Apache Arrow, every mention

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the MAD Podcast 31

Verbatim, from the transcripts: passages where Apache Arrow comes up on the MAD Podcast

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▶ 33:55 Tomasz Tunguz Then you have the iceberg, uh, compute of, uh, separation of compute and storage where the biggest companies really want to keep their data on their own systems and then use iceberg and Parquet and Arrow as a specific format, uh, and then…

▶ 0:08 Julien Le Dem Yeah, so I'm going to talk about, um, open lineage, and I think in that case, we took a page from the Arrow playbook, and really into, um, how we build a community, and then, like, this is the kind of thing that, um, there's a real need…
▶ 6:05 Julien Le Dem Uh, and really we took a page off the Arrow playbooks. 3 times in the scene
▶ 27:05 Julien Le Dem There's a need for a standard, so let's, we're creating a focal point where everybody can contribute, and we're all collaborating together, and this, like, you know, like, Arrow took five years to get where it is, and now it's really clear…

▶ 7:58 Matt Turck Your focus for the last few years has been Arrow.
▶ 13:22 Matt Turck And so how does Arrow work and how does it solve the problem?
▶ 15:18 Matt Turck So our, uh, as a very strategic place in the ecosystem in, in that precisely enable all those pieces to, to work together. 7 times in the scene
▶ 17:55 Wes McKinney So, uh, yeah, I mean, the back story is, uh, you know, 2016, uh, Arrow started, um, I, I moved from, uh, from, from Cloudera to Two Sigma. 10 times in the scene
▶ 21:50 Wes McKinney Spark, uh, Spark supports Arrow as a, as an interchange format, and it's used heavily in the interface with Python and R, for example. 4 times in the scene
▶ 23:16 Wes McKinney So, you know, the folks from Nvidia, um, have a large team building the, the rapids project, which is, uh, uh, CUDA based, uh, uh, computing, uh, against arrow data.

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