| # |
| # 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.avro in local Spark distro: |
| |
| $ cd $SPARK_HOME |
| $ ./bin/spark-submit --driver-class-path /path/to/example/jar \ |
| > ./examples/src/main/python/avro_inputformat.py \ |
| > examples/src/main/resources/users.avro |
| {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': []} |
| |
| To read name and favorite_color fields only, specify the following reader schema: |
| |
| $ cat examples/src/main/resources/user.avsc |
| {"namespace": "example.avro", |
| "type": "record", |
| "name": "User", |
| "fields": [ |
| {"name": "name", "type": "string"}, |
| {"name": "favorite_color", "type": ["string", "null"]} |
| ] |
| } |
| |
| $ ./bin/spark-submit --driver-class-path /path/to/example/jar \ |
| > ./examples/src/main/python/avro_inputformat.py \ |
| > examples/src/main/resources/users.avro examples/src/main/resources/user.avsc |
| {u'favorite_color': None, u'name': u'Alyssa'} |
| {u'favorite_color': u'red', u'name': u'Ben'} |
| """ |
| import sys |
| |
| from functools import reduce |
| from pyspark.sql import SparkSession |
| |
| if __name__ == "__main__": |
| if len(sys.argv) != 2 and len(sys.argv) != 3: |
| print(""" |
| Usage: avro_inputformat <data_file> [reader_schema_file] |
| |
| Run with example jar: |
| ./bin/spark-submit --driver-class-path /path/to/example/jar \ |
| /path/to/examples/avro_inputformat.py <data_file> [reader_schema_file] |
| Assumes you have Avro data stored in <data_file>. Reader schema can be optionally specified |
| in [reader_schema_file]. |
| """, file=sys.stderr) |
| sys.exit(-1) |
| |
| path = sys.argv[1] |
| |
| spark = SparkSession\ |
| .builder\ |
| .appName("AvroKeyInputFormat")\ |
| .getOrCreate() |
| |
| sc = spark.sparkContext |
| |
| conf = None |
| if len(sys.argv) == 3: |
| schema_rdd = sc.textFile(sys.argv[2], 1).collect() |
| conf = {"avro.schema.input.key": reduce(lambda x, y: x + y, schema_rdd)} |
| |
| avro_rdd = sc.newAPIHadoopFile( |
| path, |
| "org.apache.avro.mapreduce.AvroKeyInputFormat", |
| "org.apache.avro.mapred.AvroKey", |
| "org.apache.hadoop.io.NullWritable", |
| keyConverter="org.apache.spark.examples.pythonconverters.AvroWrapperToJavaConverter", |
| conf=conf) |
| output = avro_rdd.map(lambda x: x[0]).collect() |
| for k in output: |
| print(k) |
| |
| spark.stop() |