Learning Spark: Lightning-Fast Big Data Analysis 中文翻译

Learning Spark: Lightning-Fast Big Data Analysis 中文翻译行为纯属个人对于Spark的兴趣，仅供学习。

如果我的翻译行为侵犯您的版权，请您告知，我将停止对此书的开源翻译。

Translation the book of Learning Spark: Lightning-Fast Big Data Analysis is only for spark developer educational purposes. If I violated your copyright, please let me know.

 

Learning Spark 英文原版

Learning Spark: Lightning-Fast Big Data Analysis  http://shop.oreilly.com/product/0636920028512.do

在 databricks 官网上发布了此书的优惠码（promo code: BWORM），在购买时别忘了使用省银子。 https://databricks.com/spark/developer-resources

 

中文翻译

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.

GitHub上分享了中文翻译的PDF版和原书源码，GitBook则可分享中文翻译的多种文件格式（PDF, ePub, mobi and website）。

目前此书的翻译进度由我的业余空余时间和兴趣所决定，无法预知翻译的结束时间和进度表。另外对于此书的翻译只关注技术部分，因此翻译从第二章开始。

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 is active in open source. She is the author of an 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 with 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 was a PhD student and then postdoc in the AMPLab at UC Berkeley, focused on large scale distributed computing 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 scheduling system. More recently, he developed and led the AMP Camp Big Data Bootcamps and first Spark Summit, and has been contributing to the Spark project.

Patrick Wendell is an engineer at Databricks as well as a Spark Committer and PMC member. In the Spark project, Patrick has 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 an M.S. in Computer Science at UC Berkeley. His research 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 Spark and CTO at Databricks. He holds a PhD from UC Berkeley, where he started Spark as a research project. He now serves as its Vice President at Apache. Apart from Spark, he has made research and open source contributions to other projects in the cluster computing area, including Apache Hadoop (where he is a committer) and Apache Mesos (which he also helped start at Berkeley).