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#
# 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
import json
from pyspark import SparkContext
"""
Create test data in HBase first:
hbase(main):016:0> create 'test', 'f1'
0 row(s) in 1.0430 seconds
hbase(main):017:0> put 'test', 'row1', 'f1:a', 'value1'
0 row(s) in 0.0130 seconds
hbase(main):018:0> put 'test', 'row1', 'f1:b', 'value2'
0 row(s) in 0.0030 seconds
hbase(main):019:0> put 'test', 'row2', 'f1', 'value3'
0 row(s) in 0.0050 seconds
hbase(main):020:0> put 'test', 'row3', 'f1', 'value4'
0 row(s) in 0.0110 seconds
hbase(main):021:0> scan 'test'
ROW COLUMN+CELL
row1 column=f1:a, timestamp=1401883411986, value=value1
row1 column=f1:b, timestamp=1401883415212, value=value2
row2 column=f1:, timestamp=1401883417858, value=value3
row3 column=f1:, timestamp=1401883420805, value=value4
4 row(s) in 0.0240 seconds
"""
if __name__ == "__main__":
if len(sys.argv) != 3:
print("""
Usage: hbase_inputformat <host> <table>
Run with example jar:
./bin/spark-submit --driver-class-path /path/to/example/jar \
/path/to/examples/hbase_inputformat.py <host> <table> [<znode>]
Assumes you have some data in HBase already, running on <host>, in <table>
optionally, you can specify parent znode for your hbase cluster - <znode>
""", file=sys.stderr)
exit(-1)
host = sys.argv[1]
table = sys.argv[2]
sc = SparkContext(appName="HBaseInputFormat")
# Other options for configuring scan behavior are available. More information available at
# https://github.com/apache/hbase/blob/master/hbase-server/src/main/java/org/apache/hadoop/hbase/mapreduce/TableInputFormat.java
conf = {"hbase.zookeeper.quorum": host, "hbase.mapreduce.inputtable": table}
if len(sys.argv) > 3:
conf = {"hbase.zookeeper.quorum": host, "zookeeper.znode.parent": sys.argv[3],
"hbase.mapreduce.inputtable": table}
keyConv = "org.apache.spark.examples.pythonconverters.ImmutableBytesWritableToStringConverter"
valueConv = "org.apache.spark.examples.pythonconverters.HBaseResultToStringConverter"
hbase_rdd = sc.newAPIHadoopRDD(
"org.apache.hadoop.hbase.mapreduce.TableInputFormat",
"org.apache.hadoop.hbase.io.ImmutableBytesWritable",
"org.apache.hadoop.hbase.client.Result",
keyConverter=keyConv,
valueConverter=valueConv,
conf=conf)
hbase_rdd = hbase_rdd.flatMapValues(lambda v: v.split("\n")).mapValues(json.loads)
output = hbase_rdd.collect()
for (k, v) in output:
print((k, v))
sc.stop()
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