#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from __future__ import print_function
import sys
from pyspark import SparkContext
"""
Create test table in HBase first:
hbase(main):001:0> create 'test', 'f1'
0 row(s) in 0.7840 seconds
> hbase_outputformat <host> test row1 f1 q1 value1
> hbase_outputformat <host> test row2 f1 q1 value2
> hbase_outputformat <host> test row3 f1 q1 value3
> hbase_outputformat <host> test row4 f1 q1 value4
hbase(main):002:0> scan 'test'
ROW COLUMN+CELL
row1 column=f1:q1, timestamp=1405659615726, value=value1
row2 column=f1:q1, timestamp=1405659626803, value=value2
row3 column=f1:q1, timestamp=1405659640106, value=value3
row4 column=f1:q1, timestamp=1405659650292, value=value4
4 row(s) in 0.0780 seconds
"""
if __name__ == "__main__":
if len(sys.argv) != 7:
print("""
Usage: hbase_outputformat <host> <table> <row> <family> <qualifier> <value>
Run with example jar:
./bin/spark-submit --driver-class-path /path/to/example/jar \
/path/to/examples/hbase_outputformat.py <args>
Assumes you have created <table> with column family <family> in HBase
running on <host> already
""", file=sys.stderr)
exit(-1)
host = sys.argv[1]
table = sys.argv[2]
sc = SparkContext(appName="HBaseOutputFormat")
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"}
keyConv = "org.apache.spark.examples.pythonconverters.StringToImmutableBytesWritableConverter"
valueConv = "org.apache.spark.examples.pythonconverters.StringListToPutConverter"
sc.parallelize([sys.argv[3:]]).map(lambda x: (x[0], x)).saveAsNewAPIHadoopDataset(
conf=conf,
keyConverter=keyConv,
valueConverter=valueConv)
sc.stop()
