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https://issues.apache.org/jira/browse/BEAM-7402?focusedWorklogId=253035&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-253035
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ASF GitHub Bot logged work on BEAM-7402:
----------------------------------------
Author: ASF GitHub Bot
Created on: 03/Jun/19 10:17
Start Date: 03/Jun/19 10:17
Worklog Time Spent: 10m
Work Description: kamilwu commented on pull request #8675: [BEAM-7402]
BigQuery IO read performance tests
URL: https://github.com/apache/beam/pull/8675#discussion_r289777487
##########
File path: sdks/python/apache_beam/io/gcp/bigquery_io_read_pipeline.py
##########
@@ -14,66 +14,135 @@
# See the License for the specific language governing permissions and
# limitations under the License.
#
-
-"""A Dataflow job that counts the number of rows in a BQ table.
-
- Can be configured to simulate slow reading for a given number of rows.
+"""
+A pipeline that reads data from a BigQuery table and counts the number of
+rows.
+
+Besides of the standard options, there are options with special meaning:
+* input_dataset - BQ dataset id.
+* input_table - BQ table id.
+The table will be created and populated with data from Synthetic Source if it
+does not exist.
+* input_options - options for Synthetic Source:
+num_records - number of rows to be inserted,
+value_size - the length of a single row,
+key_size - required option, but its value has no meaning,
+* num_slow - an integer in range [0,100] used to customize slow reading
+simulation.
+
+Example test run on DataflowRunner:
+
+python setup.py nosetests \
+ --test-pipeline-options="
+ --runner=TestDataflowRunner
+ --project=...
+ --staging_location=gs://...
+ --temp_location=gs://...
+ --sdk_location=.../dist/apache-beam-x.x.x.dev0.tar.gz
+ --input_dataset=...
+ --input_table=...
+ --input_options='{
+ \"num_records\": 1024,
+ \"key_size\": 1,
+ \"value_size\": 1024,
+ }'" \
+ --tests apache_beam.io.gcp.tests.bigquery_io_read_pipeline
"""
from __future__ import absolute_import
-import argparse
+import base64
import logging
import random
import time
-
-import apache_beam as beam
-from apache_beam.options.pipeline_options import PipelineOptions
+import unittest
+
+from apache_beam import DoFn
+from apache_beam import Map
+from apache_beam import ParDo
+from apache_beam.io import BigQueryDisposition
+from apache_beam.io import BigQuerySource
+from apache_beam.io import Read
+from apache_beam.io import WriteToBigQuery
+from apache_beam.io.gcp.bigquery_tools import BigQueryWrapper
+from apache_beam.io.gcp.bigquery_tools import parse_table_schema_from_json
+from apache_beam.testing.load_tests.load_test import LoadTest
+from apache_beam.testing.synthetic_pipeline import SyntheticSource
from apache_beam.testing.test_pipeline import TestPipeline
from apache_beam.testing.util import assert_that
from apache_beam.testing.util import equal_to
-
-
-class RowToStringWithSlowDown(beam.DoFn):
-
- def process(self, element, num_slow=0, *args, **kwargs):
-
- if num_slow == 0:
- yield ['row']
- else:
- rand = random.random() * 100
- if rand < num_slow:
- time.sleep(0.01)
- yield ['slow_row']
- else:
+from apache_beam.transforms.combiners import Count
+
+
+class BigQueryIOReadTest(LoadTest):
+ def setUp(self):
+ super(BigQueryIOReadTest, self).setUp()
+ self.num_slow = self.pipeline.get_option('num_slow') or 0
+ self.input_dataset = self.pipeline.get_option('input_dataset')
+ self.input_table = self.pipeline.get_option('input_table')
+ self._check_for_input_data()
+
+ def _check_for_input_data(self):
+ """Checks if a BQ table with input data exists and creates it if not."""
+ wrapper = BigQueryWrapper()
+ try:
+ wrapper.get_table(self.project_id, self.input_dataset, self.input_table)
+ except Exception:
+ self._create_input_data()
+
+ def _create_input_data(self):
+ """
+ Runs an additional pipeline which creates test data and waits for its
+ completion.
+ """
+ SCHEMA = parse_table_schema_from_json(
+ '{"fields": [{"name": "data", "type": "BYTES"}]}')
+
+ def format_record(record):
+ # Since Syntentic Source returns data as a dictionary. we should skip
+ # one of the part
+ return {'data': base64.b64encode(record[1])}
+
+ p = TestPipeline()
+ # pylint: disable=expression-not-assigned
+ (p
+ | 'Produce rows' >> Read(SyntheticSource(self.parseTestPipelineOptions()))
+ | 'Format' >> Map(format_record)
+ | 'Write to BigQuery' >> WriteToBigQuery(
+ self.input_dataset + '.' + self.input_table,
+ schema=SCHEMA,
+ create_disposition=BigQueryDisposition.CREATE_IF_NEEDED,
+ write_disposition=BigQueryDisposition.WRITE_EMPTY))
+ p.run().wait_until_finish()
+
+ class RowToStringWithSlowDown(DoFn):
+ def process(self, element, num_slow=0, *args, **kwargs):
+ if num_slow == 0:
yield ['row']
+ else:
+ rand = random.random() * 100
+ if rand < num_slow:
+ time.sleep(0.01)
+ yield ['slow_row']
+ else:
+ yield ['row']
+ def test(self):
+ run_pipeline(self.pipeline, self.input_dataset, self.input_table,
Review comment:
Correct me if I'm wrong, but I think the slow reading doesn't care where do
the data come from. Its purpose is to just slow down the execution.
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Issue Time Tracking
-------------------
Worklog Id: (was: 253035)
Time Spent: 1h 10m (was: 1h)
> Add a performance test for BigQueryIO read
> ------------------------------------------
>
> Key: BEAM-7402
> URL: https://issues.apache.org/jira/browse/BEAM-7402
> Project: Beam
> Issue Type: Test
> Components: testing
> Reporter: Kamil Wasilewski
> Assignee: Kamil Wasilewski
> Priority: Major
> Time Spent: 1h 10m
> Remaining Estimate: 0h
>
> The task is to add a performance test for BigQuery IO read with configurable
> data size.
> The plan is:
> 1) Setup BQ table with input data if needed,
> 2) Read data from that table and do some final assertions
>
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