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Posted to issues@spark.apache.org by "Joseph Toth (JIRA)" <ji...@apache.org> on 2018/06/06 16:10:00 UTC
[jira] [Created] (SPARK-24475) Nested JSON count() Exception
Joseph Toth created SPARK-24475:
-----------------------------------
Summary: 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
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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