Apache Hadoop YARN, every mention

7 scenes (2015) · ← back to Apache Hadoop YARN

tap a year for its mentions
00133255201320142015episodesmentions
035201320142015episodes it came up in
002.52.555201320142015episodesmentions per episode

every year 2015 anyone Stefan Groschupf 11M.C. Srivas 6Ion Stoica 2Vaclav Petricek 1Shant Hovsepian 1Nick Mehta 1Mike Olson 1

Verbatim, from the transcripts: the passages where Apache Hadoop YARN comes up

loading…

10 Commandments for BI in Big Data, Shant Hovsepian, Arcadia Data (Data Driven NYC / FirstMark) Dec 17, 2015 · 1 mention

  • ▶ 6:56 Shant Hovsepian Thanks to things like Yarn, Mesos, we're seeing a whole new resurgence of operating systems.

B2B Big Data Challenges, Nick Mehta, Gainsight (Data Driven NYC / FirstMark Capital) Dec 17, 2015 · 1 mention

  • ▶ 1:02 Nick Mehta You've, you still have Yarn, you still have Mesosphere, you have MapR, you have Hadoop, but unfortunately you also have salespeople, right, that actually have to act on all this stuff, and that's the biggest challenge, and I'm going to…

A Fireside Chat with MapR CTO M.C. Srivas (Data Driven NYC / FirstMark) Dec 17, 2015 · 6 mentions

  • ▶ 23:24 M.C. Srivas So you have this funky thing where, you know, Impala is controlled by one company, Yarn is controlled by one company, or, or, uh, now Kudu or something.
  • ▶ 34:40 M.C. Srivas I think he meant Yarn. 5 times in the scene

The Acceleration of Innovation in Big Data w/ Stefan Groschupf, Datameer Dec 17, 2015 · 11 mentions

Ion Stoica, Databricks // Creating Apache Spark // Data Driven NYC (FirstMark Capital) Apr 2, 2015 · 2 mentions

  • ▶ 6:48 Ion Stoica Then you have this kind of resource management layer, it's YARN, and then you have the NG, or a computation layer, which is, uh, Hadoop Reduce. 2 times in the scene
Made with StarZero

Turn any episode into a week of clips.

This entire site, over 400 conversations transcribed, diarized, checked and made playable, runs on the StarZero media pipeline. Drop in your own episode and the podcast clipper finds the moments worth sharing, cuts them, captions them, and reframes them for every feed.