| # |
| # 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. |
| # |
| |
| """ |
| 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...> |
| """ |
| import sys |
| |
| from pyspark.sql import SparkSession |
| |
| 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) |
| sys.exit(-1) |
| |
| path = sys.argv[1] |
| |
| spark = SparkSession\ |
| .builder\ |
| .appName("ParquetInputFormat")\ |
| .getOrCreate() |
| |
| sc = spark.sparkContext |
| |
| parquet_rdd = sc.newAPIHadoopFile( |
| path, |
| 'org.apache.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) |
| |
| spark.stop() |