Download Apache Spark in 24 Hours, Sams Teach Yourself PDF EPUB
Author: Jeffrey Aven
Pages: 592
Size: 1.354,29 Kb
Publication Date: August 27,2016
Category: Data Mining
Apache Spark is an easy, scalable, and flexible open up supply distributed processing engine for big data systems and is probably the most active open up source big data tasks to date. “DO YOU REALIZE?
This book’s simple, step-by-step approach demonstrates how to deploy, plan, optimize, manage, integrate, and extend Spark–today, and for a long time to come. You’ll learn how to create effective solutions encompassing cloud processing, real-period stream digesting, machine learning, and even more.
Learn to
• Uncover what Apache Spark will and how it matches in to the Big Data scenery
• Deploy and operate Spark locally or in the cloud
• Connect to Spark from the shell
• Take full advantage of the Spark Cluster Architecture
• Develop Spark applications with Scala and useful Python
• Plan with the Spark API, including transformations and activities
• Apply useful data engineering/analysis approaches created for Spark
• Make use of Resilient Distributed Datasets (RDDs) for caching, persistence, and result
• Optimize Spark solution overall performance
• Make use of Spark with SQL (via Spark SQL) and with NoSQL (via Cassandra)
• Leverage cutting-edge functional programming methods
• Extend Spark with streaming, R, and Sparkling Drinking water
• Begin to build Spark-structured machine learning and graph-digesting applications
• Explore advanced messaging systems, which includes Kafka
• Preview and plan Spark’s next era of improvements
Guidelines walk you through common queries, issues, and jobs; In only 24 lessons of 1 hour or much less, Sams Train Yourself Apache Spark in a day can help you build useful Big Data solutions that leverage Spark’s amazing speed, scalability, simpleness, and versatility.” tips present insider tips and shortcuts;
“ alerts assist you to avoid pitfalls. By enough time you're finished, you'll end up being comfortable using Apache Spark to resolve a wide spectral range of Big Data problems. and “LOOK OUT!