The Exchanges

Every argument clarity score on this site is built from rows on this page. Each question and answer was assessed with names hidden, the host's own answers included, on four things from 1 to 5: directness (does it answer the question asked), coherence (do the ideas follow), precision (concrete details and clear references), compression (says a lot per word). The weighted mix (30/30/25/15) is the exchange score. A person's published score averages their exchange scores on raw tape only, at least 8 of them, shrunk toward the cohort mean. Full method →

Ion Stoica no published score: only 1 usable exchange on raw tape, and a fair score needs 8+ record → ← everyone

Every exchange below was scored with names hidden, four dimensions each from 1 to 5. An exchange's score is 0.30·directness + 0.30·coherence + 0.25·precision + 0.15·compression. The published score averages the raw tape exchange scores and shrinks small samples toward the cohort mean, so five great answers can't beat twenty good ones. Produced feed rows count only toward coarse estimates, never toward a full score.

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Answered raw tape D 4 · C 4 · P 4 · Cm 3 3.85

Q Um, and, uh, maybe one last question from me. What is the, uh, relationship between Databricks and the Spark community specifically? Uh, what percentage of, uh, the contribution do you think are, uh, produced by Databricks as opposed to the rest of the community?

A Yeah, so right now we have a great community where we have, ah, we exceeded 500 contributors. Um, it is the most active big data project right now, Spark. Ah, and a lot of contributions, still the majority of contributions comes from Databricks. And, ah, from the Databricks, you know, it's, ah, Uh, as a strategy, you know, it's, it's a two-step strategy. Like, like, first step, just to be very clear, we want Apache Spark to be highly successful. Uh, and everyone to use it. The more people use it, you know, the more potential customers have for the Databricks cloud. Uh, we don't have our own distribution. We provide only the service. And therefore, we partners, we collaborate with everyone, and we help everyone who wants to distribute Spark. Also, we, ah, try pretty hard, ah, in order to, ah, fuel the growth of the ecosystem. Ah, so we have certification programs, both for the application and for the distribution. So therefore, you know, every certified application will run on any certified SPAR distribution. Ah, this is also, will alleviate the risk of fragmentation. Ah, So, you know, really we do a lot of work and we spend a lot of resources for making Apache Spark successful.

AI assessment note: “still the majority of contributions comes from Databricks”

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