Spark 2.3: python example from the readme gives '"java.lang.IllegalArgumentException"
Closed this issue · 5 comments
I use the following versions:
python 2.7.10
pyddq==4.1.1
drunken-data-quality==4.1.1
spark 2.3.0
spark uses scala 2.11.8
java 1.8.0_162
Are there people that are able to run this? I have a feeling that this issue might be due to wrong/conflicting versions.
import os
os.environ['PYSPARK_SUBMIT_ARGS'] = '--jars /Users/vincent/Downloads/drunken-data-quality-assembly_2.11-4.1.1.jar pyspark-shell'
from pyspark.sql import SparkSession
from pyddq.core import Check
sparkSession = SparkSession.builder.appName("example-pyspark-read-and-write").getOrCreate()
df = sparkSession.createDataFrame([(1, "a"), (1, None), (3, "c")])
check = Check(df)
check.hasUniqueKey("_1", "_2").isNeverNull("_1").run()
above test case gives the following error:
Traceback (most recent call last):
File "/Users/vincent/Library/Preferences/PyCharmCE2017.1/scratches/scratch_3.py", line 9, in <module>
check.hasUniqueKey("_1", "_2").isNeverNull("_1").run()
File "/Users/vincent/Workspace/test_dags/venv/lib/python2.7/site-packages/pyddq/core.py", line 436, in run
self.jvmCheck.run(jvm_reporters)
File "/Users/vincent/Workspace/test_dags/venv/lib/python2.7/site-packages/py4j/java_gateway.py", line 1160, in __call__
answer, self.gateway_client, self.target_id, self.name)
File "/Users/vincent/Workspace/test_dags/venv/lib/python2.7/site-packages/pyspark/sql/utils.py", line 63, in deco
return f(*a, **kw)
File "/Users/vincent/Workspace/test_dags/venv/lib/python2.7/site-packages/py4j/protocol.py", line 320, in get_return_value
format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling o49.run.
: 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 de.frosner.ddq.core.Runner$$anonfun$run$1.apply(Runner.scala:22)
at de.frosner.ddq.core.Runner$$anonfun$run$1.apply(Runner.scala:19)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.immutable.List.map(List.scala:285)
at de.frosner.ddq.core.Runner$.run(Runner.scala:19)
at de.frosner.ddq.core.Check.run(Check.scala:209)
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)
Hi @vincentclaes! Can you check if it runs with Spark 2.2?
thanks @FRosner using spark 2.2 did the job!
Ok. So we're gonna check why it's not working with Spark 2.3 👍
Hi Frosner.
pyddq will support fro python3 .
if it will not support , Can you suggest me the tool of data quality rule base engine .
Thanks
It doesn't support Python 3 at the moment and I'm not actively working on this project right now. If you want, feel free to submit a PR though, we'll review it asap.