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# Copyright 2011 Matthew Tai
# Copyright 2011 Yelp
#
# Licensed 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.
"""Run an MRJob inline by running all mappers and reducers through the same
process. Useful for debugging."""
from __future__ import with_statement
__author__ = 'Matthew Tai <mtai@adku.com>'
import logging
import os
import shutil
import subprocess
import sys
try:
from cStringIO import StringIO
StringIO # quiet "redefinition of unused ..." warning from pyflakes
except ImportError:
from StringIO import StringIO
from mrjob.conf import combine_dicts
from mrjob.conf import combine_local_envs
from mrjob.runner import MRJobRunner
from mrjob.job import MRJob
from mrjob.util import save_current_environment
log = logging.getLogger('mrjob.inline')
class InlineMRJobRunner(MRJobRunner):
"""Runs an :py:class:`~mrjob.job.MRJob` without invoking the job as
a subprocess, so it's easy to attach a debugger.
This is NOT the default way of testing jobs; to more accurately
simulate your environment prior to running on Hadoop/EMR, use ``-r local``.
It's rare to need to instantiate this class directly (see
:py:meth:`~InlineMRJobRunner.__init__` for details).
"""
alias = 'inline'
def __init__(self, mrjob_cls=None, **kwargs):
""":py:class:`~mrjob.inline.InlineMRJobRunner` takes the same keyword
args as :py:class:`~mrjob.runner.MRJobRunner`. However, please note:
* *hadoop_extra_args*, *hadoop_input_format*, *hadoop_output_format*,
and *hadoop_streaming_jar*, *jobconf*, and *partitioner* are ignored
because they require Java. If you need to test these, consider
starting up a standalone Hadoop instance and running your job with
``-r hadoop``.
* *cmdenv*, *python_bin*, *setup_cmds*, *setup_scripts*,
*steps_python_bin*, *upload_archives*, and *upload_files* are ignored
because we don't invoke the job as a subprocess or run it in its own
directory.
"""
super(InlineMRJobRunner, self).__init__(**kwargs)
assert ((mrjob_cls) is None or issubclass(mrjob_cls, MRJob))
self._mrjob_cls = mrjob_cls
self._prev_outfile = None
self._final_outfile = None
self._counters = []
@classmethod
def _opts_combiners(cls):
# on windows, PYTHONPATH should use ;, not :
return combine_dicts(
super(InlineMRJobRunner, cls)._opts_combiners(),
{'cmdenv': combine_local_envs})
# options that we ignore because they require real Hadoop
IGNORED_HADOOP_OPTS = [
'hadoop_extra_args',
'hadoop_streaming_jar',
'jobconf'
]
# keyword arguments that we ignore that are stored directly in
# self._<kwarg_name> because they aren't configurable from mrjob.conf
# use the version with the underscore to better support grepping our code
IGNORED_HADOOP_ATTRS = [
'_hadoop_input_format',
'_hadoop_output_format',
'_partitioner',
]
# options that we ignore because they involve running subprocesses
IGNORED_LOCAL_OPTS = [
'python_bin',
'setup_cmds',
'setup_scripts',
'steps_python_bin',
'upload_archives',
'upload_files',
]
def _run(self):
self._setup_output_dir()
assert self._script # shouldn't be able to run if no script
default_opts = self.get_default_opts()
for ignored_opt in self.IGNORED_HADOOP_OPTS:
if self._opts[ignored_opt] != default_opts[ignored_opt]:
log.warning('ignoring %s option (requires real Hadoop): %r' %
(ignored_opt, self._opts[ignored_opt]))
for ignored_attr in self.IGNORED_HADOOP_ATTRS:
value = getattr(self, ignored_attr)
if value is not None:
log.warning(
'ignoring %s keyword arg (requires real Hadoop): %r' %
(ignored_attr[1:], value))
for ignored_opt in self.IGNORED_LOCAL_OPTS:
if self._opts[ignored_opt] != default_opts[ignored_opt]:
log.warning('ignoring %s option (use -r local instead): %r' %
(ignored_opt, self._opts[ignored_opt]))
with save_current_environment():
# set cmdenv variables
os.environ.update(self._get_cmdenv())
# run mapper, sort, reducer for each step
for step_number, step_name in enumerate(self._get_steps()):
self._invoke_inline_mrjob(step_number, 'step-%d-mapper' %
step_number, is_mapper=True,
has_combiner=('C' in step_name))
if 'R' in step_name:
mapper_output_path = self._prev_outfile
sorted_mapper_output_path = self._decide_output_path(
'step-%d-mapper-sorted' % step_number)
with open(sorted_mapper_output_path, 'w') as sort_out:
proc = subprocess.Popen(
['sort', mapper_output_path],
stdout=sort_out, env={'LC_ALL': 'C'})
proc.wait()
# This'll read from sorted_mapper_output_path
self._invoke_inline_mrjob(step_number, 'step-%d-reducer' %
step_number, is_reducer=True)
# move final output to output directory
self._final_outfile = os.path.join(self._output_dir, 'part-00000')
log.info('Moving %s -> %s' % (self._prev_outfile, self._final_outfile))
shutil.move(self._prev_outfile, self._final_outfile)
def _get_steps(self):
"""Redefine this so that we can get step descriptions without
calling a subprocess."""
job_args = ['--steps'] + self._mr_job_extra_args(local=True)
return self._mrjob_cls(args=job_args)._steps_desc()
def _invoke_inline_mrjob(self, step_number, outfile_name, is_mapper=False,
is_reducer=False, is_combiner=False,
has_combiner=False, child_stdin=None):
child_stdin = child_stdin or sys.stdin
common_args = (['--step-num=%d' % step_number] +
self._mr_job_extra_args(local=True))
if is_mapper:
child_args = (
['--mapper'] + self._decide_input_paths() + common_args)
elif is_reducer:
child_args = (
['--reducer'] + self._decide_input_paths() + common_args)
elif is_combiner:
child_args = ['--combiner'] + common_args + ['-']
child_instance = self._mrjob_cls(args=child_args)
# Use custom stdin
if has_combiner:
child_stdout = StringIO()
else:
outfile = self._decide_output_path(outfile_name)
child_stdout = open(outfile, 'w')
child_instance.sandbox(stdin=child_stdin, stdout=child_stdout)
child_instance.execute()
if has_combiner:
sorted_lines = sorted(child_stdout.getvalue().splitlines())
combiner_stdin = StringIO('\n'.join(sorted_lines))
else:
child_stdout.flush()
child_stdout.close()
while len(self._counters) <= step_number:
self._counters.append({})
child_instance.parse_counters(self._counters[step_number - 1])
self.print_counters([step_number + 1])
if has_combiner:
self._invoke_inline_mrjob(step_number, outfile_name,
is_combiner=True,
child_stdin=combiner_stdin)
combiner_stdin.close()
def counters(self):
return self._counters
def _decide_input_paths(self):
# decide where to get input
if self._prev_outfile is not None:
input_paths = [self._prev_outfile]
else:
input_paths = []
for path in self._input_paths:
if path == '-':
input_paths.append(self._dump_stdin_to_local_file())
else:
input_paths.append(path)
return input_paths
def _decide_output_path(self, outfile_name):
# run the mapper
outfile = os.path.join(self._get_local_tmp_dir(), outfile_name)
log.info('writing to %s' % outfile)
log.debug('')
self._prev_outfile = outfile
return outfile
def _setup_output_dir(self):
if not self._output_dir:
self._output_dir = os.path.join(
self._get_local_tmp_dir(), 'output')
if not os.path.isdir(self._output_dir):
log.debug('Creating output directory %s' % self._output_dir)
self.mkdir(self._output_dir)
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