[Spark基础]-- spark rdd collect操作官方解释

官方原文如下

Printing elements of an RDD

Another common idiom is attempting to print out the elements of an RDD using rdd.foreach(println) or rdd.map(println). On a single machine, this will generate the expected output and print all the RDD’s elements. However, in cluster mode, the output to stdout being called by the executors is now writing to the executor’s stdout instead, not the one on the driver, so stdout on the driver won’t show these! To print all elements on the driver, one can use the collect() method to first bring the RDD to the driver node thus: rdd.collect().foreach(println). This can cause the driver to run out of memory, though, because collect() fetches the entire RDD to a single machine; if you only need to print a few elements of the RDD, a safer approach is to use the take(): rdd.take(100).foreach(println).

 

主要意思是：

打印一个弹性分布式数据集元素，使用时要注意不要导致内存溢出！

建议使用 take(): rdd.take(100).foreach(println)，

而不使用rdd.collect().foreach(println)。

因为后者会导致内存溢出！！