Top Apache Beam Interview Questions (2024)

1. What is Apache Beam?

2. What is Pipeline in Apache Beam?

3. What is PCollection in Apache Beam?

4. What is PTransform in Apache Beam?

5. How multiple transforms process the same PCollection in Apache Beam?

6. What is Apache Beam SDKs?

7. Is Apache beam ETL?

8. What is Bounded and Unbounded PCollection in Apache Beam?

9. What is Apache Beam Pipeline Runners?

10. Which are the supported runners in Beam?

11. What are Timestamps in Apache Beam?

12. What are Watermarks in Apache Beam?

Q: What is Apache Beam?
Ans:

Apache Beam is a unified open-source framework for defining batch and streaming data parallel processing pipelines. The Apache Beam programming model makes large-scale data processing easier to understand. You can create a programm that defines the pipeline using one of the Apache Beam SDKs.

Q: What is Pipeline in Apache Beam?
Ans:

A pipeline contains the whole data processing task from beginning to end. Reading, manipulating, and writing output data are all part of this process. Pipelines must be created by all Beam driver programmes. You must also define the execution parameters when you establish the Pipeline, which inform the Pipeline where and how to run.

// Start by defining the options for the pipeline.
PipelineOptions options = PipelineOptionsFactory.create();

// Then create the pipeline.
Pipeline p = Pipeline.create(options);

A linear flow of operations is represented by the simplest pipelines. A linear pipeline begins with a single input collection, performs three transforms successively, and concludes with a single output collection.

Sometimes pipeline, on the other hand, may be considerably more complicated. A pipeline is a series of stages represented by a Directed Acyclic Graph. It supports multiple input sources and output sinks, and its operations (PTransforms) can read and write multiple PCollections.

Q: What is PCollection in Apache Beam?
Ans:

Beam pipeline uses a PCollection to represent a distributed data set. The data set might be bounded, which means it comes from a fixed source such as a file, or unbounded, which means it comes from a constantly updating source such as a subscription or another mechanism. A PCollection is normally created by reading data from an external data source, but you may also generate a PCollection from in-memory data in your driver application. PCollections are then used as the inputs and outputs for each step of pipeline.

 // Create the PCollection 'lines' by applying a 'Read' transform.
    PCollection<String> lines = pipeline.apply(
      "ReadInputFile", TextIO.read().from("c://tecjgeeknext/files/input.txt"));

Q: What is PTransform in Apache Beam?
Ans:

In pipeline, a PTransform represents a data processing operation, or a step. Each PTransform takes one or more PCollection objects as input, applies a processing function to the PCollection's elements, and returns zero or more PCollection objects as output.

Q: How multiple transforms process the same PCollection in Apache Beam?
Ans:

Without consuming or modifying the input, you can use the same PCollection as input for several transforms. As shown in the below diagram , pipeline builds a PCollection of table rows from its input (first names represented as texts) from a database table. The pipeline then performs several transformations on the same PCollection. Transform A extracts all names in the PCollection that begin with the letter "A," while Transform B extracts all names in the PCollection that begin with the letter "B." PCollection is the same for both transforms A and B.

Program which reads single input and applies two transforms.

PCollection<String> dbRowCollection = ...;

PCollection<String> aCollection = dbRowCollection.apply("aTrans", ParDo.of(new DoFn<String, String>(){
  @ProcessElement
  public void processElement(ProcessContext c) {
    if(c.element().startsWith("A")){
      c.output(c.element());
    }
  }
}));

PCollection<String> bCollection = dbRowCollection.apply("bTrans", ParDo.of(new DoFn<String, String>(){
  @ProcessElement
  public void processElement(ProcessContext c) {
    if(c.element().startsWith("B")){
      c.output(c.element());
    }
  }
}));

Q: What is Apache Beam SDKs?
Ans:

The Beam SDKs provide an uniform programming model for representing and transforming data sets of any size, even if the input is a finite data set from a batch data source or an infinite data set from a streaming data source. Beam SDKs utilise the same classes to represent bounded and unbounded data, as well as the same transforms to manipulate it. Using the Beam SDK of our preference, we can create a program that defines our data processing pipeline.

The language-specific SDKs that Beam presently supports are:

Apache Beam Java SDK Java Apache Beam Python SDK Python Apache Beam Go SDK Go logo

Q: Is Apache beam ETL?
Ans:

Apache Beam is an open source unified programming model for defining and executing data processing pipelines, such as ETL, batch, and stream (continuous) processing.

Q: What is Bounded and Unbounded PCollection in Apache Beam?
Ans:

1. Bounded is finite and like in batch use cases.
2. Unbounded could never end, like in streaming use cases.

These are based on batch and stream processing intuitions, however in Beam, the two are combined, and bounded and unbounded PCollections can coexist in the same pipeline. You'll need to reject pipelines that contain unbounded PCollections when your runner can only support bounded PCollections.

Q: What is Apache Beam Pipeline Runners?
Ans:

The Beam Pipeline Runners convert the data processing pipeline user define in the Beam program into an API that can be used with the user's preferred distributed processing back-end. When we run the Beam program, we will need to select a runner for the back-end where our pipeline will be executed.

Q: Which are the supported runners in Beam?
Ans:

The following runners are currently supported by Beam:

1. Direct Runner
2. Apache Flink Runner
3. Apache Nemo Runner
4. Apache Samza Runner
5. Apache Spark Runner
6. Google Cloud Dataflow Runner
7. Hazelcast Jet Runner
8. Twister2 Runner