MapR Stream and PySpark - apache-spark

Question

Does PySpark work (compatible) for MapR Streams?
Any example code?
I've tried that but keep getting exception
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)
On Scala, it seems to work fine, but on PySpark, not.

Answer 1

I downloaded the latest build http://package.mapr.com/releases/ecosystem-5.x/redhat/mapr-spark-1.6.1.201612010646-1.noarch.rpm and it resolved the issue.
I've checked the the pyspark kafka.py, and found it updated. I was using label 1605, now 1611.