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An approach to index tuning – Part 2

SQL Performance

In my last post , I started to outline the process I go through when tuning queries – specifically when I discover that I need to add a new index, or modify an existing one. His version can be used for the plan cache – the only challenge there is the information is transient, so you may not capture every query that uses a particular index.

Tuning 137
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Impact of Data locality on DB workloads.

n0derunner

Many different queries are executing in parallel, some hitting RAM cache, some hitting storage. The Postgres DB is totally un-tuned and contains purely default settings. The variation in the transaction rate is due to the benchmark itself, the transaction rate is not expected to be uniform.

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KPTI/KAISER Meltdown Initial Performance Regressions

Brendan Gregg

In this post I'll look at the Linux kernel page table isolation (KPTI) patches that workaround Meltdown: what overheads to expect, and ways to tune them. Much of my testing was on Linux 4.14.11 Some older kernels have the KAISER patches for Meltdown, and so far the performance overheads look similar. and 4.14.12

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KPTI/KAISER Meltdown Initial Performance Regressions

Brendan Gregg

In this post I'll look at the Linux kernel page table isolation (KPTI) patches that workaround Meltdown: what overheads to expect, and ways to tune them. Much of my testing was on Linux 4.14.11 Some older kernels have the KAISER patches for Meltdown, and so far the performance overheads look similar. and 4.14.12

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How To Boost Resource Loading With The New Priority Hint `fetchpriority`

Smashing Magazine

However, developers with a deep understanding of the project may want to improve performance beyond that by doing some fine-tuning under the hood. It’s common knowledge that better website performance results in more conversions, more traffic, and better user experience. Fine-tuning JavaScript Resource Priorities.

Media 70
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HTTP/3: Practical Deployment Options (Part 3)

Smashing Magazine

This approach was touted to be better for fine-grained caching because each subresource could be cached individually and the full bundle didn’t need to be redownloaded if one of them changed. As such, a micro-optimization is, again, how you probably need to fine-tune things on a low level to really benefit from it.

Network 105
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Egnyte Architecture: Lessons learned in building and scaling a multi petabyte content platform

High Scalability

Edge caching. In general, Egnyte connect architecture shards and caches data at different levels based on: Amount of data. Nginx for disk based caching. We use different types of caching techniques depending on the problem statements. Disk based caching. Hybrid Sync. On prem data processing. Offline access.