In this blog post, we’ll discuss how we’ve improved TokuDB and
PerconaFT fragmented data file performance.
Through our internal benchmarking and some user reports, we have
found that with long term heavy write use TokuDB/PerconaFT
performance can degrade significantly on large data files. Using
smaller node sizes makes the problem worse (which is one of our
performance tuning recommendations when you have faster storage).
The problem manifests as low CPU utilization, a drop in
overall TPS and high client response times during prolonged
checkpointing.
This post explains a little about how PerconaFT structures
dictionary files and where the current implementation breaks
down. Hopefully, it explains the nature of the issue, and how our
solution helps addresses it. It also provides some contrived
benchmarks that prove the solution.
PerconaFT map file disk format
NOTE. …
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