def test_mr_reduce(self):
stdin = StringIO("\n".join(["foo\tbar\tbar1", "baz\tbad\tbad1\tbad2"]))
stdout = StringIO()
def process(key, vals):
return [[key, len(list(vals)[0])]]
mr_reduce(process, fd=stdin, out=stdout)
self.assertEqual(stdout.getvalue(), "foo\t2\nbaz\t3\n")
def join_things(fields, deleted=False, spam=True):
"""A reducer that joins thing table dumps and data table dumps"""
# Because of how Python handles scope, if we want to modify these outside
# the closure function below, they need to be inside a mutable object.
# http://stackoverflow.com/a/23558809/120999
counters = {
'processed': 0,
'skipped': 0,
}
def process(thing_id, vals):
data = {}
thing = None
for val in vals:
if val[0] == 'thing':
thing = format_dataspec(val,
['data_type', # e.g. 'thing'
'thing_type', # e.g. 'link'
'ups',
'downs',
'deleted',
'spam',
'timestamp'])
elif val[0] == 'data':
val = format_dataspec(val,
['data_type', # e.g. 'data'
'thing_type', # e.g. 'link'
'key', # e.g. 'sr_id'
'value'])
if val.key in fields:
data[val.key] = val.value
if (
# silently ignore if we didn't see the 'thing' row
thing is not None
# remove spam and deleted as appriopriate
and (deleted or thing.deleted == 'f')
and (spam or thing.spam == 'f')
# and silently ignore items that don't have all of the
# data that we need
and all(field in data for field in fields)):
counters['processed'] += 1
yield ((thing_id, thing.thing_type, thing.ups, thing.downs,
thing.deleted, thing.spam, thing.timestamp)
+ tuple(data[field] for field in fields))
else:
counters['skipped'] += 1
mr_reduce(process)
# Print to stderr to avoid getting this caught up in the pipe of
# compute_time_listings.
print >> sys.stderr, '%s items processed, %s skipped' % (
counters['processed'], counters['skipped'])
def join_things(fields, deleted=False, spam=True):
"""A reducer that joins thing table dumps and data table dumps"""
# Because of how Python handles scope, if we want to modify these outside
# the closure function below, they need to be inside a mutable object.
# http://stackoverflow.com/a/23558809/120999
counters = {
'processed': 0,
'skipped': 0,
}
def process(thing_id, vals):
data = {}
thing = None
for val in vals:
if val[0] == 'thing':
thing = format_dataspec(val,
['data_type', # e.g. 'thing'
'thing_type', # e.g. 'link'
'ups',
'downs',
'deleted',
'spam',
'timestamp'])
elif val[0] == 'data':
val = format_dataspec(val,
['data_type', # e.g. 'data'
'thing_type', # e.g. 'link'
'key', # e.g. 'sr_id'
'value'])
if val.key in fields:
data[val.key] = val.value
if (
# silently ignore if we didn't see the 'thing' row
thing is not None
# remove spam and deleted as appriopriate
and (deleted or thing.deleted == 'f')
and (spam or thing.spam == 'f')
# and silently ignore items that don't have all of the
# data that we need
and all(field in data for field in fields)):
counters['processed'] += 1
yield ((thing_id, thing.thing_type, thing.ups, thing.downs,
thing.deleted, thing.spam, thing.timestamp)
+ tuple(data[field] for field in fields))
else:
counters['skipped'] += 1
mr_reduce(process)
# Print to stderr to avoid getting this caught up in the pipe of
# compute_time_listings.
print >> sys.stderr, '%s items processed, %s skipped' % (
counters['processed'], counters['skipped'])
def test_mr_reduce(self):
stdin = StringIO("\n".join([
"foo\tbar\tbar1",
"baz\tbad\tbad1\tbad2",
]))
stdout = StringIO()
def process(key, vals):
return [[key, len(list(vals)[0])]]
mr_reduce(process, fd=stdin, out=stdout)
self.assertEqual(stdout.getvalue(), "foo\t2\nbaz\t3\n")
def join_things(fields, deleted=False, spam=True):
"""A reducer that joins thing table dumps and data table dumps"""
def process(thing_id, vals):
data = {}
thing = None
for val in vals:
if val[0] == 'thing':
thing = format_dataspec(
val,
[
'data_type', # e.g. 'thing'
'thing_type', # e.g. 'link'
'ups',
'downs',
'deleted',
'spam',
'timestamp'
])
elif val[0] == 'data':
val = format_dataspec(
val,
[
'data_type', # e.g. 'data'
'thing_type', # e.g. 'link'
'key', # e.g. 'sr_id'
'value'
])
if val.key in fields:
data[val.key] = val.value
if (
# silently ignore if we didn't see the 'thing' row
thing is not None
# remove spam and deleted as appriopriate
and (deleted or thing.deleted == 'f') and
(spam or thing.spam == 'f')
# and silently ignore items that don't have all of the
# data that we need
and all(field in data for field in fields)):
yield ((thing_id, thing.thing_type, thing.ups, thing.downs,
thing.deleted, thing.spam, thing.timestamp) +
tuple(data[field] for field in fields))
mr_reduce(process)
def join_things(fields, deleted=False, spam=True):
"""A reducer that joins thing table dumps and data table dumps"""
def process(thing_id, vals):
data = {}
thing = None
for val in vals:
if val[0] == "thing":
thing = format_dataspec(
val,
[
"data_type", # e.g. 'thing'
"thing_type", # e.g. 'link'
"ups",
"downs",
"deleted",
"spam",
"timestamp",
],
)
elif val[0] == "data":
val = format_dataspec(
val, ["data_type", "thing_type", "key", "value"] # e.g. 'data' # e.g. 'link' # e.g. 'sr_id'
)
if val.key in fields:
data[val.key] = val.value
if (
# silently ignore if we didn't see the 'thing' row
thing is not None
# remove spam and deleted as appriopriate
and (deleted or thing.deleted == "f")
and (spam or thing.spam == "f")
# and silently ignore items that don't have all of the
# data that we need
and all(field in data for field in fields)
):
yield (
(thing_id, thing.thing_type, thing.ups, thing.downs, thing.deleted, thing.spam, thing.timestamp)
+ tuple(data[field] for field in fields)
)
mr_reduce(process)
def join_things(fields, deleted=False, spam=True):
"""A reducer that joins thing table dumps and data table dumps"""
def process(thing_id, vals):
data = {}
thing = None
for val in vals:
if val[0] == 'thing':
thing = format_dataspec(val,
['data_type', # e.g. 'thing'
'thing_type', # e.g. 'link'
'ups',
'downs',
'deleted',
'spam',
'timestamp'])
elif val[0] == 'data':
val = format_dataspec(val,
['data_type', # e.g. 'data'
'thing_type', # e.g. 'link'
'key', # e.g. 'sr_id'
'value'])
if val.key in fields:
data[val.key] = val.value
if (
# silently ignore if we didn't see the 'thing' row
thing is not None
# remove spam and deleted as appriopriate
and (deleted or thing.deleted == 'f')
and (spam or thing.spam == 'f')
# and silently ignore items that don't have all of the
# data that we need
and all(field in data for field in fields)):
yield ((thing_id, thing.thing_type, thing.ups, thing.downs,
thing.deleted, thing.spam, thing.timestamp)
+ tuple(data[field] for field in fields))
mr_reduce(process)
def join_things(
fields,
deleted=False,
spam=True,
fd=STDIN,
out=STDOUT,
err=STDERR,
defaults=None,
):
"""A reducer that joins thing table dumps and data table dumps
:param list fields: list of data fields that the resulting thing must
contain. Any things that missing these any of these fields (unless
provided in the dump or by :param:`defaults`) will be silently dropped.
:param bool deleted: Allow deleted items.
:param bool spam: Allow spam items.
:param file fd: Input stream.
:param file out: Output stream.
:param file err: Error stream.
:param defaults: mapping of fieldnames to default values if not provided
in the input stream.
:type defaults: dict or None
"""
# Because of how Python handles scope, if we want to modify these outside
# the closure function below, they need to be inside a mutable object.
# http://stackoverflow.com/a/23558809/120999
counters = {
'processed': 0,
'skipped': 0,
}
def process(thing_id, vals):
data = {}
if defaults:
data.update(defaults)
thing = None
for val in vals:
if val[0] == 'thing':
thing = format_dataspec(val,
['data_type', # e.g. 'thing'
'thing_type', # e.g. 'link'
'ups',
'downs',
'deleted',
'spam',
'timestamp'])
elif val[0] == 'data':
val = format_dataspec(val,
['data_type', # e.g. 'data'
'thing_type', # e.g. 'link'
'key', # e.g. 'sr_id'
'value'])
if val.key in fields:
data[val.key] = val.value
if (
# silently ignore if we didn't see the 'thing' row
thing is not None
# remove spam and deleted as appriopriate
and (deleted or thing.deleted == 'f')
and (spam or thing.spam == 'f')
# and silently ignore items that don't have all of the
# data that we need
and all(field in data for field in fields)):
counters['processed'] += 1
yield ((thing_id, thing.thing_type, thing.ups, thing.downs,
thing.deleted, thing.spam, thing.timestamp)
+ tuple(data[field] for field in fields))
else:
counters['skipped'] += 1
mr_reduce(process, fd=fd, out=out)
# Print to stderr to avoid getting this caught up in the pipe of
# compute_time_listings.
err.write(
'%s items processed, %s skipped\n' % (
counters['processed'], counters['skipped']
)
)
def join_things(
fields,
deleted=False,
spam=True,
fd=STDIN,
out=STDOUT,
err=STDERR,
defaults=None,
):
"""A reducer that joins thing table dumps and data table dumps
:param list fields: list of data fields that the resulting thing must
contain. Any things that missing these any of these fields (unless
provided in the dump or by :param:`defaults`) will be silently dropped.
:param bool deleted: Allow deleted items.
:param bool spam: Allow spam items.
:param file fd: Input stream.
:param file out: Output stream.
:param file err: Error stream.
:param defaults: mapping of fieldnames to default values if not provided
in the input stream.
:type defaults: dict or None
"""
# Because of how Python handles scope, if we want to modify these outside
# the closure function below, they need to be inside a mutable object.
# http://stackoverflow.com/a/23558809/120999
counters = {
'processed': 0,
'skipped': 0,
}
def process(thing_id, vals):
data = {}
if defaults:
data.update(defaults)
thing = None
for val in vals:
if val[0] == 'thing':
thing = format_dataspec(
val,
[
'data_type', # e.g. 'thing'
'thing_type', # e.g. 'link'
'ups',
'downs',
'deleted',
'spam',
'timestamp'
])
elif val[0] == 'data':
val = format_dataspec(
val,
[
'data_type', # e.g. 'data'
'thing_type', # e.g. 'link'
'key', # e.g. 'sr_id'
'value'
])
if val.key in fields:
data[val.key] = val.value
if (
# silently ignore if we didn't see the 'thing' row
thing is not None
# remove spam and deleted as appriopriate
and (deleted or thing.deleted == 'f') and
(spam or thing.spam == 'f')
# and silently ignore items that don't have all of the
# data that we need
and all(field in data for field in fields)):
counters['processed'] += 1
yield ((thing_id, thing.thing_type, thing.ups, thing.downs,
thing.deleted, thing.spam, thing.timestamp) +
tuple(data[field] for field in fields))
else:
counters['skipped'] += 1
mr_reduce(process, fd=fd, out=out)
# Print to stderr to avoid getting this caught up in the pipe of
# compute_time_listings.
err.write('%s items processed, %s skipped\n' %
(counters['processed'], counters['skipped']))
