Apache Beam is an open source, unified programming model for defining and executing parallel data processing pipelines. It's power lies in its ability to run both batch and streaming pipelines, with execution being carried out by one of Beam's supported distributed processing back-ends: Apache Apex, Apache Flink, Apache Spark, and Google Cloud Dataflow. Apache Beam is useful for ETL (Extract, Transform, and Load) tasks such as moving data between different storage media and data sources, transforming data into a more desirable format, and loading data onto a new system.
In Apache Beam training course, you will learn to implement the Apache Beam SDKs in a Java or Python application that defines a data processing pipeline for decomposing a big data set into smaller chunks for independent, parallel processing.
By attending Apache Beam workshop, delegates will learn to:
- Install and configure Apache Beam.
- Use a single programming model to carry out both batch and stream processing from withing their Java or Python application.
- Execute pipelines across multiple environments.
- Experience with Python Programming.
- Experience with the Linux command line.
The Apache Beam class is ideal for: