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performanceFeatures or improvements that positively affect seq-db performanceFeatures or improvements that positively affect seq-db performance
Description
For search requests on real seq-db instances there are two major contributors of CPU usage:
- iterating through query tree (left side on the flamegraph)
- reading LID blocks from disk (right side on the flamegraph)
The first part will be addressed through batcher query execution and block skipping. The second part can be partially addressed though lower LID pages. Databases strive to align page size to 4kb which is equal to the minimum amount which can be read from disk.
Pros:
- higher cache granularity and efficiency
- better skipping granurality
- faster performance on search query and histograms
Cons:
- more independent disk reads on aggregations
- more independent read on S3 searches
Most cons can be addressed through intelligent prefetching and repacking fracs before uploading to S3.
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performanceFeatures or improvements that positively affect seq-db performanceFeatures or improvements that positively affect seq-db performance