I haven’t been blogging much about the changes in MySQL for a while. But the MySQL and InnoDB engineers have been doing a ton of work over the last couple years, and now it’s seeing the light of day, so it’s time to offer words of congratulations and appreciation about that.

I was holding my breath for a big-splash 5.5 GA announcement at last week’s conference, but I was wrong. Still, there’s a lot to talk about in 5.5, with a dozen or more substantial blog posts from the InnoDB and MySQL teams alone over the last week or so! Here are a few choice tidbits of the good, the bad, and the ugly.

InnoDB is the default storage engine

“No big deal,” I thought. “Serious users do this anyway.” But then Morgan Tocker pointed out that it really is a big deal. This is going to cause a sea change in the way MySQL is …

Oracle outlines MySQL plans. Datameer launches with Series A funding. And more.

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“Tracking the open source news wires, so you don’t have to.”

# Oracle confirmed InnoDB as the default MySQL storage engine, Hot Backup to become part of MySQL Enterprise and announced MySQL Cluster 7.1.

# Datameer launched Analytics Solution, which combines Hadoop with a spreadsheet interface, and also closed a $2.5m Series A round of funding from Redpoint Ventures.

# Infobright announced that it grew its customers base from 50 to …

What a busy week! Lots of MySQL 5.5 announcements that just happened to coincide with the MySQL Conference and Expo in Silicon Valley. Here are some highlights of the performance and scalability work that the InnoDB team was involved with.

A good prep for the week of news is the article Introduction to MySQL 5.5, which includes information about the major performance and scalability features. That article will lead you into the MySQL 5.5 manual for general features and the InnoDB 1.1 manual for performance & scalability info.

Then there were the conference presentations from InnoDB team members, which continued the twin themes of performance and scalability:

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I just announced our continuation of the Embedded InnoDB project under the name of HailDB. Check out the announcement over at http://www.haildb.com/.

HailDB is a relational database that is embeddable within applications. You embed HailDB by linking to a shared library and calling a clean and simple API. HailDB is a continuation of the Embedded InnoDB project. It is not itself a database server, but is a library implementing the storage layer. With the addition of the HailDB plugin to Drizzle you get a full SQL interface.

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Been at the MySQL conference the last few days, and I have to say, I’m really blown away by MySQL 5.5.4‘s improvements.  Last year I keynoted and I begged Oracle on stage to realize that MySQL and InnoDB under one roof represented opportunity.  It’s clear they heard the community – this is some serious progress, and right when we needed it.

Jeremy Zawodny’s blog post covers most of the stuff I’m really excited about, and there are some great detailed technical slides …

Well… the start of it :)

I’ve taken the approach of taking tiny incremental steps (and getting review for each step) in implementing a Storage Engine based on the Embedded InnoDB library. What hit lp:drizzle (the trunk branch, for the 2010-04-07 milestone tarball) is only a handful of these small steps, so this engine is not remotely ready for end users.

There should be more of my Embedded InnoDB work hitting the tree in the upcoming days/weeks, enough to get it to a satte that one could describe as functional :)

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The InnoDB Plugin manual is now available on the MySQL web site.

One of the exciting things[1] about working on a storage engine in Drizzle is that you get to manage your own metadata. When the database engine you’re writing the storage engine interface for has a pretty complete data dictionary (e.g. Embedded InnoDB) you could just directly use it. At some point I plan to do this for the embedded_innodb engine for Drizzle so that you could just point Drizzle at an existing Embedded InnoDB database and run SQL queries on it.

The Drizzle table message does have some things in it that aren’t in the InnoDB data dictionary though (e.g. table and column comments). We want to preserve these (and also things like there may be several data types in Drizzle that map to the same data type in InnoDB). Since the Embedded InnoDB API allows us to do things within the DDL transaction (such …

Last week a customer called me and reported that MySQL was 30 times slower than MS SQL server. Oooops. That's a lot. No way to argue or throw smoke bombs. 30 times slower! It was a standard installation of MySQL (typical install option) on plain Windows 7 and the same for MS SQL Server 2008. The test run was a batch of 30.000 INSERT commands in an SQL script. Runtime was 1 minute on MSSQL and 30 minutes on MySQL. Some tests later we found out that it was only bad on InnoDB. MyISAM was as fast as MSSQL. (I didn't care which one was a bit faster. I didn't care as long as InnoDB was 30 times slower) Finally we nailed the problem down to one parameter in MySQL: innodb_flush_log_at_trx_commit Each INSERT statement is a single transaction (autocommit mode). MySQL is configured very faithfully and ensures that each …

In XtraDB we have the table INNODB_BUFFER_POOL_PAGES_INDEX which shows which pages belong to which indexes in which tables. Using thing information and standard TABLES table we can see how well different tables fit in buffer pool.

PLAIN TEXT SQL:

1. mysql> SELECT d.*,round(100*cnt*16384/(data_length+index_length),2) fit FROM (SELECT schema_name,table_name,count(*) cnt,sum(dirty),sum(hashed)  FROM INNODB_BUFFER_POOL_PAGES_INDEX GROUP BY schema_name,table_name ORDER BY cnt DESC LIMIT 20) d JOIN TABLES ON (TABLES.table_schema=d.schema_name AND TABLES.table_name=d.table_name);
2. +-------------+---------------------+---------+------------+-------------+--------+
3. | schema_name | table_name          | cnt     | sum(dirty) | sum(hashed) | fit    |
4. …