MapReduce Design Patterns: Building Effective Algorithms and Analytics for Hadoop and Other Systems

by Donald Miner

MapReduce Design Building Effective Algorithms and Analytics for Hadoop and Other Systems

Genres: Programming, Computer Science, Software, Nonfiction, Technical, Computers, Technology

Paperback

First published September 22, 2012

Reviews

[Rinat Sharipov · Rating 5 out of 5]

Big data engineer’s handbook

[Alexei · Rating 4 out of 5]

A very good primer on the bread-and-butter techniques of using Hadoop (also applicable to other MR platforms). Some patterns like filtering are infuriatingly simple, but you'll benefit from knowing the caveats of others, and from charting the MapReduce problem space that these patterns address.

I wish this book covered approximations more, like mentioning that you can do a count distinct query with HyperLogLog, but unfortunately it only ever deals with using Bloom filters for reducing bandwidth requirements of reduce-side joins. Also, something relating to graph processing would be nice to see, because it's such a rich problem domain and knowing how to address it with MapReduce would be very nice.

[Radheshyam · Rating 5 out of 5]

ewrw

[Varun]

grt

[Delhi Irc]

Location: ND6 IRC
Accession No: DL027413

[TN · Rating 4 out of 5]

It is a generally good book. I found most of the patterns well presented. However, a bit more on possible implications and comparisons will be very useful.