blob: 8bd6b9debe0df446a9412de1e3462dc9bc7dad39 [file] [log] [blame]
#!/bin/bash
#
# 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.
# The line below is interpreted as an invalid command in bash and a string literal in
# python.
'''' &>/dev/null
set -e
# pypy is preferred since it's about 10x faster than cpython.
if which pypy &>/dev/null; then
exec pypy $0
else
exec python $0
fi
'''
'''This is a reducer for use with hadoop streaming. See data_generator.DatabasePopulator
for more information on how this file is used.
'''
import os
import random
import subprocess
import sys
# When running locally, the PYTHONPATH needed by impala-shell interferes with python
# through YARN. Specifically, when the data generator needs to import common.py, python
# looks at $IMPALA_HOME/tests/common and errors when it doesn't find what was asked for.
sys.path.insert(1, os.getcwd())
from data_generator_mapred_common import deserialize
for line in sys.stdin:
_, batch_idx, serialized_table_data_generator = line.split("\t")
table_data_generator = deserialize(serialized_table_data_generator)
random.seed(table_data_generator.randomization_seed)
output_file_name = "batch_%s.data" % batch_idx
with open(output_file_name, "w") as output_file:
table_data_generator.output_file = output_file
table_data_generator.populate_output_file()
put = subprocess.Popen(["hadoop", "fs", "-put", output_file.name,
table_data_generator.table.storage_location],
stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
put.wait()
if put.returncode != 0:
raise Exception("Error uploading data to hdfs: %s" % put.communicate()[0])
os.remove(output_file.name)