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InnoDB Performance Optimization Basics

Percona

This blog is in reference to our previous ones for ‘Innodb Performance Optimizations Basics’ 2007 and 2013. By caching hot datasets, indexes, and ongoing changes, InnoDB can provide faster response times and utilize disk IO in a much more optimal way. have been released since then with some major changes.

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New (Old) Paper.

n0derunner

A 2007 paper, that still has lots to say on the subject of benchmarking storage and filesystems. A Nine year study of filesystem and storage benchmarking Download. Use a mix of macro and micro benchmarks Understand what you are testing, cached results are fine – as long as that is what you had intended.

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Progress Delayed Is Progress Denied

Alex Russell

After 20 years of neck-in-neck competition, often starting from common code lineages, there just isn't that much left to wring out of the system. Consistent improvement is the name of the game, and it can still have positive impacts, particularly as users lean on the system more heavily over time. Where Chrome Has Lagged.

Media 145
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A Decade of Dynamo: Powering the next wave of high-performance, internet-scale applications

All Things Distributed

With these requirements in mind, and a willingness to question the status quo, a small group of distributed systems experts came together and designed a horizontally scalable distributed database that would scale out for both reads and writes to meet the long-term needs of our business. This was the genesis of the Amazon Dynamo database.

Internet 128
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Egnyte Architecture: Lessons learned in building and scaling a multi petabyte content platform

High Scalability

He and his colleagues spend their productive hours scaling large distributed file systems. It is limited by the disk space; it can’t expand storage elastically; it chokes if you run few I/O intensive processes or try collaborating with 100 other users. Edge caching. Optimize on prem cold storage cost. Introduction.