I am trying to run the script from this blog
import sys
import json
from pyspark import SparkContext
from pyspark.streaming import StreamingContext
def SaveRecord(rdd):
host = 'sparkmaster.example.com'
table = 'cats'
keyConv = "org.apache.spark.examples.pythonconverters.StringToImmutableBytesWritableConverter"
valueConv = "org.apache.spark.examples.pythonconverters.StringListToPutConverter"
conf = {"hbase.zookeeper.quorum": host,
"hbase.mapred.outputtable": table,
"mapreduce.outputformat.class": "org.apache.hadoop.hbase.mapreduce.TableOutputFormat",
"mapreduce.job.output.key.class": "org.apache.hadoop.hbase.io.ImmutableBytesWritable",
"mapreduce.job.output.value.class": "org.apache.hadoop.io.Writable"}
datamap = rdd.map(lambda x: (str(json.loads(x)["id"]),[str(json.loads(x)["id"]),"cfamily","cats_json",x]))
datamap.saveAsNewAPIHadoopDataset(conf=conf,keyConverter=keyConv,valueConverter=valueConv)
if __name__ == "__main__":
if len(sys.argv) != 3:
print("Usage: StreamCatsToHBase.py <hostname> <port>")
exit(-1)
sc = SparkContext(appName="StreamCatsToHBase")
ssc = StreamingContext(sc, 1)
lines = ssc.socketTextStream(sys.argv[1], int(sys.argv[2]))
lines.foreachRDD(SaveRecord)
ssc.start() # Start the computation
ssc.awaitTermination() # Wait for the computation to terminate
I am unable to run it. I have tried three different command line options but none is producing the output nor writing the data to hbase table
Here are the command line options that i tried
spark-submit --jars /usr/local/spark/lib/spark-examples-1.5.2-hadoop2.4.0.jar --jars /usr/local/hbase/lib/hbase-examples-1.1.2.jar sp_json.py localhost 2389 > sp_json.log
spark-submit --driver-class-path /usr/local/spark/lib/spark-examples-1.5.2-hadoop2.4.0.jar sp_json.py localhost 2389 > sp_json.log
spark-submit --driver-class-path /usr/local/spark/lib/spark-examples-1.5.2-hadoop2.4.0.jar --jars /usr/local/hbase/lib/hbase-examples-1.1.2.jar sp_json.py localhost 2389 > sp_json.log
Here is the logfile. It is too verbose. It is one of the reasons that debugging is difficult in Apache spark because it spits out too much information.
