The latest from the MySQL community

This blog shares some column store database benchmark results, and compares the query performance of MariaDB ColumnStore v. 1.0.7 (based on InfiniDB), Clickhouse and Apache Spark.

I’ve already written about ClickHouse (Column Store database).

The purpose of the benchmark is to see how these three solutions work on a single big server, with many CPU cores and large amounts of RAM. Both systems are massively parallel (MPP) database systems, so they should use many cores for SELECT queries.

For the benchmarks, I chose …

This blog compares how PostgreSQL and MySQL handle millions of queries per second.

Anastasia: Can open source databases cope with millions of queries per second? Many open source advocates would answer “yes.” However, assertions aren’t enough for well-grounded proof. That’s why in this blog post, we share the benchmark testing results from Alexander Korotkov (CEO of Development, Postgres Professional) and Sveta Smirnova (Principal Technical Services Engineer, Percona). The comparative research of PostgreSQL 9.6 and MySQL 5.7 performance will be especially valuable for environments with multiple databases.

The idea behind this research is to provide an honest comparison for the two popular RDBMSs. Sveta and Alexander wanted to test the most recent versions of both MySQL and PostgreSQL with the same tool, under the same challenging …

So I tried to do my first set of benchmarks and testing on RocksDB today, but I ran into a problem and had to file a bug:
https://github.com/facebook/mysql-5.6/issues/365

MySQL @ Facebook RocksDB appears to store at least 2x the size of the volume of changes in a transaction. I don't know how much space for the row + overhead there is in each transcation, so I'm just going to say 2x the raw size of the data changed in the transaction, as approximation. I am not sure how this works for updates either, that is whether old/new row information is maintained. If old/row data is maintained, then a pure update workload you would need 4x the ram for the given transactional changes. My bulk load was 12GB of raw data, so it failed as I have only 12GB of RAM in my test system.

The workaround (as suggested in the bug) is to set two configuration …

So I tried to do my first set of benchmarks and testing on RocksDB today, but I ran into a problem and had to file a bug:
https://github.com/facebook/mysql-5.6/issues/365

MySQL @ Facebook RocksDB appears to store at least 2x the size of the volume of changes in a transaction. I don't know how much space for the row + overhead there is in each transcation, so I'm just going to say 2x the raw size of the data changed in the transaction, as approximation. I am not sure how this works for updates either, that is whether old/new row information is maintained. If old/row data is maintained, then a pure update workload you would need 4x the ram for the given transactional changes. My bulk load was 12GB of raw data, so it failed as I have only 12GB of RAM in my test system.

The workaround (as suggested in the bug) is to set two configuration …

In this blog post, I’ll discuss changes I’ve made to the

tpcc-mysql

 benchmark tool. These changes make it less random and support multi-schema.

This post might only be interesting to performance researchers. The

tpcc-mysql

 benchmark to is what I use to test different hardware (as an example, see my previous post: https://www.percona.com/blog/2016/07/26/testing-samsung-storage-in-tpcc-mysql-benchmark-percona-server/).

The first change is support for multiple schemas, rather than just one schema. Supporting only one schema creates too much internal locking in MySQL on the same rows or the same index. Locking is fine …

Saturday I was in my favorite grocery store, standing in the line, browsing the net on my phone. I read Vadim Tkachenko‘s blog post about Measuring Percona Server Docker CPU/network overhead and his findings were opposite than mine – he didn’t found any measurable difference. Reading his post, he did found huge impact in networking […]

Saturday I was in my favourite grocery store, standing in the line, browsing the net on my phone. I read Vadim Tkachenko‘s blog post about Measuring Percona Server Docker CPU/network overhead and his findings were the opposite than mine – he didn’t found any measurable difference. Reading his post, he did found huge impact in networking which I didn’t […]

Back in October I have write about possible ways of running multiple MySQL instances on the same hardware. As the months passing by, the project of splitting our database schemas into standalone instances is closing in, so I started to check the different ways.

EDIT: This post is outdated, here is the follow up.

I started with docker, because we’ll use containers anyway with the applications, and I think it is a good idea to minimise the diversity of an infrastructure. I used the docker’s “official” Percona image (it is official by Docker not by Percona!) which is easy to use, and flexible enough. (https://hub.docker.com/_/percona/) This image supports using custom config files, you can mount your …

Back in October I have write about possible ways of running multiple MySQL instances on the same hardware. As the months passing by, the project of splitting our database schemas into standalone instances is closing in, so I started to check the different ways. EDIT: This post is outdated, here is the follow up. I started […]

When you have read my previous blog post about MariaDB 10.1 GA performance, you have probably wondered why I didn’t include any numbers for MySQL 5.7. There are two reasons: first MySQL wasn’t GA at that time and secondly MySQL is not running stable on Power8. Today I will come up with a comparison benchmark. […]

The post MariaDB 10.1 and MySQL 5.7 performance on commodity hardware appeared first on MariaDB.org.