: Tuesday, February 02, 2016 3:34 PM To: us...@zeppelin.incubator.apache.org Cc: dev@zeppelin.incubator.apache.org Subject: Re: csv dependencies loaded in %spark but not %sql in spark 1.6/zeppelin 0.5.6 Same here. I want to know the answer too. On Feb 2, 2016, at 12:32 PM, Jonathan Kelly <jonathaka...@gmail.com<mailto:jonathaka...@gmail.com>> wrote: Hey, I just ran into that same exact issue yesterday and wasn't sure if I was doing something wrong or what. Glad to know it's not just me! Unfortunately I have not yet had the time to look any deeper into it. Would you mind filing a JIRA if there isn't already one? On Tue, Feb 2, 2016 at 12:29 PM Lin, Yunfeng <yunfeng....@citi.com<mailto:yunfeng....@citi.com>> wrote: Hi guys, I load spark-csv dependencies in %spark, but not in %sql using apache zeppelin 0.5.6 with spark 1.6.0. Everything is working fine in zeppelin 0.5.5 with spark 1.5 through Do you have similar problems? I am loading spark csv dependencies (https://github.com/databricks/spark-csv<https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_databricks_spark-2Dcsv&d=BQMFaQ&c=j-EkbjBYwkAB4f8ZbVn1Fw&r=b2BXWa66OlJ_NWqk5P310M6mGfus8eDC5O4J0-nePFY&m=dSXRZCZNlnU1tx9rtyX9UWfdjT0EPbafKr2NyIrXP-o&s=zUPPWKYhZiNUuIUWmlXXGF_94ImGHQ4qHpFCU0xSEzg&e=>) Using: %dep z.load(“PATH/commons-csv-1.1.jar”) z.load(“PATH/spark-csv_2.10-1.3.0.jar”) z.load(“PATH/univocity-parsers-1.5.1.jar:) z.load(“PATH/scala-library-2.10.5.jar”) I am able to load a csv from hdfs using data frame API in spark. It is running perfect fine. %spark val df = sqlContext.read .format("com.databricks.spark.csv") .option("header", "false") // Use finrst line of all files as header .option("inferSchema", "true") // Automatically infer data types .load("hdfs://sd-6f48-7fe6:8020/tmp/people.txt") // this is a file in HDFS df.registerTempTable("people") df.show() This also work: %spark val df2=sqlContext.sql(“select * from people”) df2.show() But this doesn’t work…. %sql select * from people java.lang.ClassNotFoundException: com.databricks.spark.csv.CsvRelation$$anonfun$1$$anonfun$2 at java.net.URLClassLoader$1.run(URLClassLoader.java:366) at java.net.URLClassLoader$1.run(URLClassLoader.java:355) at java.security.AccessController.doPrivileged(Native Method) at java.net.URLClassLoader.findClass(URLClassLoader.java:354) at java.lang.ClassLoader.loadClass(ClassLoader.java:425) at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:308) at java.lang.ClassLoader.loadClass(ClassLoader.java:358) at java.lang.Class.forName0(Native Method) at java.lang.Class.forName(Class.java:270) at org.apache.spark.util.InnerClosureFinder$$anon$4.visitMethodInsn(ClosureCleaner.scala:435) at org.apache.xbean.asm5.ClassReader.a(Unknown Source) at org.apache.xbean.asm5.ClassReader.b(Unknown Source) at org.apache.xbean.asm5.ClassReader.accept(Unknown Source) at org.apache.xbean.asm5.ClassReader.accept(Unknown Source) at org.apache.spark.util.ClosureCleaner$.getInnerClosureClasses(ClosureCleaner.scala:84) at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:187) at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:122) at org.apache.spark.SparkContext.clean(SparkContext.scala:2055) at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1.apply(RDD.scala:707) at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1.apply(RDD.scala:706) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111) at org.apache.spark.rdd.RDD.withScope(RDD.scala:316) at org.apache.spark.rdd.RDD.mapPartitions(RDD.scala:706) at com.databricks.spark.csv.CsvRelation.tokenRdd(CsvRelation.scala:90) at com.databricks.spark.csv.CsvRelation.buildScan(CsvRelation.scala:104) at com.databricks.spark.csv.CsvRelation.buildScan(CsvRelation.scala:152) at org.apache.spark.sql.execution.datasources.DataSourceStrategy$$anonfun$4.apply(DataSourceStrategy.scala:64) at org.apache.spark.sql.execution.datasources.DataSourceStrategy$$anonfun$4.apply(DataSourceStrategy.scala:64) at org.apache.spark.sql.execution.datasources.DataSourceStrategy$$anonfun$pruneFilterProject$1.apply(DataSourceStrategy.scala:274) at org.apache.spark.sql.execution.datasources.DataSourceStrategy$$anonfun$pruneFilterProject$1.apply(DataSourceStrategy.scala:273) at org.apache.spark.sql.execution.datasources.DataSourceStrategy$.pruneFilterProjectRaw(DataSourceStrategy.scala:352) at org.apache.spark.sql.execution.datasources.DataSourceStrategy$.pruneFilterProject(DataSourceStrategy.scala:269) at org.apache.spark.sql.execution.datasources.DataSourceStrategy$.apply(DataSourceStrategy.scala:60) at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58) at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58) at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) at org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59) at org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54) at org.apache.spark.sql.execution.SparkStrategies$BasicOperators$.apply(SparkStrategies.scala:349) at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58) at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58) at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) at org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59) at org.apache.spark.sql.execution.QueryExecution.sparkPlan$lzycompute(QueryExecution.scala:47) at org.apache.spark.sql.execution.QueryExecution.sparkPlan(QueryExecution.scala:45) at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:52) at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:52) at org.apache.spark.sql.DataFrame.withCallback(DataFrame.scala:2134) at org.apache.spark.sql.DataFrame.head(DataFrame.scala:1413) at org.apache.spark.sql.DataFrame.take(DataFrame.scala:1495) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:606) at org.apache.zeppelin.spark.ZeppelinContext.showDF(ZeppelinContext.java:297) at org.apache.zeppelin.spark.SparkSqlInterpreter.interpret(SparkSqlInterpreter.java:144) at org.apache.zeppelin.interpreter.ClassloaderInterpreter.interpret(ClassloaderInterpreter.java:57) at org.apache.zeppelin.interpreter.LazyOpenInterpreter.interpret(LazyOpenInterpreter.java:93) at org.apache.zeppelin.interpreter.remote.RemoteInterpreterServer$InterpretJob.jobRun(RemoteInterpreterServer.java:300) at org.apache.zeppelin.scheduler.Job.run(Job.java:169) at org.apache.zeppelin.scheduler.FIFOScheduler$1.run(FIFOScheduler.java:134) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471) at java.util.concurrent.FutureTask.run(FutureTask.java:262) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:178) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:292) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) at java.lang.Thread.run(Thread.java:745) I notice that in the source code of spark interpreter (class: org.apache.zeppelin.spark.ZeppelinContext. There are something different between spark 1.5 and spark 1.6. Spark 1.5 is using SQLContext while Spark 1.6 is HiveContext. Unfortunately, no matter true or false are set in zeppelin.spark.useHiveContext, %sql just can’t find csv dependencies … try { // Use reflection because of classname returned by queryExecution changes from // Spark <1.5.2 org.apache.spark.sql.SQLContext$QueryExecution // Spark 1.6.0> org.apache.spark.sql.hive.HiveContext$QueryExecution Object qe = df.getClass().getMethod("queryExecution").invoke(df); Object a = qe.getClass().getMethod("analyzed").invoke(qe); scala.collection.Seq seq = (scala.collection.Seq) a.getClass().getMethod("output").invoke(a); columns = (List<Attribute>) scala.collection.JavaConverters.seqAsJavaListConverter(seq) .asJava(); } catch (NoSuchMethodException | SecurityException | IllegalAccessException | IllegalArgumentException | InvocationTargetException e) { throw new InterpreterException(e); } Yunfeng