Apache Spark with Java – Hands On! Course
Learn how to slice and dice data using Apache Spark, the next-generation big data technology!
What you’ll learn
Apache Spark with Java – Hands On! Course
- To solve big data problems, use the most capable big data batch and stream processing engine.
- Master the new Spark Java Datasets API to quickly slice and dice large amounts of data.
- Create, deploy, and run Spark jobs in the cloud, and compare performance across different hardware configurations.
- Optimize Spark clusters to work efficiently with massive data and gain a better understanding of performance optimization.
- Spark SQL, Dataframes, and Datasets can be used to transform structured and semi-structured data.
- Linear Regression, Logistic Regression, and K-Means Clustering are examples of common Machine Learning techniques that can be implemented in Sparks.
Requirements
- A basic understanding of Java programming is necessary. There’s also a crash course on Java 8 lambdas.
A personal computer with an internet connection is required.
The software you’ll need for this course is absolutely free, and I’ll show you how to install it on your computer.
Description
It’s been updated!
Apache Spark is a batch and stream processing engine for the future generation. Its popularity has soared in recent years, and having this technology on your resume is genuinely transformative. Currently, over 3000 firms are utilizing Spark in production, and the number is rapidly expanding! Some of the things you’ll learn are listed below:
- How to use Spark SQL Dataframes to create Spark Java Applications.
- Understand the inner workings of the Spark Standalone cluster.
- In Spark Java, learn how to slice and dice your data using various transformations.
- When working with Spark Datasets, how to marshall and unmarshall Java domain objects (pojos).
- Ingest data of multiple sizes and file formats using master joins, filters, aggregations, and ingest data of various sizes and file formats (txt, csv, Json etc.).
- Analyze over 18 million real-world Reddit comments to determine the most popular words.
- Create programs to stream stock market index files using Spark Streaming.
- Stream messages and network sockets queued in a Kafka cluster.
- Learn how to use Spark MLlib to create the most popular machine learning algorithms.
- Linear Regression, Logistic Regression, and K-Means Clustering are among the most widely used algorithms.
Who this course is for:
- Anyone who wants to add this highly desirable technology to their portfolio as a Java developer.
- Who wants to work in the field of data science?
- Anyone interested in learning more about big data.
- Anyone who wishes to use Spark to implement machine learning algorithms.
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