Apache Spark is a lightning-fast unified analytics engine for big data and machine learning. Since its release, Apache Spark has seen rapid adoption by enterprises across a wide range of industries. Internet powerhouses such as Netflix, Yahoo, and eBay have deployed Spark at a massive scale. It has quickly become the largest open-source community in big data. So, mastering Apache Spark opens a wide range of professional opportunities.

This course starts with an introduction to Apache Spark where you see what Apache Spark is in brief. Then, you will be installing and using Apache Spark. After that, you will look at the Spark execution model and architecture in detail. Next, you will learn the Spark programming model and developer experience. Following that, you will look at the Spark Structured API foundation, and Spark data sources and sinks. Then, you will explore Spark Data frame and dataset transformations along with aggregations in Apache Spark. Finally, you will look at the Spark Data frame joins in detail.

By the end of this course, you will understand Spark programming and apply that knowledge to build data engineering solutions.

All the resource files are uploaded on the GitHub repository at https://github.com/PacktPublishing/Spark-Programming-in-Scala-for-Beginners-with-Apache-Spark-3

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Spis treści

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