[GitHub] [samza] xinyuiscool commented on a change in pull request #948: SAMZA-2124: Add Beam API doc to the website

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xinyuiscool commented on a change in pull request #948: SAMZA-2124: Add Beam API doc to the website
URL: https://github.com/apache/samza/pull/948#discussion_r264818525
 
 

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 File path: docs/learn/documentation/versioned/api/beam-api.md
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+---
+layout: page
+title: Apache Beam API
+---
+<!--
+   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.
+-->
+
+### Table Of Contents
+- [Introduction](#introduction)
+- [Basic Concepts](#basic-concepts)
+- [Apache Beam - A Samza’s Perspective](#apache-beam---a-samza’s-perspective)
+
+### Introduction
+
+Apache Beam brings an easy-to-use, but powerful API and model for state-of-art stream and batch data processing with portability across a variety of languages. The Beam API and model has the following characteristics:
+
+- *Simple constructs, powerful semantics*: the whole beam API can be simply described by a `Pipeline` object, which captures all your data processing steps from input to output. Beam SDK supports over [20 data IOs](https://beam.apache.org/documentation/io/built-in/), and data transformations from simple [Map](https://beam.apache.org/releases/javadoc/2.11.0/org/apache/beam/sdk/transforms/MapElements.html) to complex [Combines and Joins](https://beam.apache.org/releases/javadoc/2.11.0/index.html?org/apache/beam/sdk/transforms/Combine.html).
+
+- *Strong consistency via event-time*: Beam provides advanced [event-time support](https://beam.apache.org/documentation/programming-guide/#watermarks-and-late-data) so you can perform windowing and aggregations based on when the events happen, instead of when they are consumed. The event-time mechanism improves the accuracy of processing results, and has repeatability when reprocessing the same data set.
+
+- *Comprehensive stream processing semantics*: Beam supports an up-to-date stream processing model, including [tumbling/sliding/session windows](https://beam.apache.org/documentation/programming-guide/#windowing), joins and aggregations. It provides [triggers](https://beam.apache.org/documentation/programming-guide/#triggers) based on conditions of early and late firings, and late arrival handling with accumulation mode and allowed lateness.
+
+- *Portability with multiple programming languages*: Beam supports a consistent API in multiple languages, including [Java, Python and Go](https://beam.apache.org/roadmap/portability/). This allows you to leverage the rich ecosystem built for different languages, e.g. ML libs for Python.
+
+### Basic Concepts
+
+Let's walk through the WordCount example to illustrate the Beam basic concepts. A Beam program often starts by creating a [Pipeline](https://beam.apache.org/releases/javadoc/2.11.0/org/apache/beam/sdk/Pipeline.html) object in your `main()` function.
+
+{% highlight java %}
+
+// Start by defining the options for the pipeline.
+PipelineOptions options = PipelineOptionsFactory.create();
+
+// Then create the pipeline.
+Pipeline p = Pipeline.create(options);
+
+{% endhighlight %}
+
+Let's apply the first data transform to read from a text file using [TextIO.read()](https://beam.apache.org/releases/javadoc/2.11.0/org/apache/beam/sdk/io/TextIO.html):
+
+{% highlight java %}
+
+PCollection<String> lines = p.apply(
+  "ReadLines", TextIO.read().from("/path/to/inputData"));
+
+{% endhighlight %}
+
+To break down each line into words, you can use a [FlatMap](https://beam.apache.org/releases/javadoc/2.11.0/org/apache/beam/sdk/transforms/FlatMapElements.html):
+
+{% highlight java %}
+
+PCollection<String> words = lines.apply(
+    FlatMapElements.into(TypeDescriptors.strings())
+        .via((String word) -> Arrays.asList(word.split("\\W+"))));
+
+{% endhighlight %}
+
+Beam provides a build-in transform [Count.perElement](https://beam.apache.org/releases/javadoc/2.11.0/org/apache/beam/sdk/transforms/Count.html) to count the number of elements based on each value. Let's use it here to count the words:
+
+{% highlight java %}
+
+PCollection<KV<String, Long>> counts = pipeline.apply(Count.perElement());
+
+{% endhighlight %}
+
+Finally we format the counts into strings and write to a file using `TextIO.write()`:
+
+{% highlight java %}
+
+counts.apply(ToString.kvs())
+      .apply(TextIO.write().to("/path/to/output").withoutSharding());
+
+{% endhighlight %}
+
+To run your pipeline and wait for the results, just do:
+
+{% highlight java %}
+
+pipeline.run().waitUntilFinish();
+
+{% endhighlight %}
+
+Or you can run your pipeline asynchronously, e.g. when you submit it to a remote cluster:
+
+{% highlight java %}
+
+pipeline.run();
+
+{% endhighlight %}
+
+To run this Beam program with Samza, you can simply provides "--runner=SamzaRunner" as a program argument. You can follow our [quick start](/startup/quick-start/{{site.version}}/beam.html) to set up your project and run different examples. For more details on writing the Beam program, please refer the comprehensive [Beam programming guide](https://beam.apache.org/documentation/programming-guide/).
 
 Review comment:
   fixed.

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