I wrote a pyspark script that reads two json files, coGroup
them and sends the result to an elasticsearch cluster; everything works (mostly) as expected when I run it locally, I downloaded the elasticsearch-hadoop
jar file for the org.elasticsearch.hadoop.mr.EsOutputFormat
and org.elasticsearch.hadoop.mr.LinkedMapWritable
classes, and then run my job with pyspark using the --jars
argument, and I can see documents appearing in my elasticsearch cluster.
When I try to run it on a spark cluster, however, I'm getting this error:
Traceback (most recent call last):
File "/root/spark/spark_test.py", line 141, in <module>
conf=es_write_conf
File "/root/spark/python/pyspark/rdd.py", line 1302, in saveAsNewAPIHadoopFile
keyConverter, valueConverter, jconf)
File "/root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py", line 538, in __call__
File "/root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", line 300, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.saveAsNewAPIHadoopFile.
: java.lang.ClassNotFoundException: org.elasticsearch.hadoop.mr.LinkedMapWritable
at java.net.URLClassLoader$1.run(URLClassLoader.java:366)
at java.net.URLClassLoader$1.run(URLClassLoader.java:355)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:354)
at java.lang.ClassLoader.loadClass(ClassLoader.java:425)
at java.lang.ClassLoader.loadClass(ClassLoader.java:358)
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(Class.java:274)
at org.apache.spark.util.Utils$.classForName(Utils.scala:157)
at org.apache.spark.api.python.PythonRDD$$anonfun$getKeyValueTypes$1$$anonfun$apply$9.apply(PythonRDD.scala:611)
at org.apache.spark.api.python.PythonRDD$$anonfun$getKeyValueTypes$1$$anonfun$apply$9.apply(PythonRDD.scala:610)
at scala.Option.map(Option.scala:145)
at org.apache.spark.api.python.PythonRDD$$anonfun$getKeyValueTypes$1.apply(PythonRDD.scala:610)
at org.apache.spark.api.python.PythonRDD$$anonfun$getKeyValueTypes$1.apply(PythonRDD.scala:609)
at scala.Option.flatMap(Option.scala:170)
at org.apache.spark.api.python.PythonRDD$.getKeyValueTypes(PythonRDD.scala:609)
at org.apache.spark.api.python.PythonRDD$.saveAsNewAPIHadoopFile(PythonRDD.scala:701)
at org.apache.spark.api.python.PythonRDD.saveAsNewAPIHadoopFile(PythonRDD.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
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:207)
at java.lang.Thread.run(Thread.java:745)
which seems pretty clear to me: the elasticsearch-hadoop
jar is not available on the workers; so the question: how do I send it along with my app? I could use sc.addPyFile
for a python dependency, but it won't work with jars, and using the --jars
parameters of spark-submit
doesn't help.