Ryan

@ryansmith

130 Following

3815 Followers

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People who are really serious about coffee should mineralize their own water.

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Most queries in Snowflake / Redshift scan only 100MB of data! https://www.fivetran.com/blog/how-do-people-use-snowflake-and-redshift

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Excellent paper on the pitfalls of MMAP files for DBMS workloads. I've personally reached for the MMAP silver bullet and it didn't work out for me and this paper helped me understand why. Great read! A++ https://db.cs.cmu.edu/mmap-cidr2022/

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Just discovered Bundlephobia! Neat site for checking size / impact of an NPM package. https://bundlephobia.com/package/@indexsupply/indexsupply.js

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It's fun and telling to look at these sparklines

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http://stopjava.com lol

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People aren't ready to hear that you can solve most problems with a little thinking and a little SQL.

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You know the old expression: You don't get fired for buying IBM? The expression is a little dated but you could probably make similar statements today; like: You don't get fired for building a web app in React. What are examples of the expression's antonym? You certainly could get fired for building your web app in Haskell.

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UPDATE heavy workloads on PG are known to scatter rows around on pages which may increase IO when scanning many rows in a single query. Unless you are getting 100% HOT updates (most aren't). To solve this in the past, I've used CLUSTER -- which isn't great because it requires a lock and takes a long time. It's almost unusable. pg_repack solves this by doing online re-clustering and storage reclamation. https://reorg.github.io/pg_repack/

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https://www.cs.cmu.edu/~pavlo/blog/2023/04/the-part-of-postgresql-we-hate-the-most.html Spoiler: MVCC This also helps bring awareness to the impact of UPDATE heavy workloads on PG

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I wonder what is going on when I add a seat to my github account. It does in fact take a while -- 58s in my case.

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A rebuttal to Uber’s PG/MySQL paper. Keep in mind, PG has changed since this discussion. A lot of the replication issues are long since put to rest. The storage sub-systems are the interesting point of difference between these systems. MYSQL’s indexes point to primary keys instead of a CTID. An update to a MySQL row will have same storage location but PG will be a new CTID/page — unless it was a Heap Only Tuple (HOT) update. But this means PG can reduce IO for queries. As with anything, it’s always a tradeoff. However, database systems in particular are especially sensitive to workload details. The tradeoffs really matter! https://thebuild.com/presentations/uber-perconalive-2017.pdf

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I've been working on a TS client for @indexsupply. Coming soon (or now if you sleuth the GH account)

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I was having some issues getting my @indexsupply transactional emails delivered timely. I found this absolutely cracked email guy https://www.helloinbox.email who helped me figure it out. (problem was part dns and part message formatting) would highly recommend if you want to speed run your email issues

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I'm tempted to run @indexsupply on FreeBSD. It's long since been known for its networking stack (netflix) and it ships with ZFS.

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Another smooth launch (mostly. had a bit of latency from a remote node) on @indexsupply. It's fun to have a dialed stack where new traffic can be handled without any intervention or fuss. I'm living the sysadmin's dream.

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I love a good manual. ZFS continues to be amazing!

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Legendary hacker @okwme (who has strange casts) shipped a fun new thing: https://kudzu.christmas

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