Summary
In this chapter, we discussed Hadoop MapReduce performance tuning and learned how application developers and cluster administrators can tune Hadoop in order to enhance the MapReduce job's performance.
We learned about most configuration variables related to CPU, disk I/O, memory and network utilization and discussed how these variables may affect the MapReduce job's performance.
Then, we learned about Hadoop metrics and suggested some open source monitoring tools, which enhance the Hadoop monitoring experience and are very handy to Hadoop cluster administrators and application developers.
In the next chapter, we will learn how to identify resource bottlenecks based on performance indicators and also learn about common performance tuning methods. ...
Get Optimizing Hadoop for MapReduce now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
