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src=/images/external-link-icon.png width=14 height=14 alt="External link."></a></li></ul></li></ul></nav></div><nav class="page-nav clearfix" data-offset-top=90 data-offset-bottom=500><nav id=TableOfContents><ul><li><a href=#why-use-streaming-execution>Why use streaming execution?</a></li><li><a href=#modifying-a-pipeline-to-use-stream-processing>Modifying a pipeline to use stream processing</a></li><li><a href=#running-a-streaming-pipeline>Running a streaming pipeline</a></li><li><a href=#unsupported-features>Unsupported features</a></li></ul></nav></nav><div class="body__contained body__section-nav"><h1 id=python-streaming-pipelines>Python Streaming Pipelines</h1><p>Python streaming pipeline execution became available (with some |
| <a href=#unsupported-features>limitations</a>) starting with Beam SDK version 2.5.0.</p><h2 id=why-use-streaming-execution>Why use streaming execution?</h2><p>Beam creates an unbounded PCollection if your pipeline reads from a streaming or |
| continuously-updating data source (such as Cloud Pub/Sub). A runner must |
| process an unbounded PCollection using a streaming job that runs continuously, |
| as the entire collection is never available for processing at any one time. |
| <a href=/documentation/programming-guide/#size-and-boundedness>Size and boundedness</a> |
| has more information about bounded and unbounded collections.</p><h2 id=modifying-a-pipeline-to-use-stream-processing>Modifying a pipeline to use stream processing</h2><p>To modify a batch pipeline to support streaming, you must make the following |
| code changes:</p><ul><li>Use an I/O connector that supports reading from an unbounded source.</li><li>Use an I/O connector that supports writing to an unbounded source.</li><li>Choose a <a href=/documentation/programming-guide/index.html#windowing>windowing strategy</a>.</li></ul><p>The Beam SDK for Python includes two I/O connectors that support unbounded |
| PCollections: Google Cloud Pub/Sub (reading and writing) and Google BigQuery |
| (writing).</p><p>The following snippets show the necessary code changes to modify the batch |
| WordCount example to support streaming:</p><p>These batch WordCount snippets are from |
| <a href=https://github.com/apache/beam/blob/master/sdks/python/apache_beam/examples/wordcount.py>wordcount.py</a>. |
| This code uses the TextIO I/O connector to read from and write to a bounded |
| collection.</p><pre tabindex=0><code> lines = p | 'read' >> ReadFromText(known_args.input) |
| ... |
| |
| counts = (lines |
| | 'split' >> (beam.ParDo(WordExtractingDoFn()) |
| .with_output_types(six.text_type)) |
| | 'pair_with_one' >> beam.Map(lambda x: (x, 1)) |
| | 'group' >> beam.GroupByKey() |
| | 'count' >> beam.Map(count_ones)) |
| ... |
| |
| output = counts | 'format' >> beam.Map(format_result) |
| |
| # Write the output using a "Write" transform that has side effects. |
| output | 'write' >> WriteToText(known_args.output) |
| </code></pre><p>These streaming WordCount snippets are from |
| <a href=https://github.com/apache/beam/blob/master/sdks/python/apache_beam/examples/streaming_wordcount.py>streaming_wordcount.py</a>. |
| This code uses an I/O connector that reads from and writes to an unbounded |
| source (Cloud Pub/Sub) and specifies a fixed windowing strategy.</p><pre tabindex=0><code> lines = p | beam.io.ReadFromPubSub(topic=known_args.input_topic) |
| ... |
| |
| counts = (lines |
| | 'split' >> (beam.ParDo(WordExtractingDoFn()) |
| .with_output_types(six.text_type)) |
| | 'pair_with_one' >> beam.Map(lambda x: (x, 1)) |
| | beam.WindowInto(window.FixedWindows(15, 0)) |
| | 'group' >> beam.GroupByKey() |
| | 'count' >> beam.Map(count_ones)) |
| |
| ... |
| |
| output = counts | 'format' >> beam.Map(format_result) |
| |
| # Write to Pub/Sub |
| output | beam.io.WriteStringsToPubSub(known_args.output_topic) |
| </code></pre><h2 id=running-a-streaming-pipeline>Running a streaming pipeline</h2><p>To run the example streaming WordCount pipeline, you must have a Cloud Pub/Sub |
| input topic and output topic. To create, subscribe to, and pull from a topic for |
| testing purposes, you can use the commands in the <a href=https://cloud.google.com/pubsub/docs/quickstart-cli>Cloud Pub/Sub quickstart</a>.</p><p>The following simple bash script feeds lines of an input text file to your input |
| topic:</p><pre tabindex=0><code>cat <YOUR_LOCAL_TEXT_FILE> | while read line; do gcloud pubsub topics publish <YOUR_INPUT_TOPIC_NAME> --message "$line"; done |
| </code></pre><p>Alternately, you can read from a publicly available Cloud Pub/Sub stream, such |
| as <code>projects/pubsub-public-data/topics/taxirides-realtime</code>. However, you must |
| create your own output topic to test writes.</p><p>The following commands run the |
| <a href=https://github.com/apache/beam/blob/master/sdks/python/apache_beam/examples/streaming_wordcount.py>streaming_wordcount.py</a> |
| example streaming pipeline. Specify your Cloud Pub/Sub project and input topic |
| (<code>--input_topic</code>), output Cloud Pub/Sub project and topic (<code>--output_topic</code>).</p><div class='runner-direct snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><pre tabindex=0><code class=language-direct data-lang=direct># DirectRunner requires the --streaming option |
| python -m apache_beam.examples.streaming_wordcount \ |
| --input_topic "projects/YOUR_PUBSUB_PROJECT_NAME/topics/YOUR_INPUT_TOPIC" \ |
| --output_topic "projects/YOUR_PUBSUB_PROJECT_NAME/topics/YOUR_OUTPUT_TOPIC" \ |
| --streaming</code></pre></div></div><div class='runner-flink snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><pre tabindex=0><code class=language-flink data-lang=flink>See /documentation/runners/flink/ for more information.</code></pre></div></div><div class='runner-spark snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><pre tabindex=0><code class=language-spark data-lang=spark>See /documentation/runners/spark/ for more information.</code></pre></div></div><div class='runner-dataflow snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><pre tabindex=0><code class=language-dataflow data-lang=dataflow># As part of the initial setup, install Google Cloud Platform specific extra components. |
| pip install apache-beam[gcp] |
| |
| # DataflowRunner requires the --streaming option |
| python -m apache_beam.examples.streaming_wordcount \ |
| --runner DataflowRunner \ |
| --project YOUR_GCP_PROJECT \ |
| --region YOUR_GCP_REGION \ |
| --temp_location gs://YOUR_GCS_BUCKET/tmp/ \ |
| --input_topic "projects/YOUR_PUBSUB_PROJECT_NAME/topics/YOUR_INPUT_TOPIC" \ |
| --output_topic "projects/YOUR_PUBSUB_PROJECT_NAME/topics/YOUR_OUTPUT_TOPIC" \ |
| --streaming</code></pre></div></div><p>Check your runner’s documentation for any additional runner-specific information |
| about executing streaming pipelines:</p><ul><li><a href=/documentation/runners/direct/#streaming-execution>DirectRunner streaming execution</a></li><li><a href=/documentation/runners/dataflow/#streaming-execution>DataflowRunner streaming execution</a></li><li><a href=/documentation/runners/flink/>Portable Flink runner</a></li></ul><h2 id=unsupported-features>Unsupported features</h2><p>Python streaming execution does not currently support the following features:</p><ul><li>Custom source API</li><li>User-defined custom merging <code>WindowFn</code> (with fnapi)</li><li>For portable runners, see <a href=https://s.apache.org/apache-beam-portability-support-table>portability support table</a>.</li></ul></div></div><footer class=footer><div class=footer__contained><div class=footer__cols><div class="footer__cols__col footer__cols__col__logos"><div class=footer__cols__col__logo><img src=/images/beam_logo_circle.svg class=footer__logo alt="Beam logo"></div><div class=footer__cols__col__logo><img src=/images/apache_logo_circle.svg class=footer__logo alt="Apache logo"></div></div><div class=footer-wrapper><div class=wrapper-grid><div class=footer__cols__col><div class=footer__cols__col__title>Start</div><div class=footer__cols__col__link><a href=/get-started/beam-overview/>Overview</a></div><div class=footer__cols__col__link><a href=/get-started/quickstart-java/>Quickstart (Java)</a></div><div class=footer__cols__col__link><a href=/get-started/quickstart-py/>Quickstart (Python)</a></div><div class=footer__cols__col__link><a href=/get-started/quickstart-go/>Quickstart (Go)</a></div><div class=footer__cols__col__link><a href=/get-started/downloads/>Downloads</a></div></div><div class=footer__cols__col><div class=footer__cols__col__title>Docs</div><div class=footer__cols__col__link><a href=/documentation/programming-guide/>Concepts</a></div><div class=footer__cols__col__link><a href=/documentation/pipelines/design-your-pipeline/>Pipelines</a></div><div class=footer__cols__col__link><a href=/documentation/runners/capability-matrix/>Runners</a></div></div><div class=footer__cols__col><div class=footer__cols__col__title>Community</div><div class=footer__cols__col__link><a href=/contribute/>Contribute</a></div><div class=footer__cols__col__link><a href=https://projects.apache.org/committee.html?beam target=_blank>Team<img src=/images/external-link-icon.png width=14 height=14 alt="External link."></a></div><div class=footer__cols__col__link><a href=/community/presentation-materials/>Media</a></div><div class=footer__cols__col__link><a href=/community/in-person/>Events/Meetups</a></div><div class=footer__cols__col__link><a href=/community/contact-us/>Contact Us</a></div></div><div class=footer__cols__col><div class=footer__cols__col__title>Resources</div><div class=footer__cols__col__link><a href=/blog/>Blog</a></div><div class=footer__cols__col__link><a href=https://github.com/apache/beam>GitHub</a></div></div></div><div class=footer__bottom>© |
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