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April 10, 2017 19:12
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from apache_beam.metrics.metric import MetricsFilter | |
from apache_beam.utils.pipeline_options import GoogleCloudOptions | |
from apache_beam.utils.pipeline_options import PipelineOptions | |
from apache_beam.utils.pipeline_options import SetupOptions | |
from apache_beam.utils.pipeline_options import StandardOptions | |
import googledatastore | |
import apache_beam as beam | |
import json | |
import time | |
import MySQLdb | |
from MySQLdb.cursors import SSCursor | |
kind = "part" | |
def chunks(l, n): | |
"""Yield successive n-sized chunks from l.""" | |
for i in range(0, len(l), n): | |
yield l[i:i + n] | |
class get_rows(iobase.BoundedSource): | |
def __init__(self): | |
print "init" | |
self.conn = MySQLdb.connect(host = "xxx" , user = "xxx", passwd = "xxx", db = "xxx", cursorclass=MySQLdb.cursors.SSCursor) | |
self.cursor = self.conn.cursor() | |
self.cursor.execute("SELECT * FROM part;") | |
self.i = 0 | |
self.ii = 0 | |
def estimate_size(self): | |
print "estimate size" | |
return 5000000/400 | |
def split(self, desired_bundle_size, start_position=None, end_position=None): | |
print "split" | |
for x in xrange(estimate_size()): | |
yield iobase.SourceBundle(weight=(1), | |
source=self, | |
start_position=x, | |
stop_position=x) | |
def get_range_tracker(self, start_position, end_position): | |
start, end = self._normalize(start_position, end_position) | |
return range_trackers.OffsetRangeTracker(start, end) | |
def read(self, range_tracker): | |
print "read" | |
rows = self.cursor.fetchmany(400) | |
if rows == (): | |
print "fetch done" | |
return | |
print "row batch" | |
for row in rows: | |
# The name/ID for the new entity | |
name = row[0] | |
# The Cloud Datastore key for the new entity | |
task_entity = entity_pb2.Entity() | |
googledatastore.helper.add_properties(task_entity, {'pullurl': unicode(row[1])}) | |
googledatastore.helper.add_properties(task_entity, {'pulldate': unicode(row[3])}) | |
# Prepares the new entity | |
data = json.loads(row[2]) | |
for key in data: | |
if key == "partnumbervariations": | |
for num in data[key]: | |
name = num.replace("-", "").replace(" ","") | |
if key == "title": | |
if "title2" not in data.keys() or len(data["title2"]) == 0: | |
googledatastore.helper.add_properties(task_entity, {"title": data[key]}) | |
elif key == "title2": | |
if len(data["title2"]) >= 0: | |
googledatastore.helper.add_properties(task_entity, {"title": data[key]}) | |
elif key == "uses": | |
pass | |
elif key == "description": | |
googledatastore.helper.add_properties(task_entity, {key: [d.replace("Purchase this ", "") for d in data[key]]}) | |
else: | |
d = data[key] | |
if type(d) is list or type(d) is tuple: | |
if len(d) != 0: | |
googledatastore.helper.add_properties(task_entity, {key: d}) | |
else: | |
googledatastore.helper.add_properties(task_entity, {key: d}) | |
self.i += 1 | |
if self.i % 100 == 0: | |
print "i", self.i, name | |
googledatastore.helper.add_key_path(task_entity.key, kind, name) | |
yield task_entity | |
class ReadFromCountingSource(PTransform): | |
def __init__(self, **kwargs): | |
super(ReadFromCountingSource, self).__init__(**kwargs) | |
def expand(self, pcoll): | |
return pcoll | iobase.Read(get_rows()) | |
options = PipelineOptions() | |
options.view_as(SetupOptions).save_main_session = True | |
google_cloud_options = options.view_as(GoogleCloudOptions) | |
google_cloud_options.project = 'xxxx' | |
google_cloud_options.job_name = 'myjob' | |
google_cloud_options.staging_location = 'gs://xxx/staging' | |
google_cloud_options.temp_location = 'gs://xxx/temp' | |
#options.view_as(StandardOptions).runner = 'DataflowRunner' | |
sys.setrecursionlimit(5000000/200) | |
p = beam.Pipeline(options=options) | |
gcloud_options = options.view_as(GoogleCloudOptions) | |
#(p | |
# | 'add seed' >> beam.Create(['seed']) | |
# | 'add from sql' >> beam.ParDo(get_rows()) | |
# | 'Write To Datastore' >> WriteToDatastore(gcloud_options.project)) | |
(p | |
| 'ProduceNumbers' >> ReadFromCountingSource() | |
| 'Write To Datastore' >> WriteToDatastore(gcloud_options.project)) | |
result = p.run() |
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