Project: Beam (App Definition and Development / Streaming & Messaging)
File: create-your-pipeline.md

title: "Create Your Pipeline" <!-- Licensed 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. --> {{< toc >}} Your Beam program expresses a data processing pipeline, from start to finish. This section explains the mechanics of using the classes in the Beam SDKs to build a pipeline. To construct a pipeline using the classes in the Beam SDKs, your program will need to perform the following general steps: Create a `Pipeline` object. Use a Read or Create* transform to create one or more `PCollection`s for your pipeline data. Apply transforms* to each `PCollection`. Transforms can change, filter, group, analyze, or otherwise process the elements in a `PCollection`. Each transform creates a new output `PCollection`, to which you can apply additional transforms until processing is complete. Write* or otherwise output the final, transformed `PCollection`s. Run* the pipeline. A Beam program often starts by creating a `Pipeline` object. In the Beam SDKs, each pipeline is represented by an explicit object of type `Pipeline`. Each `Pipeline` object is an independent entity that encapsulates both the data the pipeline operates over and the transforms that get applied to that data. To create a pipeline, declare a `Pipeline` object, and pass it some . {{< highlight java >}} // Start by defining the options for the pipeline. PipelineOptions options = PipelineOptionsFactory.create(); // Then create the pipeline. Pipeline p = Pipeline.create(options); {{< /highlight >}} To create your pipeline's initial `PCollection`, you apply a root transform to your pipeline object. A root transform creates a `PCollection` from either an external data source or some local data you specify. There are two kinds of root transforms in the Beam SDKs: `Read` and `Create`. `Read` transforms read data from an external source, such as a text file or a database table. `Create` transforms create a `PCollection` from an in-memory

The following example code shows how to `apply` a `TextIO.Read` root transform to read data from a text file. The transform is applied to a `Pipeline` object `p`, and returns a pipeline data set in the form of a `PCollection<String>`: {{< highlight java >}} PCollection<String> lines = p.apply( "ReadLines", TextIO.read().from("gs://some/inputData.txt")); {{< /highlight >}} You can manipulate your data using the various provided in the Beam SDKs. To do this, you apply the transforms to your pipeline's `PCollection` by calling the `apply` method on each `PCollection` that you want to process and passing the desired transform object as an argument. The following code shows how to `apply` a transform to a `PCollection` of strings. The transform is a user-defined custom transform that reverses the contents of each string and outputs a new `PCollection` containing the reversed strings. The input is a `PCollection<String>` called `words`; the code passes an instance of a `PTransform` object called `ReverseWords` to `apply`, and saves the return value as the `PCollection<String>` called `reversedWords`. {{< highlight java >}} PCollection<String> words = ...; PCollection<String> reversedWords = words.apply(new ReverseWords()); {{< /highlight >}} Once your pipeline has applied all of its transforms, you'll usually need to output the results. To output your pipeline's final `PCollection`s, you apply a `Write` transform to that `PCollection`. `Write` transforms can output the elements of a `PCollection` to an external data sink, such as a database table. You can use `Write` to output a `PCollection` at any time in your pipeline, although you'll typically write out data at the end of your pipeline. The following example code shows how to `apply` a `TextIO.Write` transform to write a `PCollection` of `String` to a text file: {{< highlight java >}} PCollection<String> filteredWords = ...; filteredWords.apply("WriteMyFile", TextIO.write().to("gs://some/outputData.txt")); {{< /highlight >}} Once you have constructed your pipeline, use the `run` method to execute the pipeline. Pipelines are executed asynchronously: the program you create sends a specification for your pipeline to a pipeline runner, which then constructs and runs the actual series of pipeline operations. {{< highlight java >}} p.run(); {{< /highlight >}} The `run` method is asynchronous. If you'd like a blocking execution instead, run your pipeline appending the `waitUntilFinish` method: {{< highlight java >}} p.run().waitUntilFinish(); {{< /highlight >}} - Learn the details of creating your pipeline, configuring pipeline options, and applying transforms. .