[ZEPPELIN-648] jar dependencies loaded in %spark but not %sql in spark 1.6/zeppelin 0.5.6

• Type: Bug
• Status: Closed
• Priority: Major
• Resolution: Duplicate
• Affects Version/s: 0.5.6
• Fix Version/s: 0.6.0

Environment

RHEL, java 1.7

• Assignee: Unassigned
• Reporter: Yunfeng Lin
• Created: 02/Feb/16 20:48
• Updated: 03/Feb/16 04:01
• Resolved: 03/Feb/16 04:01

Description

Hi guys,

I can load spark-csv dependencies in %spark, but I cannot 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 previously.

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); }

Issue Links

• is duplicated by: ZEPPELIN-194 Exception on %sql over CSV dataframe
• is duplicated by: ZEPPELIN-381 sqlContext doesn't work with tables created by external jars (e.g. com.databricks.spark.csv); spark <1.5.1