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MySQL Performance Tuning 101: Key Tips to Improve MySQL Database Performance

Percona

While there is no magic bullet for MySQL performance tuning, there are a few areas that can be focused on upfront that can dramatically improve the performance of your MySQL installation. What are the Benefits of MySQL Performance Tuning? A finely tuned database processes queries more efficiently, leading to swifter results.

Tuning 52
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PostgreSQL Performance Tuning: Optimizing Database Parameters for Maximum Efficiency

Percona

Out of the box, the default PostgreSQL configuration is not tuned for any particular workload. It is primarily the responsibility of the database administrator or developer to tune PostgreSQL according to their system’s workload. What is PostgreSQL performance tuning? Why is PostgreSQL performance tuning important?

Tuning 52
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PostgreSQL Indexes Can Hurt You: Negative Effects and the Costs Involved

Percona

Indexes are generally considered to be the panacea when it comes to SQL performance tuning, and PostgreSQL supports different types of indexes catering to different use cases. I keep seeing many articles and talks on “tuning” discussing how creating new indexes speeds up SQL but rarely ones discussing removing them.

Tuning 125
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Tuning SQL Server Reporting Services

SQL Performance

This article will cover many areas that database administrators need to be aware of in order to properly license, recover, and tune a Reporting Services installation. Tuning Options. Tuning SSRS is much like any other application. General Tuning. Reporting Services Infrastructure.

Tuning 67
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Tuning PostgreSQL Database Parameters to Optimize Performance

Percona

Out of the box, the default PostgreSQL configuration is not tuned for any particular workload. It is primarily the responsibility of the database administrator or developer to tune PostgreSQL according to their system’s workload. This parameter sets how much dedicated memory will be used by PostgreSQL for cache. wal_buffers.

Tuning 55
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Formulating ‘Out of Memory Kill’ Prediction on the Netflix App as a Machine Learning Problem

The Netflix TechBlog

Problem Statement The purpose of this article is to give insights into analyzing and predicting “out of memory” or OOM kills on the Netflix App. Some features (as an example) include Device Type ID, SDK Version, Buffer Sizes, Cache Capacities, UI resolution, Chipset Manufacturer and Brand. of the time (False Positives).

Big Data 179
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Gone Floating Labels And Green Lighthouse Scores

Smashing Magazine

Ironically, at the moment of publishing that article in late February, we still had floating labels used in most of our forms, and we wanted to explore if removing them would actually help us improve the overall experience on the site. On February 19th, most of our articles landed in the red zone. Floating Labels Are Gone.

Mobile 140