How to Install Apache Beam on CentOS?

Installation Steps for Apache Beam:

1.Install Java 8 or later. You can download the Java installer from the Oracle website.

2.Install Python 3.6 or later. You can go to their website to download the Python installer.

3.Install the Apache Beam SDK for Python. You can perform this by running the below

command in a terminal window:

$ pip install apache-beam[gcp]

Once you have installed Apache Beam, you can start writing pipelines.

Here are some of the benefits of using Apache Beam:

?It is a unified model for data processing pipelines.

?It provides a variety of features for data processing, such as batch processing, streaming processing, and machine learning.

?It is free to apply and open-source.

Here are some of the drawbacks of using Apache Beam:

?It can be complex to learn and use.

?It can be slow for some applications, especially those that use a lot of data.

?It is not as popular as some other data processing frameworks, such as Spark

Create a new Apache Beam project in IntelliJ IDEA

1.Open IntelliJ IDEA.

2.Click on the "Create New Project" button.

3. In the "New Project" dialog box, select the "Project" project type and click on the "Next" button.

4. In the "Choose a project SDK" dialog box, select the "Java SDK 1.8" option and click on the "Next" button.

5. In the "Configure Project" dialog box, enter a name for your project and click on the "Finish" button.

Add the Apache Beam SDK to your project

1.Unlock the project in IntelliJ IDEA.

2.In the project window, right-click on the "pom.xml" file and select the "Open Module Settings" menu item.

3.Select the "Dependencies" tab in the "Module Settings" dialog box.

4. Click on the "+" button and select the "Add Library" menu item.

5. In the "Add Library" dialog box, select the "Maven" tab.

6.Enter "org.apache.beam" in the "Group ID" field.

7.Enter "beam-sdks-python-io" in the "Artifact ID" field.

8.Click on the "OK" button.

Write a simple Apache Beam pipeline

$ import apache_beam as beam with beam.Pipeline() as pipeline (pipeline | 'Read data' >> beam.io.ReadFromText('data.txt') | 'Print data' >> beam.io.WriteToText('output.txt')) pipeline.run()

Run your Pipeline

$ pipeline.run()

?Thanks to our interns who participated in this initiative.

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