From a code readability perspective, this solution is ugly. It requires dozens of lines of code and four passes through the data. However, we expect that it will avoid memory errors on the executors and complete faster than the `groupByKey` or secondary sort solutions. This is because the data on each column should be mostly distinct doubles, and thus the shuffle should be fairly efficient. The final two `mapPartitions` routines involve reducing the data and can be achieved through iterator-to-iterator transformations, so we expect them to scale well. Indeed, on randomly distributed test data with many records, this solution outperforms the other implementations of the Goldilocks problem by orders of magnitude. (查看原文)
2 有用 核动力蜗牛 2017-03-13 17:35:48
在书没有正式出版前，就阅读了该书的初稿。这是一本非常不错的Spark进阶书籍。该书主要涉及spark-core和spark-sql两部分，主要从性能的角度去分析Spark的功能及使用。该书篇幅不多，没有像国内很多Spark书籍大段大段贴源码的情况。
0 有用 阿凡达弟弟 2022-05-31 11:34:33
吃透那几个例子对spark理解算是非常深入了。
0 有用 眼霜 2019-08-23 19:23:23
确实牛逼
0 有用 darcy27149 2020-04-15 22:59:12
觉得比Spark权威指南稍差一点，第六章的goldilocks的例子不错。
0 有用 我霸天君不服 2023-05-17 00:42:08 四川
翻译垃圾，纯机器翻译。内容也一般，没讲什么东西