Essential Knowledge: Parallel Programming
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At the heart of any big data system is a plethora of processes and algorithms that run in parallel to crunch data and produce results that would have taken ages if they were run in a sequential manner. Parallel computing is what enables companies like Google to index the Internet and provide big data systems like email, video streaming, etc. Once workloads can be distributed effectively over multiple processes, scaling the processing horizontally becomes an easier task. In this chapter, we will explore how to parallelize work among concurrent processing units; such concepts apply for the most part whether said processing units are concurrent threads in the same process, or multiple processes running on the same machine or on multiple machines. If you haven’t already read about process management and scheduling in Sect. 3.4 of Chap. 3, now would be a good time to visit that.
KeywordsThread Pool String Args Reentrant Locks Chun KS Throws InterruptedException
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