apache-spark - MapR Stream和PySpark

PySpark是否对MapR流有效（兼容）？

任何示例代码？

我已经尝试过了，但是不断出现异常

strLoc   = '/Path1:Stream1'
protocol = 'file://' if  ( strLoc.startswith('/') or strLoc.startswith('\\') ) else ''
from pyspark.streaming.kafka import  *;
from pyspark import  StorageLevel;
APA = KafkaUtils.createDirectStream(ssc, [strLoc], kafkaParams={ \
    "oracle.odi.prefer.dataserver.packages" : "" \
   ,"key.deserializer" : "org.apache.kafka.common.serialization.StringDeserializer" \
   ,"value.deserializer" : "org.apache.kafka.common.serialization.ByteArrayDeserializer" \
   ,"zookeeper.connect" : "maprdemo:5181" \
   ,"metadata.broker.list" : "this.will.be.ignored:9092"
   ,"group.id" : "New_Mapping_2_Physical"}, fromOffsets=None, messageHandler=None)


Traceback (most recent call last):
  File "/tmp/New_Mapping_2_Physical.py", line 77, in <module>
    ,"group.id" : "New_Mapping_2_Physical"}, fromOffsets=None, messageHandler=None)
  File "/opt/mapr/spark/spark-1.6.1/python/lib/pyspark.zip/pyspark/streaming/kafka.py", line 152, in createDirectStream
py4j.protocol.Py4JJavaError: An error occurred while calling o58.createDirectStreamWithoutMessageHandler.
: org.apache.spark.SparkException: java.nio.channels.ClosedChannelException
    at org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$checkErrors$1.apply(KafkaCluster.scala:366)
    at org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$checkErrors$1.apply(KafkaCluster.scala:366)
    at scala.util.Either.fold(Either.scala:97)
    at org.apache.spark.streaming.kafka.KafkaCluster$.checkErrors(KafkaCluster.scala:365)
    at org.apache.spark.streaming.kafka.KafkaUtils$.getFromOffsets(KafkaUtils.scala:222)
    at org.apache.spark.streaming.kafka.KafkaUtilsPythonHelper.createDirectStream(KafkaUtils.scala:720)
    at org.apache.spark.streaming.kafka.KafkaUtilsPythonHelper.createDirectStreamWithoutMessageHandler(KafkaUtils.scala:688)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
    at py4j.Gateway.invoke(Gateway.java:259)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:209)
    at java.lang.Thread.run(Thread.java:745)

在Scala上，它似乎可以正常工作，但在PySpark上，则不能。

最佳答案

我下载了最新的版本http://package.mapr.com/releases/ecosystem-5.x/redhat/mapr-spark-1.6.1.201612010646-1.noarch.rpm，它解决了该问题。

我检查了pyspark kafka.py，发现它已更新。我使用的是标签1605，现在是1611。

关于apache-spark - MapR Stream和PySpark，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/41901171/