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Balancing Database Storage Latency And Throughput

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Balancing Database Storage Latency And Throughput
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PostgreSQL for Secure Enterprises
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31
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CC Attribution 3.0 Unported:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Production PlaceOttawa, Canada

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Abstract
by Greg Smith The easiest type of benchmark to run on a database is checking its throughput: the total transactions processed during some period of time. But throughput isn't what application users care about. They want low latency. Latency and throughput have a complex dependency on each other, and you'll need a whole new type of test to balance them well. Recent advances in benchmarking tools, like the rate limit in pgbench 9.4, make it possible to analyze latency in a way that highlights this difficult to see area. The graphics and reports of the pgbench-tools package make it possible to see how tuning changes impact both latency and throughput. That that lets you test the "lore" for how best to tune your PostgreSQL server to find out what really works. Using these new tools, this talk will look at the tricky correlation between throughput and latency and how to measure each usefully in common situations. We'll look at three different storage stacks with very different latency profiles: regular disk, disk with battery-backed write cache, and SSD. We'll then look at exactly how checkpoint spikes play out on each and what you can do about them. You'll never trust a simple transactions per second count again!