MapReduce, every mention

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Verbatim, from the transcripts: the passages where MapReduce comes up

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▶ 20:58 M.C. Srivas We introduced JSON to Hadoop and Spark and in MapReduce and in Hive and everywhere.

▶ 1:16 Stefan Groschupf That's why we looked into the Google papers and implemented MapReduce and the HDFS, et cetera, et cetera.
▶ 4:38 Stefan Groschupf and then we built a MapReduce thing, and then, um, Peter Thiel, not sure, who knows Peter Thiel? 2 times in the scene
▶ 12:07 Stefan Groschupf Replacing MapReduce with TES or with Spark is really straightforward, um, especially if you use BI on top of Hadoop, um, because it basically automatically does it for you, but obviously you can't just rip out hardware and replace it,…

▶ 4:19 Oren Falkowitz Maybe, you know, eight or nine years since Google published the Bigtable paper and the MapReduce paper and some of those early big data papers which have spawned, you know, this community and all the great technological revolution, now…

▶ 6:25 Matt Turck Uh, can you, uh, maybe help us understand, um, so this HDFS, which is the storage, uh, and MapReduce, which is, uh, the processing, 4 times in the scene
▶ 7:24 Matt Turck Yes, so perhaps more specifically, can you go through the, the, the key advantages of Spark over MapReduce? 4 times in the scene

▶ 5:16 Paul Dix This is the key thing that we learned from Hadoop and Google's MapReduce framework, which is
▶ 19:19 Paul Dix So under the covers, we basically have our own MapReduce implementation that's,

▶ 18:24 Chris Wiggins Elastic MapReduce, proper MapReduce in Java. 2 times in the scene

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