| # |
| # 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 collections |
| import glob |
| import logging |
| import os |
| import tempfile |
| import unittest |
| |
| import apache_beam as beam |
| from apache_beam.testing.util import assert_that |
| from apache_beam.testing.util import equal_to |
| from apache_beam.utils import python_callable |
| from apache_beam.yaml import yaml_provider |
| from apache_beam.yaml.yaml_transform import YamlTransform |
| |
| |
| class CreateTimestamped(beam.PTransform): |
| _yaml_requires_inputs = False |
| |
| def __init__(self, elements): |
| self._elements = elements |
| |
| def expand(self, p): |
| return ( |
| p |
| | beam.Create(self._elements) |
| | beam.Map(lambda x: beam.transforms.window.TimestampedValue(x, x))) |
| |
| |
| class CreateInts(beam.PTransform): |
| _yaml_requires_inputs = False |
| |
| def __init__(self, elements): |
| self._elements = elements |
| |
| def expand(self, p): |
| return p | beam.Create(self._elements) |
| |
| |
| class SumGlobally(beam.PTransform): |
| def expand(self, pcoll): |
| return pcoll | beam.CombineGlobally(sum).without_defaults() |
| |
| |
| class SizeLimiter(beam.PTransform): |
| def __init__(self, limit, error_handling): |
| self._limit = limit |
| self._error_handling = error_handling |
| |
| def expand(self, pcoll): |
| def raise_on_big(row): |
| if len(row.element) > self._limit: |
| raise ValueError(row.element) |
| else: |
| return row.element |
| |
| good, bad = pcoll | beam.Map(raise_on_big).with_exception_handling() |
| return {'small_elements': good, self._error_handling['output']: bad} |
| |
| |
| TEST_PROVIDERS = { |
| 'CreateInts': CreateInts, |
| 'CreateTimestamped': CreateTimestamped, |
| 'SumGlobally': SumGlobally, |
| 'SizeLimiter': SizeLimiter, |
| 'PyMap': lambda fn: beam.Map(python_callable.PythonCallableWithSource(fn)), |
| } |
| |
| |
| class YamlTransformE2ETest(unittest.TestCase): |
| def test_composite(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| elements = p | beam.Create([1, 2, 3]) |
| # TODO(robertwb): Consider making the input implicit (and below). |
| result = elements | YamlTransform( |
| ''' |
| type: composite |
| input: |
| elements: input |
| transforms: |
| - type: PyMap |
| name: Square |
| input: elements |
| config: |
| fn: "lambda x: x * x" |
| - type: PyMap |
| name: Cube |
| input: elements |
| config: |
| fn: "lambda x: x * x * x" |
| - type: Flatten |
| input: [Square, Cube] |
| output: |
| Flatten |
| ''', |
| providers=TEST_PROVIDERS) |
| assert_that(result, equal_to([1, 4, 9, 1, 8, 27])) |
| |
| def test_chain_with_input(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| elements = p | beam.Create(range(10)) |
| result = elements | YamlTransform( |
| ''' |
| type: chain |
| input: |
| elements: input |
| transforms: |
| - type: PyMap |
| config: |
| fn: "lambda x: x * x + x" |
| - type: PyMap |
| config: |
| fn: "lambda x: x + 41" |
| ''', |
| providers=TEST_PROVIDERS) |
| assert_that(result, equal_to([41, 43, 47, 53, 61, 71, 83, 97, 113, 131])) |
| |
| def test_chain_with_source_sink(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| result = p | YamlTransform( |
| ''' |
| type: chain |
| source: |
| type: CreateInts |
| config: |
| elements: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] |
| transforms: |
| - type: PyMap |
| config: |
| fn: "lambda x: x * x + x" |
| sink: |
| type: PyMap |
| config: |
| fn: "lambda x: x + 41" |
| ''', |
| providers=TEST_PROVIDERS) |
| assert_that(result, equal_to([41, 43, 47, 53, 61, 71, 83, 97, 113, 131])) |
| |
| def test_chain_with_root(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| result = p | YamlTransform( |
| ''' |
| type: chain |
| transforms: |
| - type: CreateInts |
| config: |
| elements: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] |
| - type: PyMap |
| config: |
| fn: "lambda x: x * x + x" |
| - type: PyMap |
| config: |
| fn: "lambda x: x + 41" |
| ''', |
| providers=TEST_PROVIDERS) |
| assert_that(result, equal_to([41, 43, 47, 53, 61, 71, 83, 97, 113, 131])) |
| |
| def create_has_schema(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| result = p | YamlTransform( |
| ''' |
| type: chain |
| transforms: |
| - type: Create |
| config: |
| elements: [{a: 1, b: 'x'}, {a: 2, b: 'y'}] |
| - type: MapToFields |
| config: |
| language: python |
| fields: |
| repeated: a * b |
| ''') | beam.Map(lambda x: x.repeated) |
| assert_that(result, equal_to(['x', 'yy'])) |
| |
| def test_implicit_flatten(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| result = p | YamlTransform( |
| ''' |
| type: composite |
| transforms: |
| - type: Create |
| name: CreateSmall |
| config: |
| elements: [1, 2, 3] |
| - type: Create |
| name: CreateBig |
| config: |
| elements: [100, 200] |
| - type: PyMap |
| input: [CreateBig, CreateSmall] |
| config: |
| fn: "lambda x: x.element * x.element" |
| output: PyMap |
| ''', |
| providers=TEST_PROVIDERS) |
| assert_that(result, equal_to([1, 4, 9, 10000, 40000])) |
| |
| def test_csv_to_json(self): |
| try: |
| import pandas as pd |
| except ImportError: |
| raise unittest.SkipTest('Pandas not available.') |
| |
| with tempfile.TemporaryDirectory() as tmpdir: |
| data = pd.DataFrame([ |
| { |
| 'label': '11a', 'rank': 0 |
| }, |
| { |
| 'label': '37a', 'rank': 1 |
| }, |
| { |
| 'label': '389a', 'rank': 2 |
| }, |
| ]) |
| input = os.path.join(tmpdir, 'input.csv') |
| output = os.path.join(tmpdir, 'output.json') |
| data.to_csv(input, index=False) |
| |
| with beam.Pipeline() as p: |
| result = p | YamlTransform( |
| ''' |
| type: chain |
| transforms: |
| - type: ReadFromCsv |
| config: |
| path: %s |
| - type: WriteToJson |
| config: |
| path: %s |
| num_shards: 1 |
| ''' % (repr(input), repr(output))) |
| |
| output_shard = list(glob.glob(output + "*"))[0] |
| result = pd.read_json( |
| output_shard, orient='records', |
| lines=True).sort_values('rank').reindex() |
| pd.testing.assert_frame_equal(data, result) |
| |
| def test_name_is_not_ambiguous(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| result = p | YamlTransform( |
| ''' |
| type: composite |
| transforms: |
| - type: Create |
| name: Create |
| config: |
| elements: [0, 1, 3, 4] |
| - type: PyMap |
| name: PyMap |
| config: |
| fn: "lambda row: row.element * row.element" |
| input: Create |
| output: PyMap |
| ''', |
| providers=TEST_PROVIDERS) |
| # No exception raised |
| assert_that(result, equal_to([0, 1, 9, 16])) |
| |
| def test_name_is_ambiguous(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| # pylint: disable=expression-not-assigned |
| with self.assertRaisesRegex(ValueError, r'Ambiguous.*'): |
| p | YamlTransform( |
| ''' |
| type: composite |
| transforms: |
| - type: Create |
| name: CreateData |
| config: |
| elements: [0, 1, 3, 4] |
| - type: PyMap |
| name: PyMap |
| config: |
| fn: "lambda elem: elem + 2" |
| input: CreateData |
| - type: PyMap |
| name: AnotherMap |
| config: |
| fn: "lambda elem: elem + 3" |
| input: PyMap |
| output: AnotherMap |
| ''', |
| providers=TEST_PROVIDERS) |
| |
| def test_empty_inputs_throws_error(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| with self.assertRaisesRegex(ValueError, |
| 'Missing inputs for transform at ' |
| '"EmptyInputOkButYamlDoesntKnow" at line .*'): |
| _ = p | YamlTransform( |
| ''' |
| type: composite |
| transforms: |
| - type: PyTransform |
| name: EmptyInputOkButYamlDoesntKnow |
| config: |
| constructor: apache_beam.Impulse |
| ''') |
| |
| def test_empty_inputs_ok_in_source(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| # Does not throw an error like it does above. |
| _ = p | YamlTransform( |
| ''' |
| type: composite |
| source: |
| type: PyTransform |
| name: EmptyInputOkButYamlDoesntKnow |
| config: |
| constructor: apache_beam.Impulse |
| ''') |
| |
| def test_empty_inputs_ok_if_explicit(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| # Does not throw an error like it does above. |
| _ = p | YamlTransform( |
| ''' |
| type: composite |
| transforms: |
| - type: PyTransform |
| name: EmptyInputOkButYamlDoesntKnow |
| input: {} |
| config: |
| constructor: apache_beam.Impulse |
| ''') |
| |
| def test_annotations(self): |
| t = LinearTransform(5, b=100) |
| annotations = t.annotations() |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| result = p | YamlTransform( |
| ''' |
| type: chain |
| transforms: |
| - type: Create |
| config: |
| elements: [0, 1, 2, 3] |
| - type: %r |
| config: %s |
| ''' % (annotations['yaml_type'], annotations['yaml_args'])) |
| assert_that(result, equal_to([100, 105, 110, 115])) |
| |
| |
| class ErrorHandlingTest(unittest.TestCase): |
| def test_error_handling_outputs(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| result = p | YamlTransform( |
| ''' |
| type: composite |
| transforms: |
| - type: Create |
| config: |
| elements: ['a', 'b', 'biiiiig'] |
| - type: SizeLimiter |
| input: Create |
| config: |
| limit: 5 |
| error_handling: |
| output: errors |
| - name: TrimErrors |
| type: PyMap |
| input: SizeLimiter.errors |
| config: |
| fn: "lambda x: x[1][1]" |
| output: |
| good: SizeLimiter |
| bad: TrimErrors |
| ''', |
| providers=TEST_PROVIDERS) |
| assert_that(result['good'], equal_to(['a', 'b']), label="CheckGood") |
| assert_that(result['bad'], equal_to(["ValueError('biiiiig')"])) |
| |
| def test_must_handle_error_output(self): |
| with self.assertRaisesRegex(Exception, 'Unconsumed error output .*line 7'): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| _ = p | YamlTransform( |
| ''' |
| type: composite |
| transforms: |
| - type: Create |
| config: |
| elements: ['a', 'b', 'biiiiig'] |
| - type: SizeLimiter |
| input: Create |
| config: |
| limit: 5 |
| error_handling: |
| output: errors |
| ''', |
| providers=TEST_PROVIDERS) |
| |
| def test_mapping_errors(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| result = p | YamlTransform( |
| ''' |
| type: composite |
| transforms: |
| - type: Create |
| config: |
| elements: [0, 1, 2, 4] |
| - type: MapToFields |
| name: ToRow |
| input: Create |
| config: |
| language: python |
| fields: |
| num: element |
| str: "'a' * element or 'bbb'" |
| - type: Filter |
| input: ToRow |
| config: |
| language: python |
| keep: |
| str[1] >= 'a' |
| error_handling: |
| output: errors |
| - type: MapToFields |
| name: MapWithErrorHandling |
| input: Filter |
| config: |
| language: python |
| fields: |
| num: num |
| inverse: float(1 / num) |
| error_handling: |
| output: errors |
| - type: PyMap |
| name: TrimErrors |
| input: [MapWithErrorHandling.errors, Filter.errors] |
| config: |
| fn: "lambda x: x.msg" |
| - type: MapToFields |
| name: Sum |
| input: MapWithErrorHandling |
| config: |
| language: python |
| append: True |
| fields: |
| sum: num + inverse |
| output: |
| good: Sum |
| bad: TrimErrors |
| ''', |
| providers=TEST_PROVIDERS) |
| assert_that( |
| result['good'], |
| equal_to([ |
| beam.Row(num=2, inverse=.5, sum=2.5), |
| beam.Row(num=4, inverse=.25, sum=4.25) |
| ]), |
| label="CheckGood") |
| assert_that( |
| result['bad'], |
| equal_to([ |
| "IndexError('string index out of range')", # from the filter |
| "ZeroDivisionError('division by zero')", # from the mapping |
| ]), |
| label='CheckErrors') |
| |
| |
| class YamlWindowingTest(unittest.TestCase): |
| def test_explicit_window_into(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| result = p | YamlTransform( |
| ''' |
| type: chain |
| transforms: |
| - type: CreateTimestamped |
| config: |
| elements: [0, 1, 2, 3, 4, 5] |
| - type: WindowInto |
| windowing: |
| type: fixed |
| size: 4 |
| - type: SumGlobally |
| ''', |
| providers=TEST_PROVIDERS) |
| assert_that(result, equal_to([6, 9])) |
| |
| def test_windowing_on_input(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| result = p | YamlTransform( |
| ''' |
| type: chain |
| transforms: |
| - type: CreateTimestamped |
| config: |
| elements: [0, 1, 2, 3, 4, 5] |
| - type: SumGlobally |
| windowing: |
| type: fixed |
| size: 4 |
| ''', |
| providers=TEST_PROVIDERS) |
| assert_that(result, equal_to([6, 9])) |
| |
| def test_windowing_multiple_inputs(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| result = p | YamlTransform( |
| ''' |
| type: composite |
| transforms: |
| - type: CreateTimestamped |
| name: Create1 |
| config: |
| elements: [0, 2, 4] |
| - type: CreateTimestamped |
| name: Create2 |
| config: |
| elements: [1, 3, 5] |
| - type: SumGlobally |
| input: [Create1, Create2] |
| windowing: |
| type: fixed |
| size: 4 |
| output: SumGlobally |
| ''', |
| providers=TEST_PROVIDERS) |
| assert_that(result, equal_to([6, 9])) |
| |
| def test_windowing_on_output(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| result = p | YamlTransform( |
| ''' |
| type: chain |
| transforms: |
| - type: CreateTimestamped |
| config: |
| elements: [0, 1, 2, 3, 4, 5] |
| windowing: |
| type: fixed |
| size: 4 |
| - type: SumGlobally |
| ''', |
| providers=TEST_PROVIDERS) |
| assert_that(result, equal_to([6, 9])) |
| |
| def test_windowing_on_outer(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| result = p | YamlTransform( |
| ''' |
| type: chain |
| transforms: |
| - type: CreateTimestamped |
| config: |
| elements: [0, 1, 2, 3, 4, 5] |
| - type: SumGlobally |
| windowing: |
| type: fixed |
| size: 4 |
| ''', |
| providers=TEST_PROVIDERS) |
| assert_that(result, equal_to([6, 9])) |
| |
| |
| class AnnotatingProvider(yaml_provider.InlineProvider): |
| """A provider that vends transforms that do nothing but record that this |
| provider (as identified by name) was used, along with any prior history |
| of the given element. |
| """ |
| def __init__(self, name, transform_names): |
| super().__init__({ |
| transform_name: |
| lambda: beam.Map(lambda x: (x if type(x) == tuple else ()) + (name, )) |
| for transform_name in transform_names.strip().split() |
| }) |
| self._name = name |
| |
| def __repr__(self): |
| return 'AnnotatingProvider(%r)' % self._name |
| |
| |
| class AnotherAnnProvider(AnnotatingProvider): |
| """A Provider that behaves exactly as AnnotatingProvider, but is not |
| of the same type and so is considered "more distant" for matching purposes. |
| """ |
| pass |
| |
| |
| class ProviderAffinityTest(unittest.TestCase): |
| """These tests check that for a sequence of transforms, the "closest" |
| proveders are chosen among multiple possible implementations. |
| """ |
| provider1 = AnnotatingProvider("provider1", "P1 A B C ") |
| provider2 = AnnotatingProvider("provider2", "P2 A C D") |
| provider3 = AnotherAnnProvider("provider3", "P3 A B ") |
| provider4 = AnotherAnnProvider("provider4", "P4 A B D") |
| |
| providers_dict = collections.defaultdict(list) |
| for provider in [provider1, provider2, provider3, provider4]: |
| for transform_type in provider.provided_transforms(): |
| providers_dict[transform_type].append(provider) |
| |
| def test_prefers_same_provider(self): |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| result1 = p | 'Yaml1' >> YamlTransform( |
| ''' |
| type: chain |
| transforms: |
| - type: Create |
| config: |
| elements: [0] |
| - type: P1 |
| - type: A |
| - type: C |
| ''', |
| providers=self.providers_dict) |
| assert_that( |
| result1, |
| equal_to([( |
| # provider1 was chosen, as it is the only one vending P1 |
| 'provider1', |
| # All of the providers vend A, but since the input was produced |
| # by provider1, we prefer to use that again. |
| 'provider1', |
| # Similarly for C. |
| 'provider1')]), |
| label='StartWith1') |
| |
| result2 = p | 'Yaml2' >> YamlTransform( |
| ''' |
| type: chain |
| transforms: |
| - type: Create |
| config: |
| elements: [0] |
| - type: P2 |
| - type: A |
| - type: C |
| ''', |
| providers=self.providers_dict) |
| assert_that( |
| result2, |
| equal_to([( |
| # provider2 was necessarily chosen for P2 |
| 'provider2', |
| # Unlike above, we choose provider2 to implement A. |
| 'provider2', |
| # Likewise for C. |
| 'provider2')]), |
| label='StartWith2') |
| |
| def test_prefers_same_provider_class(self): |
| # Like test_prefers_same_provider, but as we cannot choose the same |
| # exact provider, we go with the next closest (which is of the same type) |
| # over an implementation from a Provider of a different type. |
| with beam.Pipeline(options=beam.options.pipeline_options.PipelineOptions( |
| pickle_library='cloudpickle')) as p: |
| result1 = p | 'Yaml1' >> YamlTransform( |
| ''' |
| type: chain |
| transforms: |
| - type: Create |
| config: |
| elements: [0] |
| - type: P1 |
| - type: A |
| - type: D |
| - type: A |
| ''', |
| providers=self.providers_dict) |
| assert_that( |
| result1, |
| equal_to([('provider1', 'provider1', 'provider2', 'provider2')]), |
| label='StartWith1') |
| |
| result3 = p | 'Yaml2' >> YamlTransform( |
| ''' |
| type: chain |
| transforms: |
| - type: Create |
| config: |
| elements: [0] |
| - type: P3 |
| - type: A |
| - type: D |
| - type: A |
| ''', |
| providers=self.providers_dict) |
| assert_that( |
| result3, |
| equal_to([('provider3', 'provider3', 'provider4', 'provider4')]), |
| label='StartWith3') |
| |
| |
| @beam.transforms.ptransform.annotate_yaml |
| class LinearTransform(beam.PTransform): |
| """A transform used for testing annotate_yaml.""" |
| def __init__(self, a, b): |
| self._a = a |
| self._b = b |
| |
| def expand(self, pcoll): |
| a = self._a |
| b = self._b |
| return pcoll | beam.Map(lambda x: a * x.element + b) |
| |
| |
| if __name__ == '__main__': |
| logging.getLogger().setLevel(logging.INFO) |
| unittest.main() |
