[
https://issues.apache.org/jira/browse/BEAM-3342?focusedWorklogId=357923&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-357923
]
ASF GitHub Bot logged work on BEAM-3342:
----------------------------------------
Author: ASF GitHub Bot
Created on: 11/Dec/19 15:58
Start Date: 11/Dec/19 15:58
Worklog Time Spent: 10m
Work Description: chamikaramj commented on pull request #8457:
[BEAM-3342] Create a Cloud Bigtable IO connector for Python
URL: https://github.com/apache/beam/pull/8457#discussion_r356682146
##########
File path: sdks/python/apache_beam/io/gcp/bigtableio.py
##########
@@ -122,22 +126,145 @@ class WriteToBigTable(beam.PTransform):
A PTransform that write a list of `DirectRow` into the Bigtable Table
"""
- def __init__(self, project_id=None, instance_id=None,
- table_id=None):
+ def __init__(self, project_id=None, instance_id=None, table_id=None):
""" The PTransform to access the Bigtable Write connector
Args:
project_id(str): GCP Project of to write the Rows
instance_id(str): GCP Instance to write the Rows
table_id(str): GCP Table to write the `DirectRows`
"""
super(WriteToBigTable, self).__init__()
- self.beam_options = {'project_id': project_id,
- 'instance_id': instance_id,
- 'table_id': table_id}
+ self._beam_options = {'project_id': project_id,
+ 'instance_id': instance_id,
+ 'table_id': table_id}
def expand(self, pvalue):
- beam_options = self.beam_options
+ beam_options = self._beam_options
return (pvalue
| beam.ParDo(_BigTableWriteFn(beam_options['project_id'],
beam_options['instance_id'],
beam_options['table_id'])))
+
+
+class _BigtableReadFn(beam.DoFn):
+ """ Creates the connector that can read rows for Beam pipeline
+
+ Args:
+ project_id(str): GCP Project ID
+ instance_id(str): GCP Instance ID
+ table_id(str): GCP Table ID
+
+ """
+
+ def __init__(self, project_id, instance_id, table_id, filter_=b''):
+ """ Constructor of the Read connector of Bigtable
+
+ Args:
+ project_id: [str] GCP Project of to write the Rows
+ instance_id: [str] GCP Instance to write the Rows
+ table_id: [str] GCP Table to write the `DirectRows`
+ filter_: [RowFilter] Filter to apply to columns in a row.
+ """
+ super(self.__class__, self).__init__()
+ self._initialize({'project_id': project_id,
+ 'instance_id': instance_id,
+ 'table_id': table_id,
+ 'filter_': filter_})
+
+ def __getstate__(self):
+ return self._beam_options
+
+ def __setstate__(self, options):
+ self._initialize(options)
+
+ def _initialize(self, options):
+ self._beam_options = options
+ self.table = None
+ self.sample_row_keys = None
+ self.row_count = Metrics.counter(self.__class__.__name__, 'Rows read')
+
+ def start_bundle(self):
+ if self.table is None:
+ self.table = Client(project=self._beam_options['project_id'])\
+ .instance(self._beam_options['instance_id'])\
+ .table(self._beam_options['table_id'])
+
+ def process(self, element, **kwargs):
+ for row in self.table.read_rows(start_key=element.start_position,
+ end_key=element.end_position,
+ filter_=self._beam_options['filter_']):
+ self.row_count.inc()
+ yield row
+
+ def display_data(self):
+ return {'projectId': DisplayDataItem(self._beam_options['project_id'],
+ label='Bigtable Project Id'),
+ 'instanceId': DisplayDataItem(self._beam_options['instance_id'],
+ label='Bigtable Instance Id'),
+ 'tableId': DisplayDataItem(self._beam_options['table_id'],
+ label='Bigtable Table Id'),
+ 'filter_': DisplayDataItem(str(self._beam_options['filter_']),
+ label='Bigtable Filter')
+ }
+
+
+class ReadFromBigTable(beam.PTransform):
+ def __init__(self, project_id, instance_id, table_id, filter_=b''):
+ """ The PTransform to access the Bigtable Read connector
+
+ Args:
+ project_id: [str] GCP Project of to read the Rows
+ instance_id): [str] GCP Instance to read the Rows
+ table_id): [str] GCP Table to read the Rows
+ filter_: [RowFilter] Filter to apply to columns in a row.
+ """
+ super(self.__class__, self).__init__()
+ self._beam_options = {'project_id': project_id,
+ 'instance_id': instance_id,
+ 'table_id': table_id,
+ 'filter_': filter_}
+
+ def __getstate__(self):
+ return self._beam_options
+
+ def __setstate__(self, options):
+ self._beam_options = options
+
+ def expand(self, pbegin):
+ from apache_beam.transforms import util
+
+ beam_options = self._beam_options
+ table = Client(project=beam_options['project_id'])\
+ .instance(beam_options['instance_id'])\
+ .table(beam_options['table_id'])
+ sample_row_keys = list(table.sample_row_keys())
+
+ if len(sample_row_keys) > 1 and sample_row_keys[0].row_key != b'':
+ SampleRowKey = namedtuple("SampleRowKey", "row_key offset_bytes")
+ first_key = SampleRowKey(b'', 0)
+ sample_row_keys.insert(0, first_key)
+ sample_row_keys = list(sample_row_keys)
+
+ def split_source(unused_impulse):
+ bundles = []
+ for i in range(1, len(sample_row_keys)):
Review comment:
This might has been implemented incorrectly. 'sample_row_keys' is
implemented in the outer scope but 'split_source' is used as input to a FlatMap
transform (hence split_source will be come a function wrapping a DoFn). Instead
of using FlatMap here implement a DoFn class and provide whatever state that it
needs to perform splitting to the constructor of the DoFn. Also note that this
class (with it's state) has to be picklable.
One difference between Direct and Dataflow runners is that Dataflow runner
pickles DoFn objects to send to remote workers. That might explain why your
code doesn't work for Dataflow.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
us...@infra.apache.org
Issue Time Tracking
-------------------
Worklog Id: (was: 357923)
Time Spent: 43h 10m (was: 43h)
> Create a Cloud Bigtable IO connector for Python
> -----------------------------------------------
>
> Key: BEAM-3342
> URL: https://issues.apache.org/jira/browse/BEAM-3342
> Project: Beam
> Issue Type: Bug
> Components: sdk-py-core
> Reporter: Solomon Duskis
> Assignee: Solomon Duskis
> Priority: Major
> Time Spent: 43h 10m
> Remaining Estimate: 0h
>
> I would like to create a Cloud Bigtable python connector.
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
