Spark Launcher 进程阻塞问题

Spark Launcher是一个很好的spark job提交工具，但是有时候会发现提交spark job之后会一直等待，将spark launcher这个进程kill 之后发现spark job状态从RUNNING变成FINISHED了，其实这个是否并非是等待spark job,而是因为进程发生了阻塞。

Spark Launcher 其实也是用了Java 的 ProcessBuilder,经过查阅发现答案在这里。
文档中也标注了：
By default, the created subprocess does not have its own terminal or console. All its standard I/O (i.e. stdin, stdout, stderr) operations will be redirected to the parent process, where they can be accessed via the streams obtained using the methods getOutputStream(), getInputStream(), and getErrorStream(). The parent process uses these streams to feed input to and get output from the subprocess. Because some native platforms only provide limited buffer size for standard input and output streams, failure to promptly write the input stream or read the output stream of the subprocess may cause the subprocess to block, or even deadlock.

尤其要注意的是，在Spark Launcher中，spark的INFO都是在 errorStream里。

所以在 spark输出的时候，要开子线程来读取buffer里面的内容，以免将buffer填满，导致进程阻塞。