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Displaying posts with tag: Database Compression Methods (reset)
How To Best Use Percona Server Column Compression With Dictionary

Very often, database performance is affected by the inability to cache all the required data in memory. Disk IO, even when using the fastest devices, takes much more time than a memory access. With MySQL/InnoDB, the main memory cache is the InnoDB buffer pool. There are many strategies we can try to fit as much data as possible in the buffer pool, and one of them is data compression.

With regular MySQL, to compress InnoDB data you can either use “Barracuda page compression” or “transparent page compression with punch holes”. The use of the ZFS filesystem is another possibility, but it is external to MySQL and doesn’t help with caching. All these solutions are transparent, but often they also have performance and management implications. If you are using Percona Server for MySQL, you have yet another option, “column …

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InnoDB Page Compression: the Good, the Bad and the Ugly

In this blog post, we’ll look at some of the facets of InnoDB page compression.

Somebody recently asked me about the best way to handle JSON data compression in MySQL. I took a quick look at InnoDB page compression and wanted to share my findings.

There is also some great material on this topic that was prepared and presented by Yura Sorokin at Percona Live Europe 2017: Yura also implemented …

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Evaluating Database Compression Methods: Update

This blog post is an update to our last post discussing database compression methods, and how they stack up against each other. 

When Vadim and I wrote about Evaluating Database Compression Methods last month, we claimed that evaluating database compression algorithms was easy these days because there are ready-to-use benchmark suites such as lzbench.

As easy as it was to do an evaluation with this tool, it turned out it was also easy to make a mistake. Due to a bug in the benchmark we got incorrect results for the LZ4 …

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Evaluating Database Compression Methods

Vadim Tkachenko and I have been working with Fractal Tree® storage engines (Fractal Tree engines are available in Percona Server for MySQL and MongoDB as TokuDB and PerconaFT, respectively). While doing so, we’ve become interested evaluating database compression methods, to see how to make compression algorithms work even better than they do currently.  

In this blog post, I will discuss what we found in our compression research.


Before we get to evaluation database compression methods, let’s review what compression properties are most relevant to databases in general. The first thing to consider is compression and decompression performance. Databases tend to be very sensitive to decompression performance, as it is often done in the “foreground” – …

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