MariaDB 5.5 and then MySQL 5.6 got Index Condition Pushdown (ICP) optimization (initially coded by yours truly). The idea of ICP is simple: after reading the index record, check the part of WHERE condition that can be computed using index columns, and only then read the table record. That way, we avoid reading table rows that don’t satisfy index condition:

It seems apparent that ICP can never make things slower. The WHERE clause has to be checked anyway, and not reading certain records can only make things faster.

That was what I thought, too, until recently Joffrey Michaie observed the contrary “in the wild”: we’ve got a real-world case where using Index Condition Pushdown was slower than not using it: …

In a previous blog post (Importing related MySQL tables into an Excel Data Model using MySQL for Excel) we covered in detail how an Excel Data Model can be created containing tables and their relationships so the data can be analyzed in Excel via a PivotTable. In this blog post we are going to talk about one of the features included since MySQL for Excel 1.3.0 that allows you to create PivotTables for data imported from MySQL tables, views or stored procedures, or more importantly for the whole Excel Data Model if it is created.

Remember you can install the latest GA or maintenance version using the MySQL Installer or optionally you can download directly any GA or non-GA version from the MySQL Developer …

MySQL has information_schema.tables that contain information such as “data_length” or “avg_row_length.” Documentation on this table however is quite poor, making an assumption that those fields are self explanatory – they are not when it comes to tables that employ compression. And this is where inconsistency is born. Lets take a look at the same table containing some highly compressible data using different storage engines that support MySQL compression:

TokuDB:

mysql> select * from information_schema.tables where table_schema='test' G
*************************** 1. row ***************************
TABLE_CATALOG: def
TABLE_SCHEMA: test
TABLE_NAME: comp
TABLE_TYPE: BASE TABLE
ENGINE: TokuDB
VERSION: 10
ROW_FORMAT: tokudb_zlib
TABLE_ROWS: 40960
AVG_ROW_LENGTH: 10003
DATA_LENGTH: 409722880
MAX_DATA_LENGTH: …

It seems its all about cloud these days. Even the hardware is being marketed with cloud in perspective. Databases like Oracle, SQL Server and MySQL are ahead in the cloud game and this Log Buffer Edition covers that all.

Oracle:

Oracle Database 12c was launched over a year ago delivering the next-generation of the #1 database, designed to meet modern business needs, providing a new multitenant architecture on top of a fast, scalable, reliable, and secure database platform.

Oracle OpenWorld 2014 Session Presentations Now Available.

Today, Oracle is using big data technology and concepts to …

Fri, 2014-10-10 10:08jensbollmann

Installing MariaDB became very easy on the latest CentOS /RHEL Linux version 7. During initial setup MariaDB has a tick in the graphical setup environment which enables MariaDB and replaces MySQL.

During installation the section

allows enabling a MariaDB server.

If you prefer the command line the installation can be performed with:

shell> yum install mariadb-server

MariaDB is shipped untuned and not protected with MariaDB version 5.5.35. No basic optimizations in the configuration file have been set and the root user has no password. An update will install the version 5.5.37. (The latest version of MariaDB October 2014 is Version 5.5.39).

shell> yum update

It is important to secure the server. MariaDB is shipped with a script to harden the system accordingly using a user dialog. It is highly recommended to use this script before …

Fri, 2014-10-10 09:36benstillman

For several years, I have hosted a medium sized Invision Power Board (IPB) site. The site has roughly 9,000+ users and 1,000,000+ posts. I work with MariaDB on a daily basis, and often find myself recommending it to customers. It's only appropriate I put my money where my mouth is, so to speak. This blog post has no benchmarks. It is just a very simple to follow set of steps I took to migrate my site from MySQL 5.1 to MariaDB 10 on CentOS 6.5 with very little downtime for the end users.

To do this, I setup a new virtual server for MariaDB, use mysqldump to export the data with master info, restored this backup to MariaDB, setup replication, set the site to offline, switched the conf_global.php database values, then set the site to online. Sounds easy, right? It was. Very easy. Here are the steps I took with more detail.

For these steps, we will call the original MySQL 5.1 server DB1 and …

October 9, 2014 By Severalnines

Installing, configuring, deploying databases and performing repetitive administrative tasks are all part of a DBA’s or sysadmin’s job. This can get pretty repetitive and overwhelming if you are part of a centralized IT team, running multiple databases for your organization’s different departments, or a managed hosting provider responsible for setting up and operating databases for external clients. One way to get out of this ‘manual, repetitive task’ business is through a Database as a Service (DBaaS).

DBaaS is a way of delivering database functionality as a service to one or more consumers. A DBaaS platform would provide automated procedures for database deployment, monitoring, backups, recovery/repair, scaling, security/multi-tenancy, etc. This type of automation is especially useful where agility is needed, e.g. for systems that require elasticity by scaling out or scaling back at short …

The MySQL Server 5.7.5 Development Milestone Release, which was published recently, contains some significant changes to the metadata locking (MDL) subsystem and to the usage of the THR_LOCK manager for InnoDB tables. This post provides more information about these changes, which resulted in nice improvements in both scalability and performance.

Sometime during the development cycle of MySQL 5.6 we realized that locks used in the metadata locking subsystem (MDL) implementation can become a scalability bottleneck when many short statements were executed in @autocommit=1 mode against InnoDB tables.

Bug #66473 is a good example (8-table Sysbench POINT_SELECT/InnoDB test). In this particular case the bottleneck was the mutex protecting the MDL_map hash which …

Following my previous post, I got some excellent feedback in the forms of comments, tweets and other chat. In no particular order:

• Commenter Tibi noted that ensuring I’m mounting with noatime, nodiratime and nobarrier should all improve performance.
• Commenter benbradley pointed out a missing flag on some of my sysbench tests which will necessitate re-testing.
• Former co-worker @preston4tw suggests looking at different IO schedulers. For all tests past, I used deadline which seems to be best, but re-testing with noop could be useful.
• Fellow DBA @kormoc encouraged me to try many smaller partitions to limit the number of concurrent fsyncs.

There seem to be …

The EXPLAIN command is one of MySQL’s most useful tools for understanding query performance. When you EXPLAIN a query, MySQL will return the plan created by the query optimizer. It also shows you how that query will be indexed and an estimate of how many rows are processed by that query. From this information, it is easy to see if your queries are taking advantage of table indexes or if you can change them for some extra performance. VividCortex provides a lot of information on query performance, including samples of the queries that are run against your database. Now, those samples will have EXPLAIN data for them too!

So what does the EXPLAIN feature look like in VividCortex? Here’s a screenshot to illustrate:

Those who are familiar with our application will recognize the query-drilldown view. Each of the dots in the scatterplot represents a sample for the selected query, …