Apache Beam is an open-source unified programming model that allows you to define both batch and streaming data processing pipelines. It provides a SQL-like language called Beam SQL that enables you to query and process data in a declarative manner.

In this blog post, we will explore how to use Apache Beam SQL with Java to perform query processing on data streams or batch datasets.

Setting Up Apache Beam SQL with Java

To get started with Apache Beam SQL in Java, you need to include the necessary dependencies in your project. Add the following Maven dependencies to your pom.xml file:

<dependencies>
  <!-- Apache Beam Core -->
  <dependency>
    <groupId>org.apache.beam</groupId>
    <artifactId>beam-sdks-java-core</artifactId>
    <version>2.33.0</version>
  </dependency>
  
  <!-- Apache Beam SQL -->
  <dependency>
    <groupId>org.apache.beam</groupId>
    <artifactId>beam-sdks-java-sql</artifactId>
    <version>2.33.0</version>
  </dependency>
  
  <!-- Apache Beam Runners -->
  <dependency>
    <groupId>org.apache.beam</groupId>
    <artifactId>beam-runners-direct-java</artifactId>
    <version>2.33.0</version>
  </dependency>
</dependencies>

Once you have the dependencies added, you can start writing Apache Beam SQL queries in Java.

Performing Query Processing with Apache Beam SQL

To demonstrate query processing with Apache Beam SQL, let’s consider a simple example where we want to filter out even numbers from a stream of integers.

import org.apache.beam.runners.direct.DirectRunner;
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.io.TextIO;
import org.apache.beam.sdk.options.PipelineOptionsFactory;
import org.apache.beam.sdk.values.PCollection;

public class ApacheBeamSQLExample {

  public static void main(String[] args) {
    PipelineOptions options = PipelineOptionsFactory.create();
    options.setRunner(DirectRunner.class);

    Pipeline pipeline = Pipeline.create(options);

    // Read the input data from a text file
    PCollection<Integer> input = pipeline.apply(TextIO.read().from("input.txt"))
        .apply("ParseNumbers", ParDo.of(new ParseNumbersFn()));
        
    // Apply the Apache Beam SQL query
    PCollection<Integer> output = input.apply("FilterEvenNumbers", SqlTransform.query(
        "SELECT * FROM PCOLLECTION WHERE MOD(value, 2) <> 0"));

    // Write the output to a text file
    output.apply(TextIO.write().to("output.txt"));

    pipeline.run().waitUntilFinish();
  }
}

In the code snippet above, we create a Pipeline and set the runner to DirectRunner, which executes the pipeline on the local machine.

We then read the input data from a text file using TextIO, and parse each line into integers using a custom ParseNumbersFn transform.

Next, we apply the Apache Beam SQL query SELECT * FROM PCOLLECTION WHERE MOD(value, 2) <> 0 to filter out even numbers from the input collection.

Finally, we write the output collection to a text file using TextIO.

Conclusion

Apache Beam SQL provides a powerful way to perform query processing on data streams or batch datasets. In this blog post, we explored how to set up Apache Beam SQL with Java and perform query processing using a simple example. As you dive deeper into Apache Beam SQL, you’ll discover a wide range of operations and transformations that can be applied to your data.

#ApacheBeam #Java