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Posted to commits@beam.apache.org by al...@apache.org on 2017/02/20 00:21:57 UTC
[2/7] beam git commit: [BEAM-1218] Move GCP specific IO into separate
module
http://git-wip-us.apache.org/repos/asf/beam/blob/908c8532/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/datastoreio.py
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diff --git a/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/datastoreio.py b/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/datastoreio.py
new file mode 100644
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@@ -0,0 +1,391 @@
+#
+# 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.
+#
+
+"""A connector for reading from and writing to Google Cloud Datastore"""
+
+import logging
+
+from google.cloud.proto.datastore.v1 import datastore_pb2
+from googledatastore import helper as datastore_helper
+
+from apache_beam.io.google_cloud_platform.datastore.v1 import helper
+from apache_beam.io.google_cloud_platform.datastore.v1 import query_splitter
+from apache_beam.transforms import Create
+from apache_beam.transforms import DoFn
+from apache_beam.transforms import FlatMap
+from apache_beam.transforms import GroupByKey
+from apache_beam.transforms import Map
+from apache_beam.transforms import PTransform
+from apache_beam.transforms import ParDo
+from apache_beam.transforms.util import Values
+
+__all__ = ['ReadFromDatastore', 'WriteToDatastore', 'DeleteFromDatastore']
+
+
+class ReadFromDatastore(PTransform):
+ """A ``PTransform`` for reading from Google Cloud Datastore.
+
+ To read a ``PCollection[Entity]`` from a Cloud Datastore ``Query``, use
+ ``ReadFromDatastore`` transform by providing a `project` id and a `query` to
+ read from. You can optionally provide a `namespace` and/or specify how many
+ splits you want for the query through `num_splits` option.
+
+ Note: Normally, a runner will read from Cloud Datastore in parallel across
+ many workers. However, when the `query` is configured with a `limit` or if the
+ query contains inequality filters like `GREATER_THAN, LESS_THAN` etc., then
+ all the returned results will be read by a single worker in order to ensure
+ correct data. Since data is read from a single worker, this could have
+ significant impact on the performance of the job.
+
+ The semantics for the query splitting is defined below:
+ 1. If `num_splits` is equal to 0, then the number of splits will be chosen
+ dynamically at runtime based on the query data size.
+
+ 2. Any value of `num_splits` greater than
+ `ReadFromDatastore._NUM_QUERY_SPLITS_MAX` will be capped at that value.
+
+ 3. If the `query` has a user limit set, or contains inequality filters, then
+ `num_splits` will be ignored and no split will be performed.
+
+ 4. Under certain cases Cloud Datastore is unable to split query to the
+ requested number of splits. In such cases we just use whatever the Cloud
+ Datastore returns.
+
+ See https://developers.google.com/datastore/ for more details on Google Cloud
+ Datastore.
+ """
+
+ # An upper bound on the number of splits for a query.
+ _NUM_QUERY_SPLITS_MAX = 50000
+ # A lower bound on the number of splits for a query. This is to ensure that
+ # we parellelize the query even when Datastore statistics are not available.
+ _NUM_QUERY_SPLITS_MIN = 12
+ # Default bundle size of 64MB.
+ _DEFAULT_BUNDLE_SIZE_BYTES = 64 * 1024 * 1024
+
+ def __init__(self, project, query, namespace=None, num_splits=0):
+ """Initialize the ReadFromDatastore transform.
+
+ Args:
+ project: The Project ID
+ query: Cloud Datastore query to be read from.
+ namespace: An optional namespace.
+ num_splits: Number of splits for the query.
+ """
+ logging.warning('datastoreio read transform is experimental.')
+ super(ReadFromDatastore, self).__init__()
+
+ if not project:
+ ValueError("Project cannot be empty")
+ if not query:
+ ValueError("Query cannot be empty")
+ if num_splits < 0:
+ ValueError("num_splits must be greater than or equal 0")
+
+ self._project = project
+ # using _namespace conflicts with DisplayData._namespace
+ self._datastore_namespace = namespace
+ self._query = query
+ self._num_splits = num_splits
+
+ def expand(self, pcoll):
+ # This is a composite transform involves the following:
+ # 1. Create a singleton of the user provided `query` and apply a ``ParDo``
+ # that splits the query into `num_splits` and assign each split query a
+ # unique `int` as the key. The resulting output is of the type
+ # ``PCollection[(int, Query)]``.
+ #
+ # If the value of `num_splits` is less than or equal to 0, then the
+ # number of splits will be computed dynamically based on the size of the
+ # data for the `query`.
+ #
+ # 2. The resulting ``PCollection`` is sharded using a ``GroupByKey``
+ # operation. The queries are extracted from the (int, Iterable[Query]) and
+ # flattened to output a ``PCollection[Query]``.
+ #
+ # 3. In the third step, a ``ParDo`` reads entities for each query and
+ # outputs a ``PCollection[Entity]``.
+
+ queries = (pcoll.pipeline
+ | 'User Query' >> Create([self._query])
+ | 'Split Query' >> ParDo(ReadFromDatastore.SplitQueryFn(
+ self._project, self._query, self._datastore_namespace,
+ self._num_splits)))
+
+ sharded_queries = (queries
+ | GroupByKey()
+ | Values()
+ | 'flatten' >> FlatMap(lambda x: x))
+
+ entities = sharded_queries | 'Read' >> ParDo(
+ ReadFromDatastore.ReadFn(self._project, self._datastore_namespace))
+ return entities
+
+ def display_data(self):
+ disp_data = {'project': self._project,
+ 'query': str(self._query),
+ 'num_splits': self._num_splits}
+
+ if self._datastore_namespace is not None:
+ disp_data['namespace'] = self._datastore_namespace
+
+ return disp_data
+
+ class SplitQueryFn(DoFn):
+ """A `DoFn` that splits a given query into multiple sub-queries."""
+ def __init__(self, project, query, namespace, num_splits):
+ super(ReadFromDatastore.SplitQueryFn, self).__init__()
+ self._datastore = None
+ self._project = project
+ self._datastore_namespace = namespace
+ self._query = query
+ self._num_splits = num_splits
+
+ def start_bundle(self):
+ self._datastore = helper.get_datastore(self._project)
+
+ def process(self, query, *args, **kwargs):
+ # distinct key to be used to group query splits.
+ key = 1
+
+ # If query has a user set limit, then the query cannot be split.
+ if query.HasField('limit'):
+ return [(key, query)]
+
+ # Compute the estimated numSplits if not specified by the user.
+ if self._num_splits == 0:
+ estimated_num_splits = ReadFromDatastore.get_estimated_num_splits(
+ self._project, self._datastore_namespace, self._query,
+ self._datastore)
+ else:
+ estimated_num_splits = self._num_splits
+
+ logging.info("Splitting the query into %d splits", estimated_num_splits)
+ try:
+ query_splits = query_splitter.get_splits(
+ self._datastore, query, estimated_num_splits,
+ helper.make_partition(self._project, self._datastore_namespace))
+ except Exception:
+ logging.warning("Unable to parallelize the given query: %s", query,
+ exc_info=True)
+ query_splits = [query]
+
+ sharded_query_splits = []
+ for split_query in query_splits:
+ sharded_query_splits.append((key, split_query))
+ key += 1
+
+ return sharded_query_splits
+
+ def display_data(self):
+ disp_data = {'project': self._project,
+ 'query': str(self._query),
+ 'num_splits': self._num_splits}
+
+ if self._datastore_namespace is not None:
+ disp_data['namespace'] = self._datastore_namespace
+
+ return disp_data
+
+ class ReadFn(DoFn):
+ """A DoFn that reads entities from Cloud Datastore, for a given query."""
+ def __init__(self, project, namespace=None):
+ super(ReadFromDatastore.ReadFn, self).__init__()
+ self._project = project
+ self._datastore_namespace = namespace
+ self._datastore = None
+
+ def start_bundle(self):
+ self._datastore = helper.get_datastore(self._project)
+
+ def process(self, query, *args, **kwargs):
+ # Returns an iterator of entities that reads in batches.
+ entities = helper.fetch_entities(self._project, self._datastore_namespace,
+ query, self._datastore)
+ return entities
+
+ def display_data(self):
+ disp_data = {'project': self._project}
+
+ if self._datastore_namespace is not None:
+ disp_data['namespace'] = self._datastore_namespace
+
+ return disp_data
+
+ @staticmethod
+ def query_latest_statistics_timestamp(project, namespace, datastore):
+ """Fetches the latest timestamp of statistics from Cloud Datastore.
+
+ Cloud Datastore system tables with statistics are periodically updated.
+ This method fethes the latest timestamp (in microseconds) of statistics
+ update using the `__Stat_Total__` table.
+ """
+ query = helper.make_latest_timestamp_query(namespace)
+ req = helper.make_request(project, namespace, query)
+ resp = datastore.run_query(req)
+ if len(resp.batch.entity_results) == 0:
+ raise RuntimeError("Datastore total statistics unavailable.")
+
+ entity = resp.batch.entity_results[0].entity
+ return datastore_helper.micros_from_timestamp(
+ entity.properties['timestamp'].timestamp_value)
+
+ @staticmethod
+ def get_estimated_size_bytes(project, namespace, query, datastore):
+ """Get the estimated size of the data returned by the given query.
+
+ Cloud Datastore provides no way to get a good estimate of how large the
+ result of a query is going to be. Hence we use the __Stat_Kind__ system
+ table to get size of the entire kind as an approximate estimate, assuming
+ exactly 1 kind is specified in the query.
+ See https://cloud.google.com/datastore/docs/concepts/stats.
+ """
+ kind = query.kind[0].name
+ latest_timestamp = ReadFromDatastore.query_latest_statistics_timestamp(
+ project, namespace, datastore)
+ logging.info('Latest stats timestamp for kind %s is %s',
+ kind, latest_timestamp)
+
+ kind_stats_query = (
+ helper.make_kind_stats_query(namespace, kind, latest_timestamp))
+
+ req = helper.make_request(project, namespace, kind_stats_query)
+ resp = datastore.run_query(req)
+ if len(resp.batch.entity_results) == 0:
+ raise RuntimeError("Datastore statistics for kind %s unavailable" % kind)
+
+ entity = resp.batch.entity_results[0].entity
+ return datastore_helper.get_value(entity.properties['entity_bytes'])
+
+ @staticmethod
+ def get_estimated_num_splits(project, namespace, query, datastore):
+ """Computes the number of splits to be performed on the given query."""
+ try:
+ estimated_size_bytes = ReadFromDatastore.get_estimated_size_bytes(
+ project, namespace, query, datastore)
+ logging.info('Estimated size bytes for query: %s', estimated_size_bytes)
+ num_splits = int(min(ReadFromDatastore._NUM_QUERY_SPLITS_MAX, round(
+ (float(estimated_size_bytes) /
+ ReadFromDatastore._DEFAULT_BUNDLE_SIZE_BYTES))))
+
+ except Exception as e:
+ logging.warning('Failed to fetch estimated size bytes: %s', e)
+ # Fallback in case estimated size is unavailable.
+ num_splits = ReadFromDatastore._NUM_QUERY_SPLITS_MIN
+
+ return max(num_splits, ReadFromDatastore._NUM_QUERY_SPLITS_MIN)
+
+
+class _Mutate(PTransform):
+ """A ``PTransform`` that writes mutations to Cloud Datastore.
+
+ Only idempotent Datastore mutation operations (upsert and delete) are
+ supported, as the commits are retried when failures occur.
+ """
+
+ # Max allowed Datastore write batch size.
+ _WRITE_BATCH_SIZE = 500
+
+ def __init__(self, project, mutation_fn):
+ """Initializes a Mutate transform.
+
+ Args:
+ project: The Project ID
+ mutation_fn: A function that converts `entities` or `keys` to
+ `mutations`.
+ """
+ self._project = project
+ self._mutation_fn = mutation_fn
+ logging.warning('datastoreio write transform is experimental.')
+
+ def expand(self, pcoll):
+ return (pcoll
+ | 'Convert to Mutation' >> Map(self._mutation_fn)
+ | 'Write Mutation to Datastore' >> ParDo(_Mutate.DatastoreWriteFn(
+ self._project)))
+
+ def display_data(self):
+ return {'project': self._project,
+ 'mutation_fn': self._mutation_fn.__class__.__name__}
+
+ class DatastoreWriteFn(DoFn):
+ """A ``DoFn`` that write mutations to Datastore.
+
+ Mutations are written in batches, where the maximum batch size is
+ `Mutate._WRITE_BATCH_SIZE`.
+
+ Commits are non-transactional. If a commit fails because of a conflict over
+ an entity group, the commit will be retried. This means that the mutation
+ should be idempotent (`upsert` and `delete` mutations) to prevent duplicate
+ data or errors.
+ """
+ def __init__(self, project):
+ self._project = project
+ self._datastore = None
+ self._mutations = []
+
+ def start_bundle(self):
+ self._mutations = []
+ self._datastore = helper.get_datastore(self._project)
+
+ def process(self, element):
+ self._mutations.append(element)
+ if len(self._mutations) >= _Mutate._WRITE_BATCH_SIZE:
+ self._flush_batch()
+
+ def finish_bundle(self):
+ if self._mutations:
+ self._flush_batch()
+ self._mutations = []
+
+ def _flush_batch(self):
+ # Flush the current batch of mutations to Cloud Datastore.
+ helper.write_mutations(self._datastore, self._project, self._mutations)
+ logging.debug("Successfully wrote %d mutations.", len(self._mutations))
+ self._mutations = []
+
+
+class WriteToDatastore(_Mutate):
+ """A ``PTransform`` to write a ``PCollection[Entity]`` to Cloud Datastore."""
+ def __init__(self, project):
+ super(WriteToDatastore, self).__init__(
+ project, WriteToDatastore.to_upsert_mutation)
+
+ @staticmethod
+ def to_upsert_mutation(entity):
+ if not helper.is_key_valid(entity.key):
+ raise ValueError('Entities to be written to the Cloud Datastore must '
+ 'have complete keys:\n%s' % entity)
+ mutation = datastore_pb2.Mutation()
+ mutation.upsert.CopyFrom(entity)
+ return mutation
+
+
+class DeleteFromDatastore(_Mutate):
+ """A ``PTransform`` to delete a ``PCollection[Key]`` from Cloud Datastore."""
+ def __init__(self, project):
+ super(DeleteFromDatastore, self).__init__(
+ project, DeleteFromDatastore.to_delete_mutation)
+
+ @staticmethod
+ def to_delete_mutation(key):
+ if not helper.is_key_valid(key):
+ raise ValueError('Keys to be deleted from the Cloud Datastore must be '
+ 'complete:\n%s", key')
+ mutation = datastore_pb2.Mutation()
+ mutation.delete.CopyFrom(key)
+ return mutation
http://git-wip-us.apache.org/repos/asf/beam/blob/908c8532/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/datastoreio_test.py
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diff --git a/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/datastoreio_test.py b/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/datastoreio_test.py
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+#
+# 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.
+#
+
+import unittest
+
+from google.cloud.proto.datastore.v1 import datastore_pb2
+from google.cloud.proto.datastore.v1 import query_pb2
+from google.protobuf import timestamp_pb2
+from googledatastore import helper as datastore_helper
+from mock import MagicMock, call, patch
+
+from apache_beam.io.google_cloud_platform.datastore.v1 import fake_datastore
+from apache_beam.io.google_cloud_platform.datastore.v1 import helper
+from apache_beam.io.google_cloud_platform.datastore.v1 import query_splitter
+from apache_beam.io.google_cloud_platform.datastore.v1.datastoreio import _Mutate
+from apache_beam.io.google_cloud_platform.datastore.v1.datastoreio import ReadFromDatastore
+from apache_beam.io.google_cloud_platform.datastore.v1.datastoreio import WriteToDatastore
+
+
+class DatastoreioTest(unittest.TestCase):
+ _PROJECT = 'project'
+ _KIND = 'kind'
+ _NAMESPACE = 'namespace'
+
+ def setUp(self):
+ self._mock_datastore = MagicMock()
+ self._query = query_pb2.Query()
+ self._query.kind.add().name = self._KIND
+
+ def test_get_estimated_size_bytes_without_namespace(self):
+ entity_bytes = 100
+ timestamp = timestamp_pb2.Timestamp(seconds=1234)
+ self.check_estimated_size_bytes(entity_bytes, timestamp)
+
+ def test_get_estimated_size_bytes_with_namespace(self):
+ entity_bytes = 100
+ timestamp = timestamp_pb2.Timestamp(seconds=1234)
+ self.check_estimated_size_bytes(entity_bytes, timestamp, self._NAMESPACE)
+
+ def test_SplitQueryFn_with_num_splits(self):
+ with patch.object(helper, 'get_datastore',
+ return_value=self._mock_datastore):
+ num_splits = 23
+
+ def fake_get_splits(datastore, query, num_splits, partition=None):
+ return self.split_query(query, num_splits)
+
+ with patch.object(query_splitter, 'get_splits',
+ side_effect=fake_get_splits):
+
+ split_query_fn = ReadFromDatastore.SplitQueryFn(
+ self._PROJECT, self._query, None, num_splits)
+ split_query_fn.start_bundle()
+ returned_split_queries = []
+ for split_query in split_query_fn.process(self._query):
+ returned_split_queries.append(split_query)
+
+ self.assertEqual(len(returned_split_queries), num_splits)
+ self.assertEqual(0, len(self._mock_datastore.run_query.call_args_list))
+ self.verify_unique_keys(returned_split_queries)
+
+ def test_SplitQueryFn_without_num_splits(self):
+ with patch.object(helper, 'get_datastore',
+ return_value=self._mock_datastore):
+ # Force SplitQueryFn to compute the number of query splits
+ num_splits = 0
+ expected_num_splits = 23
+ entity_bytes = (expected_num_splits *
+ ReadFromDatastore._DEFAULT_BUNDLE_SIZE_BYTES)
+ with patch.object(ReadFromDatastore, 'get_estimated_size_bytes',
+ return_value=entity_bytes):
+
+ def fake_get_splits(datastore, query, num_splits, partition=None):
+ return self.split_query(query, num_splits)
+
+ with patch.object(query_splitter, 'get_splits',
+ side_effect=fake_get_splits):
+ split_query_fn = ReadFromDatastore.SplitQueryFn(
+ self._PROJECT, self._query, None, num_splits)
+ split_query_fn.start_bundle()
+ returned_split_queries = []
+ for split_query in split_query_fn.process(self._query):
+ returned_split_queries.append(split_query)
+
+ self.assertEqual(len(returned_split_queries), expected_num_splits)
+ self.assertEqual(0,
+ len(self._mock_datastore.run_query.call_args_list))
+ self.verify_unique_keys(returned_split_queries)
+
+ def test_SplitQueryFn_with_query_limit(self):
+ """A test that verifies no split is performed when the query has a limit."""
+ with patch.object(helper, 'get_datastore',
+ return_value=self._mock_datastore):
+ self._query.limit.value = 3
+ split_query_fn = ReadFromDatastore.SplitQueryFn(
+ self._PROJECT, self._query, None, 4)
+ split_query_fn.start_bundle()
+ returned_split_queries = []
+ for split_query in split_query_fn.process(self._query):
+ returned_split_queries.append(split_query)
+
+ self.assertEqual(1, len(returned_split_queries))
+ self.assertEqual(0, len(self._mock_datastore.method_calls))
+
+ def test_SplitQueryFn_with_exception(self):
+ """A test that verifies that no split is performed when failures occur."""
+ with patch.object(helper, 'get_datastore',
+ return_value=self._mock_datastore):
+ # Force SplitQueryFn to compute the number of query splits
+ num_splits = 0
+ expected_num_splits = 1
+ entity_bytes = (expected_num_splits *
+ ReadFromDatastore._DEFAULT_BUNDLE_SIZE_BYTES)
+ with patch.object(ReadFromDatastore, 'get_estimated_size_bytes',
+ return_value=entity_bytes):
+
+ with patch.object(query_splitter, 'get_splits',
+ side_effect=ValueError("Testing query split error")):
+ split_query_fn = ReadFromDatastore.SplitQueryFn(
+ self._PROJECT, self._query, None, num_splits)
+ split_query_fn.start_bundle()
+ returned_split_queries = []
+ for split_query in split_query_fn.process(self._query):
+ returned_split_queries.append(split_query)
+
+ self.assertEqual(len(returned_split_queries), expected_num_splits)
+ self.assertEqual(returned_split_queries[0][1], self._query)
+ self.assertEqual(0,
+ len(self._mock_datastore.run_query.call_args_list))
+ self.verify_unique_keys(returned_split_queries)
+
+ def test_DatastoreWriteFn_with_emtpy_batch(self):
+ self.check_DatastoreWriteFn(0)
+
+ def test_DatastoreWriteFn_with_one_batch(self):
+ num_entities_to_write = _Mutate._WRITE_BATCH_SIZE * 1 - 50
+ self.check_DatastoreWriteFn(num_entities_to_write)
+
+ def test_DatastoreWriteFn_with_multiple_batches(self):
+ num_entities_to_write = _Mutate._WRITE_BATCH_SIZE * 3 + 50
+ self.check_DatastoreWriteFn(num_entities_to_write)
+
+ def test_DatastoreWriteFn_with_batch_size_exact_multiple(self):
+ num_entities_to_write = _Mutate._WRITE_BATCH_SIZE * 2
+ self.check_DatastoreWriteFn(num_entities_to_write)
+
+ def check_DatastoreWriteFn(self, num_entities):
+ """A helper function to test DatastoreWriteFn."""
+
+ with patch.object(helper, 'get_datastore',
+ return_value=self._mock_datastore):
+ entities = [e.entity for e in
+ fake_datastore.create_entities(num_entities)]
+
+ expected_mutations = map(WriteToDatastore.to_upsert_mutation, entities)
+ actual_mutations = []
+
+ self._mock_datastore.commit.side_effect = (
+ fake_datastore.create_commit(actual_mutations))
+
+ datastore_write_fn = _Mutate.DatastoreWriteFn(self._PROJECT)
+
+ datastore_write_fn.start_bundle()
+ for mutation in expected_mutations:
+ datastore_write_fn.process(mutation)
+ datastore_write_fn.finish_bundle()
+
+ self.assertEqual(actual_mutations, expected_mutations)
+ self.assertEqual((num_entities - 1) / _Mutate._WRITE_BATCH_SIZE + 1,
+ self._mock_datastore.commit.call_count)
+
+ def verify_unique_keys(self, queries):
+ """A helper function that verifies if all the queries have unique keys."""
+ keys, _ = zip(*queries)
+ keys = set(keys)
+ self.assertEqual(len(keys), len(queries))
+
+ def check_estimated_size_bytes(self, entity_bytes, timestamp, namespace=None):
+ """A helper method to test get_estimated_size_bytes"""
+
+ timestamp_req = helper.make_request(
+ self._PROJECT, namespace, helper.make_latest_timestamp_query(namespace))
+ timestamp_resp = self.make_stats_response(
+ {'timestamp': datastore_helper.from_timestamp(timestamp)})
+ kind_stat_req = helper.make_request(
+ self._PROJECT, namespace, helper.make_kind_stats_query(
+ namespace, self._query.kind[0].name,
+ datastore_helper.micros_from_timestamp(timestamp)))
+ kind_stat_resp = self.make_stats_response(
+ {'entity_bytes': entity_bytes})
+
+ def fake_run_query(req):
+ if req == timestamp_req:
+ return timestamp_resp
+ elif req == kind_stat_req:
+ return kind_stat_resp
+ else:
+ print kind_stat_req
+ raise ValueError("Unknown req: %s" % req)
+
+ self._mock_datastore.run_query.side_effect = fake_run_query
+ self.assertEqual(entity_bytes, ReadFromDatastore.get_estimated_size_bytes(
+ self._PROJECT, namespace, self._query, self._mock_datastore))
+ self.assertEqual(self._mock_datastore.run_query.call_args_list,
+ [call(timestamp_req), call(kind_stat_req)])
+
+ def make_stats_response(self, property_map):
+ resp = datastore_pb2.RunQueryResponse()
+ entity_result = resp.batch.entity_results.add()
+ datastore_helper.add_properties(entity_result.entity, property_map)
+ return resp
+
+ def split_query(self, query, num_splits):
+ """Generate dummy query splits."""
+ split_queries = []
+ for _ in range(0, num_splits):
+ q = query_pb2.Query()
+ q.CopyFrom(query)
+ split_queries.append(q)
+ return split_queries
+
+if __name__ == '__main__':
+ unittest.main()
http://git-wip-us.apache.org/repos/asf/beam/blob/908c8532/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/fake_datastore.py
----------------------------------------------------------------------
diff --git a/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/fake_datastore.py b/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/fake_datastore.py
new file mode 100644
index 0000000..ac8e0e0
--- /dev/null
+++ b/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/fake_datastore.py
@@ -0,0 +1,92 @@
+#
+# 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.
+#
+
+"""Fake datastore used for unit testing."""
+import uuid
+
+from google.cloud.proto.datastore.v1 import datastore_pb2
+from google.cloud.proto.datastore.v1 import query_pb2
+
+
+def create_run_query(entities, batch_size):
+ """A fake datastore run_query method that returns entities in batches.
+
+ Note: the outer method is needed to make the `entities` and `batch_size`
+ available in the scope of fake_run_query method.
+
+ Args:
+ entities: list of entities supposed to be contained in the datastore.
+ batch_size: the number of entities that run_query method returns in one
+ request.
+ """
+ def run_query(req):
+ start = int(req.query.start_cursor) if req.query.start_cursor else 0
+ # if query limit is less than batch_size, then only return that much.
+ count = min(batch_size, req.query.limit.value)
+ # cannot go more than the number of entities contained in datastore.
+ end = min(len(entities), start + count)
+ finish = False
+ # Finish reading when there are no more entities to return,
+ # or request query limit has been satisfied.
+ if end == len(entities) or count == req.query.limit.value:
+ finish = True
+ return create_response(entities[start:end], str(end), finish)
+ return run_query
+
+
+def create_commit(mutations):
+ """A fake Datastore commit method that writes the mutations to a list.
+
+ Args:
+ mutations: A list to write mutations to.
+
+ Returns:
+ A fake Datastore commit method
+ """
+
+ def commit(req):
+ for mutation in req.mutations:
+ mutations.append(mutation)
+
+ return commit
+
+
+def create_response(entities, end_cursor, finish):
+ """Creates a query response for a given batch of scatter entities."""
+ resp = datastore_pb2.RunQueryResponse()
+ if finish:
+ resp.batch.more_results = query_pb2.QueryResultBatch.NO_MORE_RESULTS
+ else:
+ resp.batch.more_results = query_pb2.QueryResultBatch.NOT_FINISHED
+
+ resp.batch.end_cursor = end_cursor
+ for entity_result in entities:
+ resp.batch.entity_results.add().CopyFrom(entity_result)
+
+ return resp
+
+
+def create_entities(count):
+ """Creates a list of entities with random keys."""
+ entities = []
+
+ for _ in range(count):
+ entity_result = query_pb2.EntityResult()
+ entity_result.entity.key.path.add().name = str(uuid.uuid4())
+ entities.append(entity_result)
+
+ return entities
http://git-wip-us.apache.org/repos/asf/beam/blob/908c8532/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/helper.py
----------------------------------------------------------------------
diff --git a/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/helper.py b/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/helper.py
new file mode 100644
index 0000000..1497862
--- /dev/null
+++ b/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/helper.py
@@ -0,0 +1,267 @@
+#
+# 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.
+#
+
+"""Cloud Datastore helper functions."""
+import sys
+
+from google.cloud.proto.datastore.v1 import datastore_pb2
+from google.cloud.proto.datastore.v1 import entity_pb2
+from google.cloud.proto.datastore.v1 import query_pb2
+from googledatastore import PropertyFilter, CompositeFilter
+from googledatastore import helper as datastore_helper
+from googledatastore.connection import Datastore
+from googledatastore.connection import RPCError
+
+from apache_beam.internal import auth
+from apache_beam.utils import retry
+
+
+def key_comparator(k1, k2):
+ """A comparator for Datastore keys.
+
+ Comparison is only valid for keys in the same partition. The comparison here
+ is between the list of paths for each key.
+ """
+
+ if k1.partition_id != k2.partition_id:
+ raise ValueError('Cannot compare keys with different partition ids.')
+
+ k2_iter = iter(k2.path)
+
+ for k1_path in k1.path:
+ k2_path = next(k2_iter, None)
+ if not k2_path:
+ return 1
+
+ result = compare_path(k1_path, k2_path)
+
+ if result != 0:
+ return result
+
+ k2_path = next(k2_iter, None)
+ if k2_path:
+ return -1
+ else:
+ return 0
+
+
+def compare_path(p1, p2):
+ """A comparator for key path.
+
+ A path has either an `id` or a `name` field defined. The
+ comparison works with the following rules:
+
+ 1. If one path has `id` defined while the other doesn't, then the
+ one with `id` defined is considered smaller.
+ 2. If both paths have `id` defined, then their ids are compared.
+ 3. If no `id` is defined for both paths, then their `names` are compared.
+ """
+
+ result = str_compare(p1.kind, p2.kind)
+ if result != 0:
+ return result
+
+ if p1.HasField('id'):
+ if not p2.HasField('id'):
+ return -1
+
+ return p1.id - p2.id
+
+ if p2.HasField('id'):
+ return 1
+
+ return str_compare(p1.name, p2.name)
+
+
+def str_compare(s1, s2):
+ if s1 == s2:
+ return 0
+ elif s1 < s2:
+ return -1
+ else:
+ return 1
+
+
+def get_datastore(project):
+ """Returns a Cloud Datastore client."""
+ credentials = auth.get_service_credentials()
+ return Datastore(project, credentials)
+
+
+def make_request(project, namespace, query):
+ """Make a Cloud Datastore request for the given query."""
+ req = datastore_pb2.RunQueryRequest()
+ req.partition_id.CopyFrom(make_partition(project, namespace))
+
+ req.query.CopyFrom(query)
+ return req
+
+
+def make_partition(project, namespace):
+ """Make a PartitionId for the given project and namespace."""
+ partition = entity_pb2.PartitionId()
+ partition.project_id = project
+ if namespace is not None:
+ partition.namespace_id = namespace
+
+ return partition
+
+
+def retry_on_rpc_error(exception):
+ """A retry filter for Cloud Datastore RPCErrors."""
+ if isinstance(exception, RPCError):
+ if exception.code >= 500:
+ return True
+ else:
+ return False
+ else:
+ # TODO(vikasrk): Figure out what other errors should be retried.
+ return False
+
+
+def fetch_entities(project, namespace, query, datastore):
+ """A helper method to fetch entities from Cloud Datastore.
+
+ Args:
+ project: Project ID
+ namespace: Cloud Datastore namespace
+ query: Query to be read from
+ datastore: Cloud Datastore Client
+
+ Returns:
+ An iterator of entities.
+ """
+ return QueryIterator(project, namespace, query, datastore)
+
+
+def is_key_valid(key):
+ """Returns True if a Cloud Datastore key is complete.
+
+ A key is complete if its last element has either an id or a name.
+ """
+ if not key.path:
+ return False
+ return key.path[-1].HasField('id') or key.path[-1].HasField('name')
+
+
+def write_mutations(datastore, project, mutations):
+ """A helper function to write a batch of mutations to Cloud Datastore.
+
+ If a commit fails, it will be retried upto 5 times. All mutations in the
+ batch will be committed again, even if the commit was partially successful.
+ If the retry limit is exceeded, the last exception from Cloud Datastore will
+ be raised.
+ """
+ commit_request = datastore_pb2.CommitRequest()
+ commit_request.mode = datastore_pb2.CommitRequest.NON_TRANSACTIONAL
+ commit_request.project_id = project
+ for mutation in mutations:
+ commit_request.mutations.add().CopyFrom(mutation)
+
+ @retry.with_exponential_backoff(num_retries=5,
+ retry_filter=retry_on_rpc_error)
+ def commit(req):
+ datastore.commit(req)
+
+ commit(commit_request)
+
+
+def make_latest_timestamp_query(namespace):
+ """Make a Query to fetch the latest timestamp statistics."""
+ query = query_pb2.Query()
+ if namespace is None:
+ query.kind.add().name = '__Stat_Total__'
+ else:
+ query.kind.add().name = '__Stat_Ns_Total__'
+
+ # Descending order of `timestamp`
+ datastore_helper.add_property_orders(query, "-timestamp")
+ # Only get the latest entity
+ query.limit.value = 1
+ return query
+
+
+def make_kind_stats_query(namespace, kind, latest_timestamp):
+ """Make a Query to fetch the latest kind statistics."""
+ kind_stat_query = query_pb2.Query()
+ if namespace is None:
+ kind_stat_query.kind.add().name = '__Stat_Kind__'
+ else:
+ kind_stat_query.kind.add().name = '__Stat_Ns_Kind__'
+
+ kind_filter = datastore_helper.set_property_filter(
+ query_pb2.Filter(), 'kind_name', PropertyFilter.EQUAL, unicode(kind))
+ timestamp_filter = datastore_helper.set_property_filter(
+ query_pb2.Filter(), 'timestamp', PropertyFilter.EQUAL,
+ latest_timestamp)
+
+ datastore_helper.set_composite_filter(kind_stat_query.filter,
+ CompositeFilter.AND, kind_filter,
+ timestamp_filter)
+ return kind_stat_query
+
+
+class QueryIterator(object):
+ """A iterator class for entities of a given query.
+
+ Entities are read in batches. Retries on failures.
+ """
+ _NOT_FINISHED = query_pb2.QueryResultBatch.NOT_FINISHED
+ # Maximum number of results to request per query.
+ _BATCH_SIZE = 500
+
+ def __init__(self, project, namespace, query, datastore):
+ self._query = query
+ self._datastore = datastore
+ self._project = project
+ self._namespace = namespace
+ self._start_cursor = None
+ self._limit = self._query.limit.value or sys.maxint
+ self._req = make_request(project, namespace, query)
+
+ @retry.with_exponential_backoff(num_retries=5,
+ retry_filter=retry_on_rpc_error)
+ def _next_batch(self):
+ """Fetches the next batch of entities."""
+ if self._start_cursor is not None:
+ self._req.query.start_cursor = self._start_cursor
+
+ # set batch size
+ self._req.query.limit.value = min(self._BATCH_SIZE, self._limit)
+ resp = self._datastore.run_query(self._req)
+ return resp
+
+ def __iter__(self):
+ more_results = True
+ while more_results:
+ resp = self._next_batch()
+ for entity_result in resp.batch.entity_results:
+ yield entity_result.entity
+
+ self._start_cursor = resp.batch.end_cursor
+ num_results = len(resp.batch.entity_results)
+ self._limit -= num_results
+
+ # Check if we need to read more entities.
+ # True when query limit hasn't been satisfied and there are more entities
+ # to be read. The latter is true if the response has a status
+ # `NOT_FINISHED` or if the number of results read in the previous batch
+ # is equal to `_BATCH_SIZE` (all indications that there is more data be
+ # read).
+ more_results = ((self._limit > 0) and
+ ((num_results == self._BATCH_SIZE) or
+ (resp.batch.more_results == self._NOT_FINISHED)))
http://git-wip-us.apache.org/repos/asf/beam/blob/908c8532/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/helper_test.py
----------------------------------------------------------------------
diff --git a/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/helper_test.py b/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/helper_test.py
new file mode 100644
index 0000000..689c462
--- /dev/null
+++ b/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/helper_test.py
@@ -0,0 +1,256 @@
+#
+# 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.
+#
+
+"""Tests for datastore helper."""
+import sys
+import unittest
+
+from google.cloud.proto.datastore.v1 import datastore_pb2
+from google.cloud.proto.datastore.v1 import entity_pb2
+from google.cloud.proto.datastore.v1 import query_pb2
+from google.cloud.proto.datastore.v1.entity_pb2 import Key
+from googledatastore.connection import RPCError
+from googledatastore import helper as datastore_helper
+from mock import MagicMock
+
+from apache_beam.io.google_cloud_platform.datastore.v1 import fake_datastore
+from apache_beam.io.google_cloud_platform.datastore.v1 import helper
+from apache_beam.tests.test_utils import patch_retry
+
+
+class HelperTest(unittest.TestCase):
+
+ def setUp(self):
+ self._mock_datastore = MagicMock()
+ self._query = query_pb2.Query()
+ self._query.kind.add().name = 'dummy_kind'
+ patch_retry(self, helper)
+
+ def permanent_datastore_failure(self, req):
+ raise RPCError("dummy", 500, "failed")
+
+ def transient_datastore_failure(self, req):
+ if self._transient_fail_count:
+ self._transient_fail_count -= 1
+ raise RPCError("dummy", 500, "failed")
+ else:
+ return datastore_pb2.RunQueryResponse()
+
+ def test_query_iterator(self):
+ self._mock_datastore.run_query.side_effect = (
+ self.permanent_datastore_failure)
+ query_iterator = helper.QueryIterator("project", None, self._query,
+ self._mock_datastore)
+ self.assertRaises(RPCError, iter(query_iterator).next)
+ self.assertEqual(6, len(self._mock_datastore.run_query.call_args_list))
+
+ def test_query_iterator_with_transient_failures(self):
+ self._mock_datastore.run_query.side_effect = (
+ self.transient_datastore_failure)
+ query_iterator = helper.QueryIterator("project", None, self._query,
+ self._mock_datastore)
+ fail_count = 2
+ self._transient_fail_count = fail_count
+ for _ in query_iterator:
+ pass
+
+ self.assertEqual(fail_count + 1,
+ len(self._mock_datastore.run_query.call_args_list))
+
+ def test_query_iterator_with_single_batch(self):
+ num_entities = 100
+ batch_size = 500
+ self.check_query_iterator(num_entities, batch_size, self._query)
+
+ def test_query_iterator_with_multiple_batches(self):
+ num_entities = 1098
+ batch_size = 500
+ self.check_query_iterator(num_entities, batch_size, self._query)
+
+ def test_query_iterator_with_exact_batch_multiple(self):
+ num_entities = 1000
+ batch_size = 500
+ self.check_query_iterator(num_entities, batch_size, self._query)
+
+ def test_query_iterator_with_query_limit(self):
+ num_entities = 1098
+ batch_size = 500
+ self._query.limit.value = 1004
+ self.check_query_iterator(num_entities, batch_size, self._query)
+
+ def test_query_iterator_with_large_query_limit(self):
+ num_entities = 1098
+ batch_size = 500
+ self._query.limit.value = 10000
+ self.check_query_iterator(num_entities, batch_size, self._query)
+
+ def check_query_iterator(self, num_entities, batch_size, query):
+ """A helper method to test the QueryIterator.
+
+ Args:
+ num_entities: number of entities contained in the fake datastore.
+ batch_size: the number of entities returned by fake datastore in one req.
+ query: the query to be executed
+
+ """
+ entities = fake_datastore.create_entities(num_entities)
+ self._mock_datastore.run_query.side_effect = \
+ fake_datastore.create_run_query(entities, batch_size)
+ query_iterator = helper.QueryIterator("project", None, self._query,
+ self._mock_datastore)
+
+ i = 0
+ for entity in query_iterator:
+ self.assertEqual(entity, entities[i].entity)
+ i += 1
+
+ limit = query.limit.value if query.HasField('limit') else sys.maxint
+ self.assertEqual(i, min(num_entities, limit))
+
+ def test_is_key_valid(self):
+ key = entity_pb2.Key()
+ # Complete with name, no ancestor
+ datastore_helper.add_key_path(key, 'kind', 'name')
+ self.assertTrue(helper.is_key_valid(key))
+
+ key = entity_pb2.Key()
+ # Complete with id, no ancestor
+ datastore_helper.add_key_path(key, 'kind', 12)
+ self.assertTrue(helper.is_key_valid(key))
+
+ key = entity_pb2.Key()
+ # Incomplete, no ancestor
+ datastore_helper.add_key_path(key, 'kind')
+ self.assertFalse(helper.is_key_valid(key))
+
+ key = entity_pb2.Key()
+ # Complete with name and ancestor
+ datastore_helper.add_key_path(key, 'kind', 'name', 'kind2', 'name2')
+ self.assertTrue(helper.is_key_valid(key))
+
+ key = entity_pb2.Key()
+ # Complete with id and ancestor
+ datastore_helper.add_key_path(key, 'kind', 'name', 'kind2', 123)
+ self.assertTrue(helper.is_key_valid(key))
+
+ key = entity_pb2.Key()
+ # Incomplete with ancestor
+ datastore_helper.add_key_path(key, 'kind', 'name', 'kind2')
+ self.assertFalse(helper.is_key_valid(key))
+
+ key = entity_pb2.Key()
+ self.assertFalse(helper.is_key_valid(key))
+
+ def test_compare_path_with_different_kind(self):
+ p1 = Key.PathElement()
+ p1.kind = 'dummy1'
+
+ p2 = Key.PathElement()
+ p2.kind = 'dummy2'
+
+ self.assertLess(helper.compare_path(p1, p2), 0)
+
+ def test_compare_path_with_different_id(self):
+ p1 = Key.PathElement()
+ p1.kind = 'dummy'
+ p1.id = 10
+
+ p2 = Key.PathElement()
+ p2.kind = 'dummy'
+ p2.id = 15
+
+ self.assertLess(helper.compare_path(p1, p2), 0)
+
+ def test_compare_path_with_different_name(self):
+ p1 = Key.PathElement()
+ p1.kind = 'dummy'
+ p1.name = "dummy1"
+
+ p2 = Key.PathElement()
+ p2.kind = 'dummy'
+ p2.name = 'dummy2'
+
+ self.assertLess(helper.compare_path(p1, p2), 0)
+
+ def test_compare_path_of_different_type(self):
+ p1 = Key.PathElement()
+ p1.kind = 'dummy'
+ p1.id = 10
+
+ p2 = Key.PathElement()
+ p2.kind = 'dummy'
+ p2.name = 'dummy'
+
+ self.assertLess(helper.compare_path(p1, p2), 0)
+
+ def test_key_comparator_with_different_partition(self):
+ k1 = Key()
+ k1.partition_id.namespace_id = 'dummy1'
+ k2 = Key()
+ k2.partition_id.namespace_id = 'dummy2'
+ self.assertRaises(ValueError, helper.key_comparator, k1, k2)
+
+ def test_key_comparator_with_single_path(self):
+ k1 = Key()
+ k2 = Key()
+ p1 = k1.path.add()
+ p2 = k2.path.add()
+ p1.kind = p2.kind = 'dummy'
+ self.assertEqual(helper.key_comparator(k1, k2), 0)
+
+ def test_key_comparator_with_multiple_paths_1(self):
+ k1 = Key()
+ k2 = Key()
+ p11 = k1.path.add()
+ p12 = k1.path.add()
+ p21 = k2.path.add()
+ p11.kind = p12.kind = p21.kind = 'dummy'
+ self.assertGreater(helper.key_comparator(k1, k2), 0)
+
+ def test_key_comparator_with_multiple_paths_2(self):
+ k1 = Key()
+ k2 = Key()
+ p11 = k1.path.add()
+ p21 = k2.path.add()
+ p22 = k2.path.add()
+ p11.kind = p21.kind = p22.kind = 'dummy'
+ self.assertLess(helper.key_comparator(k1, k2), 0)
+
+ def test_key_comparator_with_multiple_paths_3(self):
+ k1 = Key()
+ k2 = Key()
+ p11 = k1.path.add()
+ p12 = k1.path.add()
+ p21 = k2.path.add()
+ p22 = k2.path.add()
+ p11.kind = p12.kind = p21.kind = p22.kind = 'dummy'
+ self.assertEqual(helper.key_comparator(k1, k2), 0)
+
+ def test_key_comparator_with_multiple_paths_4(self):
+ k1 = Key()
+ k2 = Key()
+ p11 = k1.path.add()
+ p12 = k2.path.add()
+ p21 = k2.path.add()
+ p11.kind = p12.kind = 'dummy'
+ # make path2 greater than path1
+ p21.kind = 'dummy1'
+ self.assertLess(helper.key_comparator(k1, k2), 0)
+
+
+if __name__ == '__main__':
+ unittest.main()
http://git-wip-us.apache.org/repos/asf/beam/blob/908c8532/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/query_splitter.py
----------------------------------------------------------------------
diff --git a/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/query_splitter.py b/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/query_splitter.py
new file mode 100644
index 0000000..b101ad9
--- /dev/null
+++ b/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/query_splitter.py
@@ -0,0 +1,269 @@
+#
+# 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.
+#
+
+"""Implements a Cloud Datastore query splitter."""
+
+from apache_beam.io.google_cloud_platform.datastore.v1 import helper
+from google.cloud.proto.datastore.v1 import datastore_pb2
+from google.cloud.proto.datastore.v1 import query_pb2
+from google.cloud.proto.datastore.v1.query_pb2 import PropertyFilter
+from google.cloud.proto.datastore.v1.query_pb2 import CompositeFilter
+from googledatastore import helper as datastore_helper
+
+
+__all__ = [
+ 'get_splits',
+]
+
+SCATTER_PROPERTY_NAME = '__scatter__'
+KEY_PROPERTY_NAME = '__key__'
+# The number of keys to sample for each split.
+KEYS_PER_SPLIT = 32
+
+UNSUPPORTED_OPERATORS = [PropertyFilter.LESS_THAN,
+ PropertyFilter.LESS_THAN_OR_EQUAL,
+ PropertyFilter.GREATER_THAN,
+ PropertyFilter.GREATER_THAN_OR_EQUAL]
+
+
+def get_splits(datastore, query, num_splits, partition=None):
+ """Returns a list of sharded queries for the given Cloud Datastore query.
+
+ This will create up to the desired number of splits, however it may return
+ less splits if the desired number of splits is unavailable. This will happen
+ if the number of split points provided by the underlying Datastore is less
+ than the desired number, which will occur if the number of results for the
+ query is too small.
+
+ This implementation of the QuerySplitter uses the __scatter__ property to
+ gather random split points for a query.
+
+ Note: This implementation is derived from the java query splitter in
+ https://github.com/GoogleCloudPlatform/google-cloud-datastore/blob/master/java/datastore/src/main/java/com/google/datastore/v1/client/QuerySplitterImpl.java
+
+ Args:
+ datastore: the datastore client.
+ query: the query to split.
+ num_splits: the desired number of splits.
+ partition: the partition the query is running in.
+
+ Returns:
+ A list of split queries, of a max length of `num_splits`
+ """
+
+ # Validate that the number of splits is not out of bounds.
+ if num_splits < 1:
+ raise ValueError('The number of splits must be greater than 0.')
+
+ if num_splits == 1:
+ return [query]
+
+ _validate_query(query)
+
+ splits = []
+ scatter_keys = _get_scatter_keys(datastore, query, num_splits, partition)
+ last_key = None
+ for next_key in _get_split_key(scatter_keys, num_splits):
+ splits.append(_create_split(last_key, next_key, query))
+ last_key = next_key
+
+ splits.append(_create_split(last_key, None, query))
+ return splits
+
+
+def _validate_query(query):
+ """ Verifies that the given query can be properly scattered."""
+
+ if len(query.kind) != 1:
+ raise ValueError('Query must have exactly one kind.')
+
+ if len(query.order) != 0:
+ raise ValueError('Query cannot have any sort orders.')
+
+ if query.HasField('limit'):
+ raise ValueError('Query cannot have a limit set.')
+
+ if query.offset > 0:
+ raise ValueError('Query cannot have an offset set.')
+
+ _validate_filter(query.filter)
+
+
+def _validate_filter(filter):
+ """Validates that we only have allowable filters.
+
+ Note that equality and ancestor filters are allowed, however they may result
+ in inefficient sharding.
+ """
+
+ if filter.HasField('composite_filter'):
+ for sub_filter in filter.composite_filter.filters:
+ _validate_filter(sub_filter)
+ elif filter.HasField('property_filter'):
+ if filter.property_filter.op in UNSUPPORTED_OPERATORS:
+ raise ValueError('Query cannot have any inequality filters.')
+ else:
+ pass
+
+
+def _create_scatter_query(query, num_splits):
+ """Creates a scatter query from the given user query."""
+
+ scatter_query = query_pb2.Query()
+ for kind in query.kind:
+ scatter_kind = scatter_query.kind.add()
+ scatter_kind.CopyFrom(kind)
+
+ # ascending order
+ datastore_helper.add_property_orders(scatter_query, SCATTER_PROPERTY_NAME)
+
+ # There is a split containing entities before and after each scatter entity:
+ # ||---*------*------*------*------*------*------*---|| * = scatter entity
+ # If we represent each split as a region before a scatter entity, there is an
+ # extra region following the last scatter point. Thus, we do not need the
+ # scatter entity for the last region.
+ scatter_query.limit.value = (num_splits - 1) * KEYS_PER_SPLIT
+ datastore_helper.add_projection(scatter_query, KEY_PROPERTY_NAME)
+
+ return scatter_query
+
+
+def _get_scatter_keys(datastore, query, num_splits, partition):
+ """Gets a list of split keys given a desired number of splits.
+
+ This list will contain multiple split keys for each split. Only a single split
+ key will be chosen as the split point, however providing multiple keys allows
+ for more uniform sharding.
+
+ Args:
+ numSplits: the number of desired splits.
+ query: the user query.
+ partition: the partition to run the query in.
+ datastore: the client to datastore containing the data.
+
+ Returns:
+ A list of scatter keys returned by Datastore.
+ """
+ scatter_point_query = _create_scatter_query(query, num_splits)
+
+ key_splits = []
+ while True:
+ req = datastore_pb2.RunQueryRequest()
+ if partition:
+ req.partition_id.CopyFrom(partition)
+
+ req.query.CopyFrom(scatter_point_query)
+
+ resp = datastore.run_query(req)
+ for entity_result in resp.batch.entity_results:
+ key_splits.append(entity_result.entity.key)
+
+ if resp.batch.more_results != query_pb2.QueryResultBatch.NOT_FINISHED:
+ break
+
+ scatter_point_query.start_cursor = resp.batch.end_cursor
+ scatter_point_query.limit.value -= len(resp.batch.entity_results)
+
+ key_splits.sort(helper.key_comparator)
+ return key_splits
+
+
+def _get_split_key(keys, num_splits):
+ """Given a list of keys and a number of splits find the keys to split on.
+
+ Args:
+ keys: the list of keys.
+ num_splits: the number of splits.
+
+ Returns:
+ A list of keys to split on.
+
+ """
+
+ # If the number of keys is less than the number of splits, we are limited
+ # in the number of splits we can make.
+ if not keys or (len(keys) < (num_splits - 1)):
+ return keys
+
+ # Calculate the number of keys per split. This should be KEYS_PER_SPLIT,
+ # but may be less if there are not KEYS_PER_SPLIT * (numSplits - 1) scatter
+ # entities.
+ #
+ # Consider the following dataset, where - represents an entity and
+ # * represents an entity that is returned as a scatter entity:
+ # ||---*-----*----*-----*-----*------*----*----||
+ # If we want 4 splits in this data, the optimal split would look like:
+ # ||---*-----*----*-----*-----*------*----*----||
+ # | | |
+ # The scatter keys in the last region are not useful to us, so we never
+ # request them:
+ # ||---*-----*----*-----*-----*------*---------||
+ # | | |
+ # With 6 scatter keys we want to set scatter points at indexes: 1, 3, 5.
+ #
+ # We keep this as a float so that any "fractional" keys per split get
+ # distributed throughout the splits and don't make the last split
+ # significantly larger than the rest.
+
+ num_keys_per_split = max(1.0, float(len(keys)) / (num_splits - 1))
+
+ split_keys = []
+
+ # Grab the last sample for each split, otherwise the first split will be too
+ # small.
+ for i in range(1, num_splits):
+ split_index = int(round(i * num_keys_per_split) - 1)
+ split_keys.append(keys[split_index])
+
+ return split_keys
+
+
+def _create_split(last_key, next_key, query):
+ """Create a new {@link Query} given the query and range..
+
+ Args:
+ last_key: the previous key. If null then assumed to be the beginning.
+ next_key: the next key. If null then assumed to be the end.
+ query: the desired query.
+
+ Returns:
+ A split query with fetches entities in the range [last_key, next_key)
+ """
+ if not (last_key or next_key):
+ return query
+
+ split_query = query_pb2.Query()
+ split_query.CopyFrom(query)
+ composite_filter = split_query.filter.composite_filter
+ composite_filter.op = CompositeFilter.AND
+
+ if query.HasField('filter'):
+ composite_filter.filters.add().CopyFrom(query.filter)
+
+ if last_key:
+ lower_bound = composite_filter.filters.add()
+ lower_bound.property_filter.property.name = KEY_PROPERTY_NAME
+ lower_bound.property_filter.op = PropertyFilter.GREATER_THAN_OR_EQUAL
+ lower_bound.property_filter.value.key_value.CopyFrom(last_key)
+
+ if next_key:
+ upper_bound = composite_filter.filters.add()
+ upper_bound.property_filter.property.name = KEY_PROPERTY_NAME
+ upper_bound.property_filter.op = PropertyFilter.LESS_THAN
+ upper_bound.property_filter.value.key_value.CopyFrom(next_key)
+
+ return split_query
http://git-wip-us.apache.org/repos/asf/beam/blob/908c8532/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/query_splitter_test.py
----------------------------------------------------------------------
diff --git a/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/query_splitter_test.py b/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/query_splitter_test.py
new file mode 100644
index 0000000..676f311
--- /dev/null
+++ b/sdks/python/apache_beam/io/google_cloud_platform/datastore/v1/query_splitter_test.py
@@ -0,0 +1,201 @@
+#
+# 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.
+#
+
+"""Cloud Datastore query splitter test."""
+
+import unittest
+
+from mock import MagicMock
+from mock import call
+
+from apache_beam.io.google_cloud_platform.datastore.v1 import fake_datastore
+from apache_beam.io.google_cloud_platform.datastore.v1 import query_splitter
+
+from google.cloud.proto.datastore.v1 import datastore_pb2
+from google.cloud.proto.datastore.v1 import query_pb2
+from google.cloud.proto.datastore.v1.query_pb2 import PropertyFilter
+
+
+class QuerySplitterTest(unittest.TestCase):
+
+ def test_get_splits_query_with_multiple_kinds(self):
+ query = query_pb2.Query()
+ query.kind.add()
+ query.kind.add()
+ self.assertRaises(ValueError, query_splitter.get_splits, None, query, 4)
+
+ def test_get_splits_query_with_order(self):
+ query = query_pb2.Query()
+ query.kind.add()
+ query.order.add()
+
+ self.assertRaises(ValueError, query_splitter.get_splits, None, query, 3)
+
+ def test_get_splits_query_with_unsupported_filter(self):
+ query = query_pb2.Query()
+ query.kind.add()
+ test_filter = query.filter.composite_filter.filters.add()
+ test_filter.property_filter.op = PropertyFilter.GREATER_THAN
+ self.assertRaises(ValueError, query_splitter.get_splits, None, query, 2)
+
+ def test_get_splits_query_with_limit(self):
+ query = query_pb2.Query()
+ query.kind.add()
+ query.limit.value = 10
+ self.assertRaises(ValueError, query_splitter.get_splits, None, query, 2)
+
+ def test_get_splits_query_with_offset(self):
+ query = query_pb2.Query()
+ query.kind.add()
+ query.offset = 10
+ self.assertRaises(ValueError, query_splitter.get_splits, None, query, 2)
+
+ def test_create_scatter_query(self):
+ query = query_pb2.Query()
+ kind = query.kind.add()
+ kind.name = 'shakespeare-demo'
+ num_splits = 10
+ scatter_query = query_splitter._create_scatter_query(query, num_splits)
+ self.assertEqual(scatter_query.kind[0], kind)
+ self.assertEqual(scatter_query.limit.value,
+ (num_splits -1) * query_splitter.KEYS_PER_SPLIT)
+ self.assertEqual(scatter_query.order[0].direction,
+ query_pb2.PropertyOrder.ASCENDING)
+ self.assertEqual(scatter_query.projection[0].property.name,
+ query_splitter.KEY_PROPERTY_NAME)
+
+ def test_get_splits_with_two_splits(self):
+ query = query_pb2.Query()
+ kind = query.kind.add()
+ kind.name = 'shakespeare-demo'
+ num_splits = 2
+ num_entities = 97
+ batch_size = 9
+
+ self.check_get_splits(query, num_splits, num_entities, batch_size)
+
+ def test_get_splits_with_multiple_splits(self):
+ query = query_pb2.Query()
+ kind = query.kind.add()
+ kind.name = 'shakespeare-demo'
+ num_splits = 4
+ num_entities = 369
+ batch_size = 12
+
+ self.check_get_splits(query, num_splits, num_entities, batch_size)
+
+ def test_get_splits_with_large_num_splits(self):
+ query = query_pb2.Query()
+ kind = query.kind.add()
+ kind.name = 'shakespeare-demo'
+ num_splits = 10
+ num_entities = 4
+ batch_size = 10
+
+ self.check_get_splits(query, num_splits, num_entities, batch_size)
+
+ def test_get_splits_with_small_num_entities(self):
+ query = query_pb2.Query()
+ kind = query.kind.add()
+ kind.name = 'shakespeare-demo'
+ num_splits = 4
+ num_entities = 50
+ batch_size = 10
+
+ self.check_get_splits(query, num_splits, num_entities, batch_size)
+
+ def test_get_splits_with_batch_size_exact_multiple(self):
+ """Test get_splits when num scatter keys is a multiple of batch size."""
+ query = query_pb2.Query()
+ kind = query.kind.add()
+ kind.name = 'shakespeare-demo'
+ num_splits = 4
+ num_entities = 400
+ batch_size = 32
+
+ self.check_get_splits(query, num_splits, num_entities, batch_size)
+
+ def test_get_splits_with_large_batch_size(self):
+ """Test get_splits when all scatter keys are retured in a single req."""
+ query = query_pb2.Query()
+ kind = query.kind.add()
+ kind.name = 'shakespeare-demo'
+ num_splits = 4
+ num_entities = 400
+ batch_size = 500
+
+ self.check_get_splits(query, num_splits, num_entities, batch_size)
+
+ def check_get_splits(self, query, num_splits, num_entities, batch_size):
+ """A helper method to test the query_splitter get_splits method.
+
+ Args:
+ query: the query to be split
+ num_splits: number of splits
+ num_entities: number of scatter entities contained in the fake datastore.
+ batch_size: the number of entities returned by fake datastore in one req.
+ """
+
+ entities = fake_datastore.create_entities(num_entities)
+ mock_datastore = MagicMock()
+ # Assign a fake run_query method as a side_effect to the mock.
+ mock_datastore.run_query.side_effect = \
+ fake_datastore.create_run_query(entities, batch_size)
+
+ split_queries = query_splitter.get_splits(mock_datastore, query, num_splits)
+
+ # if request num_splits is greater than num_entities, the best it can
+ # do is one entity per split.
+ expected_num_splits = min(num_splits, num_entities + 1)
+ self.assertEqual(len(split_queries), expected_num_splits)
+
+ expected_requests = QuerySplitterTest.create_scatter_requests(
+ query, num_splits, batch_size, num_entities)
+
+ expected_calls = []
+ for req in expected_requests:
+ expected_calls.append(call(req))
+
+ self.assertEqual(expected_calls, mock_datastore.run_query.call_args_list)
+
+ @staticmethod
+ def create_scatter_requests(query, num_splits, batch_size, num_entities):
+ """Creates a list of expected scatter requests from the query splitter.
+
+ This list of requests returned is used to verify that the query splitter
+ made the same number of requests in the same order to datastore.
+ """
+
+ requests = []
+ count = (num_splits - 1) * query_splitter.KEYS_PER_SPLIT
+ start_cursor = ''
+ i = 0
+ scatter_query = query_splitter._create_scatter_query(query, count)
+ while i < count and i < num_entities:
+ request = datastore_pb2.RunQueryRequest()
+ request.query.CopyFrom(scatter_query)
+ request.query.start_cursor = start_cursor
+ request.query.limit.value = count - i
+ requests.append(request)
+ i += batch_size
+ start_cursor = str(i)
+
+ return requests
+
+
+if __name__ == '__main__':
+ unittest.main()