BTW, this sounds very similar to https://issues.apache.org/jira/browse/ZEPPELIN-297, which affects %pyspark and was fixed in Zeppelin 0.5.5.
On Tue, Feb 2, 2016 at 12:32 PM Jonathan Kelly <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> 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) >> >> >> >> 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 >> >
