[
https://issues.apache.org/jira/browse/SPARK-24475?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16504163#comment-16504163
]
Joseph Toth commented on SPARK-24475:
-------------------------------------
It looks like it was my version of java on this machine. It was 9 jre. I
upgraded to 10jdk, but received the error at the bottom. Then I downgraded to
8jdk and it worked. Thanks a bunch for getting back to me!
openjdk version "1.8.0_171"
OpenJDK Runtime Environment (build 1.8.0_171-8u171-b11-2-b11)
OpenJDK 64-Bit Server VM (build 25.171-b11, mixed mode)
❯ java --version
openjdk 10.0.1 2018-04-17
OpenJDK Runtime Environment (build 10.0.1+10-Debian-4)
OpenJDK 64-Bit Server VM (build 10.0.1+10-Debian-4, mixed mode)
❯ spark-shell --master 'local[2]'
WARNING: Use --illegal-access=warn to enable warnings of further illegal
reflective access operations
WARNING: All illegal access operations will be denied in a future release
2018-06-06 22:08:16 WARN NativeCodeLoader:62 - Unable to load native-hadoop
library for your platform... using builtin-java classes where applicable
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use
setLogLevel(newLevel).
Failed to initialize compiler: object java.lang.Object in compiler mirror not
found.
** Note that as of 2.8 scala does not assume use of the java classpath.
** For the old behavior pass -usejavacp to scala, or if using a Settings
** object programmatically, settings.usejavacp.value = true.
Failed to initialize compiler: object java.lang.Object in compiler mirror not
found.
** Note that as of 2.8 scala does not assume use of the java classpath.
** For the old behavior pass -usejavacp to scala, or if using a Settings
** object programmatically, settings.usejavacp.value = true.
Exception in thread "main" java.lang.NullPointerException
at
scala.reflect.internal.SymbolTable.exitingPhase(SymbolTable.scala:256)
at
scala.tools.nsc.interpreter.IMain$Request.x$20$lzycompute(IMain.scala:896)
at scala.tools.nsc.interpreter.IMain$Request.x$20(IMain.scala:895)
at
scala.tools.nsc.interpreter.IMain$Request.headerPreamble$lzycompute(IMain.scala:895)
at
scala.tools.nsc.interpreter.IMain$Request.headerPreamble(IMain.scala:895)
at
scala.tools.nsc.interpreter.IMain$Request$Wrapper.preamble(IMain.scala:918)
at
scala.tools.nsc.interpreter.IMain$CodeAssembler$$anonfun$apply$23.apply(IMain.scala:1337)
at
scala.tools.nsc.interpreter.IMain$CodeAssembler$$anonfun$apply$23.apply(IMain.scala:1336)
at scala.tools.nsc.util.package$.stringFromWriter(package.scala:64)
at
scala.tools.nsc.interpreter.IMain$CodeAssembler$class.apply(IMain.scala:1336)
at
scala.tools.nsc.interpreter.IMain$Request$Wrapper.apply(IMain.scala:908)
at
scala.tools.nsc.interpreter.IMain$Request.compile$lzycompute(IMain.scala:1002)
at scala.tools.nsc.interpreter.IMain$Request.compile(IMain.scala:997)
at scala.tools.nsc.interpreter.IMain.compile(IMain.scala:579)
at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:567)
at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:565)
> Nested JSON count() Exception
> -----------------------------
>
> Key: SPARK-24475
> URL: https://issues.apache.org/jira/browse/SPARK-24475
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.3.0
> Reporter: Joseph Toth
> Priority: Major
>
> I have nested structure json file only 2 rows.
>
> {{spark = SparkSession.builder.appName("JSONRead").getOrCreate()}}
> {{jsonData = spark.read.json(file)}}
> {{jsonData.count() will crash with the following exception, jsonData.head(10)
> works.}}{{}}
>
> Traceback (most recent call last):
> File "/usr/lib/python3/dist-packages/IPython/core/interactiveshell.py", line
> 2882, in run_code
> exec(code_obj, self.user_global_ns, self.user_ns)
> File "<ipython-input-46-ef7220990d92>", line 1, in <module>
> jsonData.count()
> File "/usr/local/lib/python3.6/dist-packages/pyspark/sql/dataframe.py", line
> 455, in count
> return int(self._jdf.count())
> File "/usr/local/lib/python3.6/dist-packages/py4j/java_gateway.py", line
> 1160, in __call__
> answer, self.gateway_client, self.target_id, self.name)
> File "/usr/local/lib/python3.6/dist-packages/pyspark/sql/utils.py", line 63,
> in deco
> return f(*a, **kw)
> File "/usr/local/lib/python3.6/dist-packages/py4j/protocol.py", line 320, in
> get_return_value
> format(target_id, ".", name), value)
> py4j.protocol.Py4JJavaError: An error occurred while calling o411.count.
> : java.lang.IllegalArgumentException
> at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
> at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
> at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
> at
> org.apache.spark.util.ClosureCleaner$.getClassReader(ClosureCleaner.scala:46)
> at
> org.apache.spark.util.FieldAccessFinder$$anon$3$$anonfun$visitMethodInsn$2.apply(ClosureCleaner.scala:449)
> at
> org.apache.spark.util.FieldAccessFinder$$anon$3$$anonfun$visitMethodInsn$2.apply(ClosureCleaner.scala:432)
> at
> scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:733)
> at
> scala.collection.mutable.HashMap$$anon$1$$anonfun$foreach$2.apply(HashMap.scala:103)
> at
> scala.collection.mutable.HashMap$$anon$1$$anonfun$foreach$2.apply(HashMap.scala:103)
> at scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:230)
> at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:40)
> at scala.collection.mutable.HashMap$$anon$1.foreach(HashMap.scala:103)
> at
> scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:732)
> at
> org.apache.spark.util.FieldAccessFinder$$anon$3.visitMethodInsn(ClosureCleaner.scala:432)
> at org.apache.xbean.asm5.ClassReader.a(Unknown Source)
> at org.apache.xbean.asm5.ClassReader.b(Unknown Source)
> at org.apache.xbean.asm5.ClassReader.accept(Unknown Source)
> at org.apache.xbean.asm5.ClassReader.accept(Unknown Source)
> at
> org.apache.spark.util.ClosureCleaner$$anonfun$org$apache$spark$util$ClosureCleaner$$clean$14.apply(ClosureCleaner.scala:262)
> at
> org.apache.spark.util.ClosureCleaner$$anonfun$org$apache$spark$util$ClosureCleaner$$clean$14.apply(ClosureCleaner.scala:261)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at
> org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:261)
> at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:159)
> at org.apache.spark.SparkContext.clean(SparkContext.scala:2292)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2066)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2092)
> at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:939)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
> at org.apache.spark.rdd.RDD.collect(RDD.scala:938)
> at
> org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:297)
> at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2770)
> at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2769)
> at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3253)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
> at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3252)
> at org.apache.spark.sql.Dataset.count(Dataset.scala:2769)
> at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native
> Method)
> at
> java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.base/java.lang.reflect.Method.invoke(Method.java:564)
> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
> at py4j.Gateway.invoke(Gateway.java:282)
> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
> at py4j.commands.CallCommand.execute(CallCommand.java:79)
> at py4j.GatewayConnection.run(GatewayConnection.java:214)
> at java.base/java.lang.Thread.run(Thread.java:844)
>
> {"insertId":"1x3kn8pg3lweeql","jsonPayload":\{"channel":"ORDER-BITF--NEO--USD","ordertype":"Sell","price":30.007999999999999,"quantity":5.2375409399999997,"timestamp":"2017-10-18
>
> 03:59:59","total":"157.16812853"},"logName":"projects/m/logs/coinigy-dev","receiveTimestamp":"2017-10-18T03:59:59.911829261Z","resource":\{"labels":{"project_id":"m"},"type":"global"},"timestamp":"2017-10-18T03:59:59.911829261Z"}
> {"insertId":"2shvsbg3lt5jpc","jsonPayload":\{"channel":"ORDER-BITF--NEO--USD","ordertype":"Sell","price":30,"quantity":353.83487022999998,"timestamp":"2017-10-18
>
> 03:59:59","total":"10615.04610690"},"logName":"projects/m/logs/coinigy-dev","receiveTimestamp":"2017-10-18T03:59:59.994692698Z","resource":\{"labels":{"project_id":"m"},"type":"global"},"timestamp":"2017-10-18T03:59:59.994692698Z"}
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