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from __future__ import print_function
#
# 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.
#
import sys
from pyspark import SparkContext
"""
Read data file users.parquet in local Spark distro:
$ cd $SPARK_HOME
$ export AVRO_PARQUET_JARS=/path/to/parquet-avro-1.5.0.jar
$ ./bin/spark-submit --driver-class-path /path/to/example/jar \\
--jars $AVRO_PARQUET_JARS \\
./examples/src/main/python/parquet_inputformat.py \\
examples/src/main/resources/users.parquet
<...lots of log output...>
{u'favorite_color': None, u'name': u'Alyssa', u'favorite_numbers': [3, 9, 15, 20]}
{u'favorite_color': u'red', u'name': u'Ben', u'favorite_numbers': []}
<...more log output...>
"""
if __name__ == "__main__":
if len(sys.argv) != 2:
print("""
Usage: parquet_inputformat.py <data_file>
Run with example jar:
./bin/spark-submit --driver-class-path /path/to/example/jar \\
/path/to/examples/parquet_inputformat.py <data_file>
Assumes you have Parquet data stored in <data_file>.
""", file=sys.stderr)
exit(-1)
path = sys.argv[1]
sc = SparkContext(appName="ParquetInputFormat")
parquet_rdd = sc.newAPIHadoopFile(
path,
'parquet.avro.AvroParquetInputFormat',
'java.lang.Void',
'org.apache.avro.generic.IndexedRecord',
valueConverter='org.apache.spark.examples.pythonconverters.IndexedRecordToJavaConverter')
output = parquet_rdd.map(lambda x: x[1]).collect()
for k in output:
print(k)
sc.stop()
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