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bear in mind that Clikchouse will quickly fall short when squeezed into traditional star schema model (it's very inefficient on multiple joins, probably even ca
by haddr 5y ago
bear in mind that Clikchouse will quickly fall short when squeezed into traditional star schema model (it's very inefficient on multiple joins, probably even can't handle more than 1 at the same time). You would really need a dabase engine that is columnar first but still operate on SQL without too much hidden pitfalls, and that is quite often challenging
- dreyfan 5y agoYes in Clickhouse you’d generally take a denormalized approach.
- hodgesrm 5y agoClickHouse can handle multiple joins just fine and has for a while. I just gave a conference talk on CH this morning that discussed this exact topic, among others. The fact is that for large datasets scans on denormalized fact tables parallelize well, which means you can (a) offer stable performance and (b) scale more efficiently. This is important for use cases like web analytics, where users play around with different dimensions and measures but still expect consistent response. Note also, dimensions for things like Year, Month, Week, and the like compress absurdly well. It is often way faster to scan these values than to join them.