jrmccluskey commented on code in PR #33702: URL: https://github.com/apache/beam/pull/33702#discussion_r1941382628
########## sdks/python/apache_beam/testing/benchmarks/README.md: ########## @@ -0,0 +1,117 @@ +<!-- + 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. +--> + +# Writing a Dataflow Cost Benchmark + +Writing a Dataflow Cost Benchmark to estimate the financial cost of executing a pipeline on Google Cloud Platform Dataflow requires 4 components in the repository: + +1. A pipeline to execute (ideally one located in the examples directory) +1. A text file with pipeline options in the `.github/workflows/cost-benchmarks-pipeline-options` [directory](../../../../../.github/workflows/cost-benchmarks-pipeline-options) +1. A test class inheriting from the `DataflowCostBenchmark` [class](../load_tests/dataflow_cost_benchmark.py) +1. An entry to execute the pipeline as part of the cost benchmarks workflow action + +### Choosing a Pipeline +Pipelines that are worth benchmarking in terms of performance and cost have a few straightforward requirements. + +1. The transforms used in the pipeline should be native to Beam *or* be lightweight and readily available in the given pipeline Review Comment: In this case I mean "short and simple code that is contained in the source code of the pipeline if it isn't a native beam transform." This is a somewhat subjective criterion, but the idea is that we want to minimize the performance impact of code that isn't Beam-provided since custom code is more variable (and generally outside our control) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
