I will be presenting at Percona Live 2014 and I’m excited to share and discuss the latest and greatest features and improvements that we have made to MySQL/InnoDB in 5.7. Great performance improvements, there are some new exciting compression features that we are working on,  GIS support,  temporary table performance etc.. There is a long list. Also, we are always interested to hear about user issues and priorities so that we can address them and/or work them into our plan. Your feedback is very important for us, if you want to influence the direction of InnoDB development then you need to talk to me .

The MariaDB project is pleased to announce the immediate availability of MariaDB 10.0.9. This is a Release Candidate release.

Among other changes, XtraDB is now the default InnoDB implementation, Oracle’s InnoDB is included as a plugin and can be dynamically loaded if desired. Packages for Ubuntu 14.04 “trusty” and Debian “Sid” have also been added to the MariaDB Ubuntu and Debian repositories.

See the Release Notes and Changelog for detailed information on this release and the …

Google senior systems engineer Jeremy Cole is once again teaming with LinkedIn senior software engineer Davi Arnaut for two InnoDB-focused sessions at the upcoming Percona Live MySQL Conference and Expo 2014 this April 1-4 in Santa Clara, California.

The duo will present “InnoDB: A journey to the core II” on April 2 and “InnoDB: A  hands-on exploration of on-disk storage with innodb-ruby” on April 4. Based on Jeremy’s InnoDB blog series, both sessions will be a continuation of …

(This is a cross-post from the Engine Yard blog. The original article appears here.)

Here is a question I've actually been asked a few times:

"I am writing a batch processing script which modifies data as part of an ongoing process that is scheduled by cron. I have the ability to group a number of modifications together into a transaction, but I'm not sure what the correct number is?"

First off, I think that this question is interesting not just in the context of batch processing, but it equally applies to all parts of the application. If you are designing a high throughput system for MySQL, there are actually some potential pain points that you can design your way around.

Potential Pain Points

Here are the situations where the size of the transaction could impact performance:

Very Small …

In my previous post I pointed out that the existing ARCHIVE storage engine in MySQL may not be the one that will satisfy your needs when it comes to effectively storing large and/or old data. But are there any good alternatives? As the primary purpose of this engine is to store rarely accessed data in disk space efficient way, I will focus here on data compression abilities rather then on performance.

The InnoDB engine provides compressed row format, but is it’s efficiency even close to the one from that available in archive engine? You can also compress MyISAM tables by using myisampack tool, but that also means a table will be read only after such operation.

Moreover, I don’t trust MyISAM nor Archive when it comes to data durability. Fortunately along came a quite new (open source since April …

One of the most expensive database operations is performing Data Definition Language (DDL, e.g. CREATE, DROP, ALTER, etc.) statements, specially, the ALTER statements because MySQL blocks the entire table for both reads and writes while modifying the table.

For the huge tables, this might take hours to get the table changed which affects the application, so that, a good planning is required for such operations in order to avoid doing these changes during the peak times. For those people who have 24/7 services or limited maintenance window, DDL on huge tables is a really nightmare.

Percona developed a very good tool called pt-online-schema-change (version 2.2.6 at the time of writing this article) to perform such operations online without blocking/affecting …

Mysqldump is a fantastic tool for backing up and restoring small and medium sized MySQL tables and databases quickly. However, when databases surge into the multi-terabyte range restoring from logical backups is inefficient. It can take a significant amount of time to insert a hundred million plus rows to a single table, even with very fast I/O. Programs like MySQL Enterprise Backup and Percona XtraBackup allow non-blocking binary copies of your InnoDB tables to be taken while it is online and processing requests. XtraBackup also has an export feature that allows InnoDB file per tablespaces to be detached from the shared table space and imported to a completely different MySQL instance.

The necessary steps to export and import InnoDB tables are in the XtraBackup documentation  …

This is a continuation of my post on migration-of-mtr-suites-to-use-innodb . To set the context here is a quick recap.

MySQL 5.5 had the following changes with respect to the default engine

• Default engine in the server changed from MyISAM to InnoDB
• MTR modified to start server with the old default MyISAM. (This was required because historically most test results were recorded with MyISAM and many of them would fail if tests were run with the new server default,  InnoDB)
• Tests retained as is in 5.5 and planned to migrate them to run with default engine in a future release

In MySQL 5.7 release we have started the migration project. Right in the beginning we realized that the switch of default engine had an unexpected side effect. MTR tests that were developed post 5.5 were also getting …

This continues on from my post yesterday and also contains content from my linux.conf.au 2014 talk (view video here).

Way back in May in the year 2000, a feature was added to MySQL that would keep many people employed for many years – replication. In 3.23.15 you could replicate from one MySQL instance to another. This is commonly cited as the results of two weeks of work by one developer. The idea is simple: create a log of all the SQL queries that modify the database and then replay them on a slave. Remember, this is before there was concurrency and everything was ISAM or MyISAM, so this worked (for certain definitions of worked).

…

William Zola over at MongoDB gave a great talk called “The (Only) Three Reasons for Slow MongoDB Performance”. It reminded me of an interesting characteristic of updates in MongoDB. Because MongoDB’s main data store is a flat file and secondary indexes store offsets into the flat file (as I explain here), if the location of a document changes, corresponding entries in secondary indexes must also change. So, an update to an unindexed field that causes the document to move also causes modifications to every secondary index, which, as William points out, can be expensive. If a document has indexed an array, this problem is exacerbated.

What …