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| <script>function showSearch(){addPlaceholder();var e,t=document.querySelector(".searchBar");t.classList.remove("disappear"),e=document.querySelector("#iconsBar"),e.classList.add("disappear")}function addPlaceholder(){$("input:text").attr("placeholder","What are you looking for?")}function endSearch(){var e,t=document.querySelector(".searchBar");t.classList.add("disappear"),e=document.querySelector("#iconsBar"),e.classList.remove("disappear")}function blockScroll(){$("body").toggleClass("fixedPosition")}function openMenu(){addPlaceholder(),blockScroll()}</script><div class="clearfix container-main-content"><div class="section-nav closed" data-offset-top=90 data-offset-bottom=500><span class="section-nav-back glyphicon glyphicon-menu-left"></span><nav><ul class=section-nav-list data-section-nav><li><span class=section-nav-list-main-title>Roadmap</span></li><li><a href=/roadmap/>Roadmap Highlights</a></li><li><a href=/roadmap/portability>Portability Framework</a></li><li class=section-nav-item><span class=section-nav-list-title>Languages</span><ul class=section-nav-list><li><a href=/roadmap/java-sdk>Java SDK</a></li><li><a href=/roadmap/go-sdk>Go SDK</a></li><li><a href=/roadmap/python-sdk>Python SDK</a></li><li><a href=/roadmap/euphoria>Euphoria API</a></li><li><a href=/roadmap/sql>SQL</a></li></ul></li><li class=section-nav-item><span class=section-nav-list-title>Runners</span><ul class=section-nav-list><li><a href=/roadmap/dataflow-runner/>Google Cloud Dataflow Runner</a></li><li><a href=/roadmap/flink-runner/>Flink Runner</a></li><li><a href=/roadmap/nemo-runner/>Nemo Runner</a></li><li><a href=/roadmap/spark-runner/>Spark Runner</a></li><li><a href=/roadmap/samza-runner/>Samza Runner</a></li><li><a href=/roadmap/twister2-runner/>Twister2 Runner</a></li></ul></li><li class=section-nav-item><span class=section-nav-list-title>Connectors</span><ul class=section-nav-list><li><a href=/roadmap/connectors-java-sdk/>Java SDK</a></li><li><a href=/roadmap/connectors-python-sdk/>Python SDK</a></li><li><a href=/roadmap/connectors-go-sdk/>Go SDK</a></li><li><a href=/roadmap/connectors-multi-sdk/>Multi-SDK Efforts</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=#overview>Overview</a></li><li><a href=#status>Status</a></li><li><a href=#issues>Issues</a><ul><li><a href=#python-on-flink>Running Python wordcount on Flink</a></li><li><a href=#python-on-spark>Running Python wordcount on Spark</a></li></ul></li><li><a href=#sdk-harness-config>SDK Harness Configuration</a></li></ul></nav></nav><div class="body__contained body__section-nav"><h1 id=portability-framework-roadmap>Portability Framework Roadmap</h1><h2 id=overview>Overview</h2><p>Interoperability between SDKs and runners is a key aspect of Apache |
| Beam. Previously, the reality was that most runners supported the |
| Java SDK only, because each SDK-runner combination required non-trivial |
| work on both sides. Most runners are also currently written in Java, |
| which makes support of non-Java SDKs far more expensive. The |
| <em>portability framework</em> rectified this situation and provided |
| full interoperability across the Beam ecosystem.</p><p>The portability framework introduces well-defined, language-neutral |
| data structures and protocols between the SDK and runner. This interop |
| layer – called the <em>portability API</em> – ensures that SDKs and runners |
| can work with each other uniformly, reducing the interoperability |
| burden for both SDKs and runners to a constant effort. It notably |
| ensures that <em>new</em> SDKs automatically work with existing runners and |
| vice versa. The framework introduces a new runner, the <em>Universal |
| Local Runner (ULR)</em>, as a practical reference implementation that |
| complements the direct runners. Finally, it enables cross-language |
| pipelines (sharing I/O or transformations across SDKs) and |
| user-customized <a href=/documentation/runtime/environments/>execution environments</a> |
| (“custom containers”).</p><p>The portability API consists of a set of smaller contracts that |
| isolate SDKs and runners for job submission, management and |
| execution. These contracts use protobufs and <a href=https://grpc.io>gRPC</a> for broad language |
| support.</p><ul><li><p><strong>Job submission and management</strong>: The <em>Runner API</em> defines a |
| language-neutral pipeline representation with transformations |
| specifying the execution environment as a docker container |
| image. The latter both allows the execution side to set up the |
| right environment as well as opens the door for custom containers |
| and cross-environment pipelines. The <em>Job API</em> allows pipeline |
| execution and configuration to be managed uniformly.</p></li><li><p><strong>Job execution</strong>: The <em>SDK harness</em> is a SDK-provided |
| program responsible for executing user code and is run separately |
| from the runner. The <em>Fn API</em> defines an execution-time binary |
| contract between the SDK harness and the runner that describes how |
| execution tasks are managed and how data is transferred. In |
| addition, the runner needs to handle progress and monitoring in an |
| efficient and language-neutral way. SDK harness initialization |
| relies on the <em>Provision</em> and <em>Artifact APIs</em> for obtaining staged |
| files, pipeline options and environment information. Docker |
| provides isolation between the runner and SDK/user environments to |
| the benefit of both as defined by the <em>container contract</em>. The |
| containerization of the SDK gives it (and the user, unless the SDK |
| is closed) full control over its own environment without risk of |
| dependency conflicts. The runner has significant freedom regarding |
| how it manages the SDK harness containers.</p></li></ul><p>The goal is that all (non-direct) runners and SDKs eventually support |
| the portability API, perhaps exclusively.</p><p>If you are interested in digging in to the designs, you can find |
| them on the <a href=https://cwiki.apache.org/confluence/display/BEAM/Design+Documents>Beam developers’ wiki</a>. |
| Another overview can be found <a href="https://docs.google.com/presentation/d/1Yg8Xm4fb-oRjiLQjwLt5153hpwwTLclZrVOKP2hQifo/edit#slide=id.g42e4c9aad6_1_3070">here</a>.</p><h2 id=status>Status</h2><p>All SDKs currently support the portability framework. |
| There is also a Python Universal Local Runner and shared java runners library. |
| Performance is good and multi-language pipelines are supported. |
| Currently, the Flink and Spark runners support portable pipeline execution |
| (which is used by default for SDKs other than Java), |
| as does Dataflow when using the <a href=https://cloud.google.com/dataflow/docs/guides/deploying-a-pipeline#dataflow-runner-v2>Dataflow Runner v2</a>. |
| See the |
| <a href=https://s.apache.org/apache-beam-portability-support-table>Portability support table</a> |
| for details.</p><h2 id=issues>Issues</h2><p>The portability effort touches every component, so the “portability” |
| label is used to identify all portability-related issues. Pure |
| design or proto definitions should use the “beam-model” component. A |
| common pattern for new portability features is that the overall |
| feature is in “beam-model” with subtasks for each SDK and runner in |
| their respective components.</p><p><strong>Issues:</strong> <a href="https://github.com/apache/beam/issues?q=is%3Aopen+is%3Aissue+label%3Aportability">query</a></p><p>Prerequisites: <a href=https://docs.docker.com/compose/install/>Docker</a>, <a href=https://docs.python-guide.org/starting/install3/linux/>Python</a>, <a href=https://openjdk.java.net/install/>Java 8</a></p><h3 id=python-on-flink>Running Python wordcount on Flink</h3><p>The Beam Flink runner can run Python pipelines in batch and streaming modes. |
| Please see the <a href=/documentation/runners/flink/>Flink Runner page</a> for more information on |
| how to run portable pipelines on top of Flink.</p><h3 id=python-on-spark>Running Python wordcount on Spark</h3><p>The Beam Spark runner can run Python pipelines in batch mode. |
| Please see the <a href=/documentation/runners/spark/>Spark Runner page</a> for more information on |
| how to run portable pipelines on top of Spark.</p><p>Python streaming mode is not yet supported on Spark.</p><h2 id=sdk-harness-config>SDK Harness Configuration</h2><p>See <a href=/documentation/runtime/sdk-harness-config/>here</a> for more information on SDK harness deployment options |
| and <a href="https://docs.google.com/presentation/d/1Cso0XP9dmj77OD9Bd53C1M3W1sPJF0ZnA20gzb2BPhE/edit?usp=sharing">here</a> |
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