Product @ ClickHouse Thinking about agentic experience & identity

Joined April 2015
1/5 ClickHouse 26.10 can reduce hash-table memory for large GROUP BY and uniqExact queries by leaving fewer slots empty. Load factor means the fraction of allocated slots that hold keys.
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4/5 The trade-off is extra CPU work for inserts and lookups. Highly parallel queries waiting on random memory access can benefit. With fewer threads, that extra work can make queries slower.
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5/5 This covers large two-level GROUP BY tables, uniqExact sets and parallel hash joins. StringHashMap is unchanged. Buffers grow in steps, so savings depend on key count. Other query allocations still need memory.
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1/5 ClickHouse 26.10 adds friendlier functional syntax for array transformations. With lower | reverse, the order you read matches the order the functions run, with less nesting and less counting brackets.
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3/5 Placeholders make short lambdas smaller too. arrayMap(plus(_, 1) | multiply(_, 2), [1, 2, 3]) gives [4, 6, 8], adding 1 then multiplying by 2. _1 and _2 can refer to separate arguments.
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4/5 This is syntax sugar over ordinary lambdas, rewritten by the analyser during query analysis, so normal typing, captures and constant folding still apply. Generated argument names avoid accidental capture.
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1/5 ClickHouse 26.10 has an experimental columns cache. It keeps columns after decompression and deserialization, so another query can reuse the in-memory column objects.
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4/5 For MergeTree, it currently covers wide parts in databases with table UUIDs. Compact parts do not use it. use_columns_cache = 1 enables it explicitly; the feature is experimental and off by default.
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5/5 Inspect system.columns_cache and ColumnsCacheHits / ColumnsCacheMisses. Compare warm queries with the cache on and off. Cache lookups and memory traffic can outweigh the decoding work they save.
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We are live with the 26.10 ClickHouse Release call! Join us, on youtube or LinkedIn youtube.com/watch?v=k30ikPXN… (a thread)
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ClickHouse 26.10 release call today. Lots of JOIN work in this one! I’ll share my highlights after the call. c.house/2610ReleaseCall
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Al Brown retweeted
Replying to @alexatallah
Last week I was on a sales call with TiDB. We were thinking of using it for an upcoming product launch. After they ran through their pitch I asked them specifically about day-to-day security measures they take. They couldn't really answer. Went with ClickHouse.
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Anthropic enters the personal assistant race with Claude Duet, built on Opus 5.5. The best model right now, for me, so I’m here for it. A couple of weeks with OpenAI’s dot has been reasonably useful, but no game-changing use cases yet. claude.com/resources/article…
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1/6 ClickHouse is a launch partner for @Cloudflare OS, with an integration for working with live ClickHouse data. I've been digging into the wider app model, especially how people can share an app and personalise their own copies with AI.
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5/6 There's an interesting attempt to solve the maintenance problem too. Personalised software means taking responsibility for the features you added and everything that came with the app, including bugs and security fixes.
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