I’m personally very excited by this work. Compaction could do with a spring clean and this feels to formalise things much more cleanly, but density tiering in particular is something I’ve wanted to incorporate for years now, as it should significantly improve STCS behaviour (most importantly reducing read amplification and the amount of disk space required, narrowing the performance delta to LCS in these important dimensions), and simplifies re-levelling of LCS, making large streams much less painful. On 21 Dec 2022, at 07:19, Henrik Ingo <henrik.i...@datastax.com> wrote:
I noticed the CEP doesn't link to this, so it should be worth mentioning that the UCS documentation is available here: https://github.com/datastax/cassandra/blob/ds-trunk/doc/unified_compaction.md
Both of the above seem to do a poor job referencing the literature we've been inspired by. I will link to Mark Callaghan's blog on the subject:
Finally, it's perhaps worth mentioning that UCS has been in production in our Astra Serverless cloud service since it was launched in March 2021. The version described by the CEP therefore already incorporates some improvements based on observed production behaviour.
Henrik Hello everyone,
I would like to open the discussion on our proposal for a unified compaction strategy that aims to solve well-known problems with compaction and improve parallelism to permit higher levels of sustained write throughput.
The strategy is based on two main observations:
- that tiered and levelled compaction can be generalized as the same thing if one observes that both form exponentially-growing levels based on the size of sstables (or non-overlapping sstable runs) and trigger a compaction when more than a given number of sstables are present on one level;
- that instead of "size" in the description above we can use "density", i.e. the size of an sstable divided by the width of the token range it covers, which permits sstables to be split at arbitrary points when the output of a compaction is written and still produce a levelled hierarchy.
The latter allows us to shard the compaction space into progressively higher numbers of shards as data moves to the higher levels of the hierarchy, improving parallelism, space requirements and the duration of compactions, and the former allows us to cover the existing strategies, as well as hybrid mixtures that can prove more efficient for some workloads.
Thank you, Branimir
|
