September 2, 2014

Faster MySQL failover with SELECT mirroring

One of my favorite MySQL configurations for high availability is master-master replication, which is just like normal master-slave replication except that you can fail over in both directions. Aside from MySQL Cluster, which is more special-purpose, this is probably the best general-purpose way to get fast failover and a bunch of other benefits (non-blocking ALTER […]

COUNT(*) vs COUNT(col)

Looking at how people are using COUNT(*) and COUNT(col) it looks like most of them think they are synonyms and just using what they happen to like, while there is substantial difference in performance and even query result. Lets look at the following series of examples:

Using delayed JOIN to optimize count(*) and LIMIT queries

In many Search/Browse applications you would see main (fact) table which contains search fields and dimension tables which contain more information about facts and which need to be joined to get query result. If you’re executing count(*) queries for such result sets MySQL will perform the join even if you use LEFT JOIN so it […]

COUNT(*) for Innodb Tables

I guess note number one about MyISAM to Innodb migration is warning what Innodb is very slow in COUNT(*) queries. The part which I often however see omitted is fact it only applies to COUNT(*) queries without WHERE clause. So if you have query like SELECT COUNT(*) FROM USER It will be much faster for […]

Managing shards of MySQL databases with MySQL Fabric

This is the fourth post in our MySQL Fabric series. In case you’re joining us now, we started with an introductory post, and then discussed High Availability (HA) using MySQL Fabric here (Part 1) and here (Part 2). Today we will talk about how MySQL Fabric can help you scale out MySQL databases with sharding. Introduction At the […]

Using InfiniDB MySQL server with Hadoop cluster for data analytics

In my previous post about Hadoop and Impala I benchmarked performance of analytical queries in Impala. This time I’ve tried InfiniDB for Hadoop (open-source version) on the modern hardware with an 8-node Hadoop cluster. One of the main advantages (at least for me) of InifiniDB for Hadoop is that it stores the data inside the Hadoop cluster but uses the […]

Parallel Query for MySQL with Shard-Query

While Shard-Query can work over multiple nodes, this blog post focuses on using Shard-Query with a single node.  Shard-Query can add parallelism to queries which use partitioned tables.  Very large tables can often be partitioned fairly easily. Shard-Query can leverage partitioning to add paralellism, because each partition can be queried independently. Because MySQL 5.6 supports the […]

Using Apache Hadoop and Impala together with MySQL for data analysis

Apache Hadoop is commonly used for data analysis. It is fast for data loads and scalable. In a previous post I showed how to integrate MySQL with Hadoop. In this post I will show how to export a table from  MySQL to Hadoop, load the data to Cloudera Impala (columnar format) and run a reporting […]

How rows_sent can be more than rows_examined?

When looking at queries that are candidates for optimization I often recommend that people look at rows_sent and rows_examined values as available in the slow query log (as well as some other places). If rows_examined is by far larger than rows_sent, say 100 larger, then the query is a great candidate for optimization. Optimization could […]

Increasing slow query performance with the parallel query execution

MySQL and Scaling-up (using more powerful hardware) was always a hot topic. Originally MySQL did not scale well with multiple CPUs; there were times when InnoDB performed poorer with more  CPU cores than with less CPU cores. MySQL 5.6 can scale significantly better; however there is still 1 big limitation: 1 SQL query will eventually use only […]