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https://issues.apache.org/jira/browse/BEAM-7246?focusedWorklogId=341632&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-341632
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ASF GitHub Bot logged work on BEAM-7246:
----------------------------------------
Author: ASF GitHub Bot
Created on: 12/Nov/19 03:09
Start Date: 12/Nov/19 03:09
Worklog Time Spent: 10m
Work Description: udim commented on pull request #9606: [BEAM-7246] Add
Google Spanner IO Read on Python SDK
URL: https://github.com/apache/beam/pull/9606#discussion_r343294655
##########
File path: sdks/python/apache_beam/io/gcp/spannerio.py
##########
@@ -0,0 +1,531 @@
+#
+# 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.
+#
+
+"""Google Cloud Spanner IO
+
+This is an experimental module for reading and writing data from Google Cloud
+Spanner. Visit: https://cloud.google.com/spanner for more details.
+
+To read from Cloud Spanner apply ReadFromSpanner transformation. It will
+return a list, where each element represents an individual row returned from
+the read operation. Both Query and Read APIs are supported.
+
+ReadFromSpanner relies on the ReadOperation objects which is exposed by the
+SpannerIO API. ReadOperation holds the immutable data which is responsible to
+execute batch and naive reads on spanner cloud. This is done for more
+convenient programming.
+
+ReadFromSpanner read from cloud spanner by providing the either 'sql' param
+in the constructor or 'table' name with 'columns' as list. For example:::
+
+ records = (pipeline
+ | ReadFromSpanner(PROJECT_ID, INSTANCE_ID, DB_NAME,
+ sql='Select * from users'))
+
+ records = (pipeline
+ | ReadFromSpanner(PROJECT_ID, INSTANCE_ID, DB_NAME,
+ table='users', columns=['id', 'name', 'email']))
+
+You can also performs the multiple reads by provide the list of ReadOperation
+to the ReadFromSpanner transform constructor. ReadOperation exposes two static
+methods. Use 'query' to perform sql based reads, 'table' to perform read from
+table name. For example:::
+
+ read_operations = [
+ ReadOperation.table('customers', ['name', 'email']),
+ ReadOperation.table('vendors', ['name', 'email']),
+ ]
+ all_users = pipeline | ReadFromSpanner(PROJECT_ID, INSTANCE_ID, DB_NAME,
+ read_operations=read_operations)
+
+ ...OR...
+
+ read_operations = [
+ ReadOperation.sql('Select name, email from customers'),
+ ReadOperation.table('vendors', ['name', 'email']),
+ ]
+ all_users = pipeline | ReadFromSpanner(PROJECT_ID, INSTANCE_ID, DB_NAME,
+ read_operations=read_operations)
+
+For more information, please review the docs on class ReadOperation.
+
+User can also able to provide the ReadOperation in form of PCollection via
+pipeline. For example:::
+
+ users = (pipeline
+ | beam.Create([ReadOperation...])
+ | ReadFromSpanner(PROJECT_ID, INSTANCE_ID, DB_NAME))
+
+User may also create cloud spanner transaction from the transform called
+`create_transaction` which is available in the SpannerIO API.
+
+The transform is guaranteed to be executed on a consistent snapshot of data,
+utilizing the power of read only transactions. Staleness of data can be
+controlled by providing the `read_timestamp` or `exact_staleness` param values
+in the constructor.
+
+This transform requires root of the pipeline (PBegin) and returns the dict
+containing 'session_id' and 'transaction_id'. This `create_transaction`
+PTransform later passed to the constructor of ReadFromSpanner. For example:::
+
+ transaction = (pipeline | create_transaction(TEST_PROJECT_ID,
+ TEST_INSTANCE_ID,
+ DB_NAME))
+
+ users = pipeline | ReadFromSpanner(PROJECT_ID, INSTANCE_ID, DB_NAME,
+ sql='Select * from users', transaction=transaction)
+
+ tweets = pipeline | ReadFromSpanner(PROJECT_ID, INSTANCE_ID, DB_NAME,
+ sql='Select * from tweets', transaction=transaction)
+
+For further details of this transform, please review the docs on the
+`create_transaction` method available in the SpannerIO API.
+
+ReadFromSpanner takes this transform in the constructor and pass this to the
+read pipeline as the singleton side input.
+"""
+from __future__ import absolute_import
+
+from collections import namedtuple
+
+from google.cloud.spanner import Client
+from google.cloud.spanner import KeySet
+from google.cloud.spanner_v1.database import BatchSnapshot
+
+from apache_beam import Create
+from apache_beam import DoFn
+from apache_beam import ParDo
+from apache_beam import Reshuffle
+from apache_beam.pvalue import AsSingleton
+from apache_beam.pvalue import PBegin
+from apache_beam.transforms import PTransform
+from apache_beam.transforms import ptransform_fn
+from apache_beam.transforms.display import DisplayDataItem
+from apache_beam.utils.annotations import experimental
+
+__all__ = ['create_transaction', 'ReadFromSpanner', 'ReadOperation']
+
+
+class ReadOperation(namedtuple("ReadOperation",
+ ["read_operation", "batch_action",
+ "transaction_action", "kwargs"])):
+ """
+ Encapsulates a spanner read operation.
+ """
+
+ __slots__ = ()
+
+ @classmethod
+ def query(cls, sql, params=None, param_types=None):
+ """
+ A convenient method to construct ReadOperation from sql query.
+
+ Args:
+ sql: SQL query statement
+ params: (optional) values for parameter replacement. Keys must match the
+ names used in sql
+ param_types: (optional) maps explicit types for one or more param values;
+ required if parameters are passed.
+ """
+
+ if params:
+ assert param_types is not None
+
+ return cls(
+ read_operation="process_query_batch",
+ batch_action="generate_query_batches",
transaction_action="execute_sql",
+ kwargs={'sql': sql, 'params': params, 'param_types': param_types}
+ )
+
+ @classmethod
+ def table(cls, table, columns, index="", keyset=None):
+ """
+ A convenient method to construct ReadOperation from table.
+
+ Args:
+ table: name of the table from which to fetch data.
+ columns: names of columns to be retrieved.
+ index: (optional) name of index to use, rather than the table's primary
+ key.
+ keyset: (optional) `KeySet` keys / ranges identifying rows to be
+ retrieved.
+ """
+ keyset = keyset or KeySet(all_=True)
+ if not isinstance(keyset, KeySet):
+ raise ValueError("keyset must be an instance of class "
+ "google.cloud.spanner_v1.keyset.KeySet")
+ return cls(
+ read_operation="process_read_batch",
+ batch_action="generate_read_batches", transaction_action="read",
+ kwargs={'table': table, 'columns': columns, 'index': index,
+ 'keyset': keyset}
+ )
+
+
+class _BeamSpannerConfiguration(namedtuple(
+ "_BeamSpannerConfiguration", ["project", "instance", "database",
+ "credentials", "pool",
+ "snapshot_read_timestamp",
+ "snapshot_exact_staleness"])):
+ """
+ It holds the immutable data of the connection string to the cloud spanner.
+ """
+
+ @property
+ def snapshot_options(self):
+ snapshot_options = {}
+ if self.snapshot_exact_staleness:
+ snapshot_options['exact_staleness'] = self.snapshot_exact_staleness
+ if self.snapshot_read_timestamp:
+ snapshot_options['read_timestamp'] = self.snapshot_read_timestamp
+ return snapshot_options
+
+
+class _NaiveSpannerReadDoFn(DoFn):
+
+ def __init__(self, spanner_configuration):
+ """
+ A naive version of Spanner read which uses the transaction API of the
+ cloud spanner.
+ https://googleapis.dev/python/spanner/latest/transaction-api.html
+
+ Args:
+ spanner_configuration: (_BeamSpannerConfiguration) Connection details to
+ connect with cloud spanner.
+ """
+ self._spanner_configuration = spanner_configuration
+ self._snapshot = None
+
+ def to_runner_api_parameter(self, context):
+ return self.to_runner_api_pickled(context)
+
+ def setup(self):
+ # setting up client to connect with cloud spanner
+ spanner_client = Client(self._spanner_configuration.project)
+ instance = spanner_client.instance(self._spanner_configuration.instance)
+ self._database = instance.database(self._spanner_configuration.database,
+ pool=self._spanner_configuration.pool)
+
+ def process(self, element, transaction_info):
+ # We used batch snapshot to reuse the same transaction passed through the
+ # side input
+ self._snapshot = BatchSnapshot.from_dict(self._database, transaction_info)
+
+ # getting the transaction from the snapshot's session to run read
operation.
+ with self._snapshot._get_session().transaction() as transaction:
Review comment:
Please don't use client library internal methods like `_get_session`. We
can't rely on them being available or working the same way in the future.
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Issue Time Tracking
-------------------
Worklog Id: (was: 341632)
Time Spent: 40m (was: 0.5h)
> Create a Spanner IO for Python
> ------------------------------
>
> Key: BEAM-7246
> URL: https://issues.apache.org/jira/browse/BEAM-7246
> Project: Beam
> Issue Type: Bug
> Components: io-py-gcp
> Reporter: Reuven Lax
> Assignee: Shehzaad Nakhoda
> Priority: Major
> Time Spent: 40m
> Remaining Estimate: 0h
>
> Add I/O support for Google Cloud Spanner for the Python SDK (Batch Only).
> Testing in this work item will be in the form of DirectRunner tests and
> manual testing.
> Integration and performance tests are a separate work item (not included
> here).
> See https://beam.apache.org/documentation/io/built-in/. The goal is to add
> Google Clound Spanner to the Database column for the Python/Batch row.
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