Learning spark:lightning-fast Big Data analysis Chinese Translation

Learning spark:lightning-fast Big Data Analysis Chinese translation behavior is purely personal interest in Spark and is for learning only.

If my translation violates your copyright, please inform me that I will stop open source translation of this book.

Translation The Book of Learning Spark:lightning-fast Big Data analysis was only for Spark developer educational purposes. If I violated your copyright, please let me know.

Learning Spark English Original

Learning spark:lightning-fast Big Data Analysis http://shop.oreilly.com/product/0636920028512.do

The coupon code for this book (promo Code:bworm) is posted on the Databricks website, so don't forget to use save money when you buy it. Https://databricks.com/spark/developer-resources

Chinese translation

Github:https://github.com/gaoxuesong/learning-spark-lightning-fast-big-data-analysis

gitbook:http://xuesong.gitbooks.io/learningspark/

Gitbook is a tool for building beautiful books using Git and Markdown. It can generate your book in multiple formats: PDF, ePub, mobi or as a website.

On GitHub, we share a PDF version of the Chinese translation and the source of the original book, and Gitbook can share various file formats for Chinese translation (PDF, EPub, Mobi and website).

The current translation of this book is determined by my spare time and interest, and it is impossible to predict the end time and schedule of the translation. In addition, the translation of this book focuses only on the technical part, so the translation begins with Chapter Ii.

Examples for Learning Spark

Codes https://github.com/gaoxuesong/learning-spark/forked from Https://github.com/databricks/learning-spark

About the orignal Author

About the orignal Author

Holden Karau is a software development engineer at Databricks and was active in open source. She is the author of a earlier Spark book. Prior to Databricks she worked on a variety of search and classification problems at Google, Foursquare, and Amazon. She graduated from the University of Waterloo and a Bachelors of Mathematics in computer science. Outside of software she enjoys playing with fire, welding, and hula hooping.

Most recently, Andy Konwinski co-founded Databricks. Before that he is a PhD student and then postdoc in the Amplab at UC Berkeley, focused on large scale distributed Computi ng and cluster scheduling. He co-created and is a committer on the Apache Mesos project. He also worked with systems engineers and researchers at Google on the design of Omega, their next generation cluster Sche Duling system. More recently, he developed and led the AMP Camp Big Data bootcamps and first Spark Summit, and have been contributing to T He Spark project.

Patrick Wendell is an engineer at Databricks as well as a Spark committer and PMC member. In the Spark project, Patrick had acted as release manager for several spark releases, including Spark 1.0. Patrick also maintains several subsystems of Spark ' s core engine. Before helping start Databricks, Patrick obtained a M.S. In computer science at UC Berkeley. His and focused on low latency scheduling for large scale analytics workloads. He holds a B.S.E in computer science from Princeton University

Matei Zaharia is the creator of Apache for Spark and CTO at Databricks. He holds a PhD from UC Berkeley, where he started Spark as a project. He now serves as it Vice president at Apache. Apart from Spark, he have made, and open source contributions to other projects in the cluster computing area, incl uding Apache Hadoop (where he's a committer) and Apache Mesos (which he also helped start at Berkeley).

Learning spark:lightning-fast Big Data analysis Chinese translation