Project: Beam (App Definition and Development / Streaming & Messaging)
File: 34_change_coders_data_encoding.md

Prompt: How to get, set, and create new coders for my Apache Beam pipeline? Response: Every `PCollection` in an Apache Beam pipeline requires a corresponding `Coder`. In most cases, the Apache Beam SDKs can automatically infer a `Coder` for a `PCollection` based on its element type or the producing transform. However, in some instances, you may need to explicitly set a `Coder` or create a custom `Coder`. In the Apache Beam SDKs for Python and Java, the `Coder` type provides the necessary methods for encoding and decoding data. To get, set, or register a coder for a particular pipeline, you can access and modify the pipelines `CoderRegistry` object. The following examples demonstrate how to get, set, and create a new `Coder` in an Apache Beam pipeline using the Python and Java SDKs. Python SDK: In the Python SDK, you can use the following methods: `coders.registry`: retrieves the pipelines `CoderRegistry` object. `CoderRegistry.get_coder`: retrieves the default `Coder` for a type. `CoderRegistry.register_coder`: sets a new `Coder` for the target type. Here is an example illustrating how to set the default `Coder` in the Python SDK: ```python apachebeam.coders.registry.registercoder(int, BigEndianIntegerCoder) ``` The provided example sets a default `Coder`, specifically `BigEndianIntegerCoder`, for `int` values in the pipeline. For custom or complex nested data types, you can implement a custom coder for your pipeline. To create a new `Coder`, you need to define a class that inherits from `Coder` and implement the required methods: `encode`: takes input values and encodes them into byte strings. `decode`: decodes the encoded byte string into its corresponding object. `is_deterministic`: specifies whether this coder encodes values deterministically or not. A deterministic coder produces the same encoded representation of a given object every time, even if it is called on different workers at different moments. The method returns `True` or `False` based on your implementation. Here is an example of a custom `Coder` implementation in the Python SDK: ```python from

import Coder class CustomCoder(Coder): def encode(self, value): pass def decode(self, encoded): pass def is_deterministic(self): return True # or False based on your implementation ``` Java SDK: In the Java SDK, you can use the following methods: `Pipeline.getCoderRegistry`: retrieves the pipelines `CoderRegistry` object. `getCoder`: retrieves the coder for an existing `PCollection`. `CoderRegistry.getCoder`: retrieves the default `Coder` for a type. `CoderRegistry.registerCoder`: sets a new default `Coder` for the target type. Here is an example of how you can set the default Coder in the Java SDK: ```java PipelineOptions options = PipelineOptionsFactory.create(); Pipeline p = Pipeline.create(options); CoderRegistry cr = p.getCoderRegistry(); cr.registerCoder(Integer.class, BigEndianIntegerCoder.class); ``` In this example, you use the method `CoderRegistry.registerCoder` to register `BigEndianIntegerCoder` for the target `integer` type. For custom or complex nested data types, you can implement a custom coder for your pipeline. For this, the `Coder` class exposes the following key methods: `encode`: takes input values and encodes them into byte strings. `decode`: decodes the encoded byte string into its corresponding object. `verifyDeterministic`: specifies whether this coder produces deterministic encodings. A deterministic coder produces the same encoded representation of a given object every time, even if it is called on different workers at different moments. The method will return `NonDeterministicException` if a coder is not deterministic. Heres an example of a custom `Coder` implementation in the Java SDK: ```java import org.apache.beam.sdk.coders.CoderException; import org.apache.beam.sdk.coders.StructuredCoder; import java.io.IOException; import java.io.InputStream; import java.io.OutputStream; public class CustomCoder extends StructuredCoder<YourType> { @Override public void encode(YourType value, OutputStream outStream) throws CoderException, IOException { // Implementation for encoding 'value' into byte strings } @Override public YourType decode(InputStream inStream) throws CoderException, IOException { // Implementation for decoding byte strings into the original object } @Override public void verifyDeterministic() throws NonDeterministicException { // Specify whether this coder produces deterministic encodings // Throw NonDeterministicException if not deterministic } } ``` Replace `YourType` with the actual type for which you want to create a new `Coder`, and implement the necessary methods based on your encoding/decoding logic.