October 22, 2014

Using MySQL 5.6 Performance Schema in multi-tenant environments

Hosting a shared MySQL instance for your internal or external clients (“multi-tenant”) was always a challenge. Multi-tenants approach or a “schema-per-customer” approach is pretty common nowadays to host multiple clients on the same MySQL sever. One of issues of this approach, however, is the lack of visibility: it is hard to tell how many resources (queries, disk, […]

TokuDB vs InnoDB in timeseries INSERT benchmark

This post is a continuation of my research of TokuDB’s  storage engine to understand if it is suitable for timeseries workloads. While inserting LOAD DATA INFILE into an empty table shows great results for TokuDB, what’s more interesting is seeing some realistic workloads. So this time let’s take a look at the INSERT benchmark.

LVM read performance during snapshots

For the same customer I am exploring ZFS for backups, the twin server is using regular LVM and XFS. On this twin, I have setup mylvmbackup for a more conservative backup approach. I quickly found some odd behaviors, the backup was taking much longer than what I was expecting. It is not the first time […]

Edge-case behavior of INSERT…ODKU

A few weeks back, I was working on a customer issue wherein they were observing database performance that dropped through the floor (to the point of an outage) roughly every 4 weeks or so. Nothing special about the environment, the hardware, or the queries; really, the majority of the database was a single table with […]

Avoiding auto-increment holes on InnoDB with INSERT IGNORE

Are you using InnoDB tables on MySQL version 5.1.22 or newer? If so, you probably have gaps in your auto-increment columns. A simple INSERT IGNORE query creates gaps for every ignored insert, but this is undocumented behaviour. This documentation bug is already submitted. Firstly, we will start with a simple question. Why do we have […]

Performance Schema tables stats

My previous benchmark on Performance Schema was mainly in memory workload and against single tables. Now after adding multi-tables support to sysbench, it is interesting to see what statistic we can get from workload that produces some disk IO. So let’s run sysbench against 100 tables, each 5000000 rows (~1.2G ) and buffer pool 30G. […]

Flexviews – part 3 – improving query performance using materialized views

Combating “data drift” In my first post in this series, I described materialized views (MVs). An MV is essentially a cached result set at one point in time. The contents of the MV will become incorrect (out of sync) when the underlying data changes. This loss of synchronization is sometimes called drift. This is conceptually […]

MySQL on Amazon RDS part 1: insert performance

Amazon’s Relational Database Service (RDS) is a cloud-hosted MySQL solution. I’ve had some clients hitting performance limitations on standard EC2 servers with EBS volumes (see SSD versus EBS death match), and one of them wanted to evaluate RDS as a replacement. It is built on the same technologies, but the hardware and networking are supposed […]

How innodb_open_files affects performance

Recently I looked at table_cache sizing which showed larger table cache does not always provides the best performance. So I decided to look at yet another similar variable – innodb_open_files which defines how many files Innodb will keep open while working in innodb_file_per_table mode. Unlike MyISAM Innodb does not have to keep open file descriptor […]

Analyzing air traffic performance with InfoBright and MonetDB

Accidentally me and Baron played with InfoBright (see http://www.percona.com/blog/2009/09/29/quick-comparison-of-myisam-infobright-and-monetdb/) this week. And following Baron’s example I also run the same load against MonetDB. Reading comments to Baron’s post I tied to load the same data to LucidDB, but I was not successful in this. I tried to analyze a bigger dataset and I took public […]