为什么apache spark不适用于java 10？我们得到非法反映然后java.lang.IllegalArgumentException

Question

有什么技术原因为什么spark 2.3不适用于java 1.10（截至2018年7月）？

这是使用spark-submit运行SparkPi示例时的输出。

$ ./bin/spark-submit ./examples/src/main/python/pi.py 
WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by org.apache.hadoop.security.authentication.util.KerberosUtil to method sun.security.krb5.Config.getInstance()
WARNING: Please consider reporting this to the maintainers of org.apache.hadoop.security.authentication.util.KerberosUtil
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
2018-07-13 14:31:30 WARN  NativeCodeLoader:62 - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
2018-07-13 14:31:31 INFO  SparkContext:54 - Running Spark version 2.3.1
2018-07-13 14:31:31 INFO  SparkContext:54 - Submitted application: PythonPi
2018-07-13 14:31:31 INFO  Utils:54 - Successfully started service 'sparkDriver' on port 58681.
2018-07-13 14:31:31 INFO  SparkEnv:54 - Registering MapOutputTracker
2018-07-13 14:31:31 INFO  SparkEnv:54 - Registering BlockManagerMaster
2018-07-13 14:31:31 INFO  BlockManagerMasterEndpoint:54 - Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information
2018-07-13 14:31:31 INFO  BlockManagerMasterEndpoint:54 - BlockManagerMasterEndpoint up
2018-07-13 14:31:31 INFO  DiskBlockManager:54 - Created local directory at /private/var/folders/mp/9hp4l4md4dqgmgyv7g58gbq0ks62rk/T/blockmgr-d24fab4c-c858-4cd8-9b6a-97b02aa630a5
2018-07-13 14:31:31 INFO  MemoryStore:54 - MemoryStore started with capacity 434.4 MB
2018-07-13 14:31:31 INFO  SparkEnv:54 - Registering OutputCommitCoordinator
...
2018-07-13 14:31:32 INFO  StateStoreCoordinatorRef:54 - Registered StateStoreCoordinator endpoint
Traceback (most recent call last):
  File "~/Documents/spark-2.3.1-bin-hadoop2.7/./examples/src/main/python/pi.py", line 44, in <module>
    count = spark.sparkContext.parallelize(range(1, n + 1), partitions).map(f).reduce(add)
  File "~/Documents/spark-2.3.1-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/rdd.py", line 862, in reduce
  File "~/Documents/spark-2.3.1-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/rdd.py", line 834, in collect
  File "~/Documents/spark-2.3.1-bin-hadoop2.7/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
  File "~/Documents/spark-2.3.1-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/sql/utils.py", line 63, in deco
  File "~/Documents/spark-2.3.1-bin-hadoop2.7/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: 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:2299)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2073)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
    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$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
    at org.apache.spark.rdd.RDD.collect(RDD.scala:938)
    at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:162)
    at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
    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:238)
    at java.base/java.lang.Thread.run(Thread.java:844)

2018-07-13 14:31:33 INFO  SparkContext:54 - Invoking stop() from shutdown hook
...

我通过切换到Java8而不是Java10解决了这个问题，如here所述。

Answer 1

主要技术原因是Spark很大程度上依赖于使用sun.misc.Unsafe直接访问本机内存，https://issues.apache.org/jira/browse/SPARK-24421在Java 9中已经被私有化了。

• http://apache-spark-developers-list.1001551.n3.nabble.com/Java-9-td20875.html
• https://issues.apache.org/jira/browse/SPARK-24417

Answer 2

提交者在这里。支持Java 9+实际上是一项相当大的工作：sun.misc.Unsafe

它几乎已经完成，应该为Spark 3.0做好准备，它应该在Java 8到11及更高版本上运行。

目标（好吧，我的）是在没有开放模块访问的情况下使其工作。

关键问题包括：

• https://issues.apache.org/jira/browse/SPARK-24421的使用必须被删除或解决
• 对引导类加载器结构的更改
• Scala支持Java 9+
• 一堆依赖更新可与Java 9+一起使用
• JAXB不再自动可用

Answer 3

Spark依赖于已在JDK 9中更改的内存API，因此从JDK 9开始不可用。

这就是原因。

请检查问题：

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