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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,
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# limitations under the License.
#
"""End-to-end test for Avro IO's fastavro support.
Writes a configurable number of records to a temporary location with fastavro,
then reads them back in from source, joins the generated records and records
that are read from the source, and verifies they have the same elements.
Usage:
DataFlowRunner:
pytest apache_beam/examples/fastavro_it_test.py \
--test-pipeline-options="
--runner=TestDataflowRunner
--project=...
--region=...
--staging_location=gs://...
--temp_location=gs://...
--output=gs://...
--sdk_location=...
"
DirectRunner:
pytest apache_beam/examples/fastavro_it_test.py \
--test-pipeline-options="
--output=/tmp
--records=5000
"
"""
# pytype: skip-file
import json
import logging
import unittest
import uuid
import pytest
from fastavro import parse_schema
from apache_beam.io.avroio import ReadAllFromAvro
from apache_beam.io.avroio import WriteToAvro
from apache_beam.runners.runner import PipelineState
from apache_beam.testing.test_pipeline import TestPipeline
from apache_beam.testing.test_utils import delete_files
from apache_beam.testing.util import BeamAssertException
from apache_beam.transforms.core import Create
from apache_beam.transforms.core import FlatMap
from apache_beam.transforms.core import Map
from apache_beam.transforms.util import CoGroupByKey
LABELS = ['abc', 'def', 'ghi', 'jkl', 'mno', 'pqr', 'stu', 'vwx']
COLORS = ['RED', 'ORANGE', 'YELLOW', 'GREEN', 'BLUE', 'PURPLE', None]
def record(i):
return {
'label': LABELS[i % len(LABELS)],
'number': i,
'number_str': str(i),
'color': COLORS[i % len(COLORS)]
}
def assertEqual(l, r):
if l != r:
raise BeamAssertException('Assertion failed: %s == %s' % (l, r))
def check(element):
assert element['color'] in COLORS
assert element['label'] in LABELS
assertEqual(
sorted(element.keys()), ['color', 'label', 'number', 'number_str'])
class FastavroIT(unittest.TestCase):
SCHEMA_STRING = '''
{"namespace": "example.avro",
"type": "record",
"name": "User",
"fields": [
{"name": "label", "type": "string"},
{"name": "number", "type": ["int", "null"]},
{"name": "number_str", "type": ["string", "null"]},
{"name": "color", "type": ["string", "null"]}
]
}
'''
def setUp(self):
self.test_pipeline = TestPipeline(is_integration_test=True)
self.uuid = str(uuid.uuid4())
self.output = '/'.join([self.test_pipeline.get_option('output'), self.uuid])
@pytest.mark.it_postcommit
def test_avro_it(self):
num_records = self.test_pipeline.get_option('records')
num_records = int(num_records) if num_records else 1000000
fastavro_output = '/'.join([self.output, 'fastavro'])
# Seed a `PCollection` with indices that will each be FlatMap'd into
# `batch_size` records, to avoid having a too-large list in memory at
# the outset
batch_size = self.test_pipeline.get_option('batch-size')
batch_size = int(batch_size) if batch_size else 10000
# pylint: disable=bad-option-value
batches = range(int(num_records / batch_size))
def batch_indices(start):
# pylint: disable=bad-option-value
return range(start * batch_size, (start + 1) * batch_size)
# A `PCollection` with `num_records` avro records
records_pcoll = \
self.test_pipeline \
| 'create-batches' >> Create(batches) \
| 'expand-batches' >> FlatMap(batch_indices) \
| 'create-records' >> Map(record)
# pylint: disable=expression-not-assigned
records_pcoll \
| 'write_fastavro' >> WriteToAvro(
fastavro_output,
parse_schema(json.loads(self.SCHEMA_STRING)),
)
result = self.test_pipeline.run()
result.wait_until_finish()
fastavro_pcoll = self.test_pipeline \
| 'create-fastavro' >> Create(['%s*' % fastavro_output]) \
| 'read-fastavro' >> ReadAllFromAvro()
mapped_fastavro_pcoll = fastavro_pcoll | "map_fastavro" >> Map(
lambda x: (x['number'], x))
mapped_record_pcoll = records_pcoll | "map_record" >> Map(
lambda x: (x['number'], x))
def validate_record(elem):
v = elem[1]
def assertEqual(l, r):
if l != r:
raise BeamAssertException('Assertion failed: %s == %s' % (l, r))
assertEqual(sorted(v.keys()), ['fastavro', 'record_pcoll'])
record_pcoll_values = v['record_pcoll']
fastavro_values = v['fastavro']
assertEqual(record_pcoll_values, fastavro_values)
assertEqual(len(record_pcoll_values), 1)
{
"record_pcoll": mapped_record_pcoll, "fastavro": mapped_fastavro_pcoll
} | CoGroupByKey() | Map(validate_record)
result = self.test_pipeline.run()
result.wait_until_finish()
self.addCleanup(delete_files, [self.output])
assert result.state == PipelineState.DONE
if __name__ == '__main__':
logging.getLogger().setLevel(logging.DEBUG)
unittest.main()