[
https://issues.apache.org/jira/browse/BEAM-2085?focusedWorklogId=582852&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-582852
]
ASF GitHub Bot logged work on BEAM-2085:
----------------------------------------
Author: ASF GitHub Bot
Created on: 14/Apr/21 20:18
Start Date: 14/Apr/21 20:18
Worklog Time Spent: 10m
Work Description: tvalentyn commented on a change in pull request #14390:
URL: https://github.com/apache/beam/pull/14390#discussion_r613559515
##########
File path: sdks/python/apache_beam/runners/dataflow/dataflow_runner_test.py
##########
@@ -863,6 +863,31 @@ def test_pack_combiners_enabled_by_experiment(self):
self._test_pack_combiners(
PipelineOptions(self.default_properties), expect_packed=True)
+ def test_resource_hints_translation(self):
+ runner = DataflowRunner()
+
+ self.default_properties.append('--experiments=use_legacy_bq_sink')
+ self.default_properties.append('--resource_hint=min_ram_per_vcpu=10GB')
+ with beam.Pipeline(runner=runner,
+ options=PipelineOptions(self.default_properties)) as p:
+ # pylint: disable=expression-not-assigned
+ (
+ p
+ | beam.Create([1])
+ | 'MapWithHints' >> beam.Map(lambda x: x + 1).with_resource_hints(
+ min_ram_per_vcpu='20GB',
+
accelerator='type:nvidia-tesla-k80;count:1;install-nvidia-drivers'
+ ))
+
+ step = self._find_step(runner.job, 'MapWithHints')
+ self.assertEqual(
+ step['properties']['resource_hints'],
+ {
+ 'beam:resources:min_ram_per_vcpu_bytes:v1': '10000000000',
Review comment:
Discussed offline, keeping as is for now.
##########
File path: sdks/python/apache_beam/runners/dataflow/dataflow_runner_test.py
##########
@@ -863,6 +863,31 @@ def test_pack_combiners_enabled_by_experiment(self):
self._test_pack_combiners(
PipelineOptions(self.default_properties), expect_packed=True)
+ def test_resource_hints_translation(self):
+ runner = DataflowRunner()
+
+ self.default_properties.append('--experiments=use_legacy_bq_sink')
+ self.default_properties.append('--resource_hint=min_ram_per_vcpu=10GB')
Review comment:
Done
##########
File path: sdks/python/apache_beam/runners/pipeline_context.py
##########
@@ -274,5 +282,44 @@ def to_runner_api(self):
return context_proto
def default_environment_id(self):
- # type: () -> Optional[str]
+ # type: () -> str
return self._default_environment_id
+
+ def get_environment_id_for_transform(
+ self, transform): # type: (Optional[ptransform.PTransform]) -> str
+ """Returns an environment id where the transform can be executed."""
+ if not transform or not transform.get_resource_hints():
+ return self.default_environment_id()
+
+ def merge_resource_hints(
+ environment_id,
+ transform): # type: (str, ptransform.PTransform) -> Dict[str, bytes]
+ # TODO: add test.
+ # Hints already defined in the environment take precedence over hints
Review comment:
Done.
##########
File path: sdks/python/apache_beam/transforms/resources.py
##########
@@ -0,0 +1,128 @@
+# 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 module for defining resource requirements for execution of transforms.
+
+Pipeline authors can use resource hints to provide additional information to
+runners about the desired aspects of the execution environment.
+
+Resource hints can be specified on a transform level for parts of the pipeline,
+or globally via --resource_hint pipeline option.
+
+See also: PTransforms.with_resource_hints().
+"""
+
+from typing import Any
+from typing import Callable
+from typing import Dict
+
+from apache_beam.portability.common_urns import resource_hints
+
+__all__ = ['parse_resource_hints', 'get_merged_hint_value']
+
+
+def _parse_str(value):
+ if not isinstance(value, str):
+ raise ValueError()
+ return value.encode('ascii')
+
+
+def _parse_int(value):
+ if isinstance(value, str):
+ value = int(value)
+ if not isinstance(value, int):
+ raise ValueError()
+ return str(value).encode('ascii')
+
+
+def _parse_any(_):
+ # For hints where only a key is relevant and value is set to None or any
value
+ return b'1'
+
+
+def _parse_storage_size_str(value): # type: (str) -> bytes
+ """Parses a human-friendly storage size string into a number of bytes.
+ """
+ if not isinstance(value, str):
+ value = str(value)
+ value = value.strip().replace(" ", "")
+ units = {
+ 'PiB': 2**50,
+ 'TiB': 2**40,
+ 'GiB': 2**30,
+ 'MiB': 2**20,
+ 'KiB': 2**10,
+ 'PB': 10**15,
+ 'TB': 10**12,
+ 'GB': 10**9,
+ 'MB': 10**6,
+ 'KB': 10**3,
+ }
+ multiplier = 1
+ for suffix in units:
+ if value.endswith(suffix):
+ multiplier = units[suffix]
+ value = value[:-len(suffix)]
+ break
+
+ return str(round(float(value) * multiplier)).encode('ascii')
+
+
+def _use_max(v1, v2):
Review comment:
Done
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Issue Time Tracking
-------------------
Worklog Id: (was: 582852)
Time Spent: 12h 20m (was: 12h 10m)
> Transforms could give hints to runners on resource requirements
> ---------------------------------------------------------------
>
> Key: BEAM-2085
> URL: https://issues.apache.org/jira/browse/BEAM-2085
> Project: Beam
> Issue Type: Improvement
> Components: beam-model, runner-core, sdk-java-core
> Affects Versions: Not applicable
> Reporter: Ismaël Mejía
> Assignee: Valentyn Tymofieiev
> Priority: P3
> Labels: Clarified
> Time Spent: 12h 20m
> Remaining Estimate: 0h
>
> As discussed in BEAM-673 runners can allocate workers to accomplish their
> work in a better way if they can take into account some hints from the
> transforms, e.g. a source can hint data locality and with this information
> the runner can allocate the workers in an better way, this can also be the
> case with a particular transform that can suggest to the runner to be
> executed in a worker with a specific resource, e.g. GPU.
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