具体描述
Ready to unleash the power of your massive dataset? With the latest edition of this comprehensive resource, you'll learn how to use Apache Hadoop to build and maintain reliable, scalable, distributed systems. It's ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. This third edition covers recent changes to Hadoop, including new material on the new MapReduce API, as well as version 2 of the MapReduce runtime (YARN) and its more flexible execution model. You'll also find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. * Store large datasets with the Hadoop Distributed File System (HDFS), then run distributed computations with MapReduce * Use Hadoop's data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence * Discover common pitfalls and advanced features for writing real-world MapReduce programs * Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud * Use Pig, a high-level query language for large-scale data processing * Analyze datasets with Hive, Hadoop's data warehousing system * Load data from relational databases into HDFS, using Sqoop * Take advantage of HBase, the database for structured and semi-structured data * Use ZooKeeper, the toolkit for building distributed systems
作者简介
目录信息
读后感
很多地方翻译的不行，需要对照英文看才能明白。。。不过对于快速学习，仍然是不错的选择。建议译者看看每部分内容的重要性，不重要的瞎翻翻就算了，重要的部分还是好好花点功夫，不要本末倒置了。比如第三章的数据流部分，这么经典的地方居然被翻译烂的一塌糊涂。不知道译者会...
评分详见：http://www.cnblogs.com/aprilrain/archive/2013/03/07/2947664.html
评分其实也不算全部读完了，读它主要是为了技术选型，考虑升级持久层架构、提高系统可扩展性，仔细研读了前几章，对Hadoop、MapReduce、HDFS的模型、机制、使用场景有了一定了解。后面几章及其生态圈内的其他项目抱着了解的心态简单浏览了一下。整体感觉还行，至少从我看过的章节来...
评分用户评价
这书到后面已经神游了，没这环境先不玩
评分很细致，跟着入门一遍。对这种快速演进的技术，还是老老实实看原版吧..中文版落后太多，等新翻译出来黄花菜都凉了
评分中英结合疗效好，不过还是建议中文为主，英文为辅。
评分很细致，跟着入门一遍。对这种快速演进的技术，还是老老实实看原版吧..中文版落后太多，等新翻译出来黄花菜都凉了
评分这书到后面已经神游了，没这环境先不玩
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