The following is a short HOWTO about deployment and use of Benchmark-kit (BMK-kit). The main idea of this kit is to simplify your life in running various MySQL benchmark workloads with less blood and minimal potential errors.

Generally as simple as the following :

$ bash /BMK/sb_exec/sb11-Prepare_50M_8tab-InnoDB.sh 32   # prepare data

$ for users in 1 2 4 8 16 32 64 128 256 512 1024 2048
do   
  # run OLTP_RW for 5min each load level..
  bash /BMK/sb_exec/sb11-OLTP_RW_50M_8tab-uniform-ps-trx.sh $users 300
  sleep 15
done

the latest public online version of the following HOWTO is always available from here : http://dimitrik.free.fr/blog/posts/mysql-perf-bmk-kit.html

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While implementing ClickHouse for query executions statistics storage in Percona Monitoring and Management (PMM),  we were faced with a question of choosing the data type for metrics we store. It came down to this question: what is the difference in performance and space usage between Uint32, Uint64, Float32, and Float64 column types?

To test this, I created a test table with an abbreviated and simplified version of the main table in our ClickHouse Schema.

The “number of queries” is stored four times in four different columns to be able to benchmark queries referencing different columns.  We can do this with ClickHouse because it is a column store and it works only with columns referenced by the query. This method would not be appropriate for testing on …

In one of my previous posts, I started a series on data compression options with MySQL. The first post focused on the more traditional compression options like InnoDB Barracuda page compression and MyISAM packing. With this second part, I’ll discuss a newer compression option, InnoDB transparent page compression with punch holes available since 5.7. First, I’ll describe the transparent page compression method and how it works. Then I’ll present similar results as in the first post.

InnoDB transparent page compression

Before we can discuss transparent page compression, we must understand how InnoDB accesses its data pages. To access an InnoDB page, you need to know the tablespace (the file) and the offset of the page within the …

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 …

Please join Percona’s Chief Evangelist, Colin Charles on Tuesday, June 26th, 2018, as he presents MariaDB Server 10.3 at 7:00 AM PDT (UTC-7) / 10:00 AM EDT (UTC-4).

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MariaDB Server 10.3 is out. It has some interesting features around system versioned tables, Oracle compatibility, column compression, an integrated SPIDER engine, as well as MyRocks. Learn about what’s new, how you can use it, and how it is different from MySQL.

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Colin Charles Chief Evangelist

Colin Charles is the Chief Evangelist at Percona. He was previously on the founding team of MariaDB Server in 2009, and had …

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: https://www.percona.com/live/e17/sessions/percona-xtradb-compressed-columns-with-dictionaries-an-alternative-to-innodb-table-compression. Yura also implemented …

In one of my previous posts, I shared InnoDB table compression statistics for a read-only dataset using the default value of innodb_compression_level (6).  In it, I claimed, without giving much detail, that using the maximum value for the compression level (9) would not make a big difference.  In this post, I will share more details about this claim.

TL;DR: tuning innodb_compression_level is not

TL;DR: we still need MyISAM and myisampack because it uses less space on disk (half of compressed InnoDB) !

In the previous post, I shared my experience with InnoDB table compression on a read-only dataset.  In it, I claimed, without giving much detail, that using MyISAM and myisampack would result is a more compact storage on disk.  In this post, I will share more details about this claim.

In my last post about big MySQL deployments, I am quickly mentioning that InnoDB compression is allowing dividing disk usage by about 4.3 on a 200+ TiB dataset.  In this post, I will give more information about this specific use case of InnoDB table compression and I will share some statistics and learnings on this system and subject.  Note that I am not covering InnoDB page compression which is

Disk space issues are common, and they’re often difficult to solve quickly. One way to recover some space is by enabling InnoDB compression.

First, of course, you want to make sure you’ve covered alternative solutions. Can you archive data? Do partitioning/sharding? These generally involve application changes and can take longer.

You may need to first do conversion to InnoDB.

While compression is available for MyISAM via myisampack, and this can be useful for some use cases (for example, if you are rotating out tables on a monthly basis), it makes the tables read-only, so generally you will want to first convert MyISAM tables to InnoDB.

Things to watch for in the schema: After working on functional and performance issues with full-text indexes after conversion to InnoDB, I wouldn’t recommend it. Application changes are also required to rewrite queries. You can consider outsourcing these to a tool …