One of the challenges in storage engine design is random I/O during a write operation. In InnoDB, a table will have one clustered index and zero or more secondary indexes.  Each of these indexes is a B-tree.  When a record is inserted into a table, the record is first inserted into clustered index and then into each of the secondary indexes.  So, the resulting I/O operation will be randomly distributed across the disk.  The I/O pattern is similarly random for update and delete operations. To mitigate this problem, the InnoDB storage engine uses a special data structure called the change buffer (previously known as the insert buffer, which is while you will see ibuf and IBUF used in various internal names).

The change buffer is another B-tree, with the ability to hold the record of any secondary index.  It is also …

Some applications have a heavy write workload on a few records – for instance when incrementing a global counter: this is called a write hotspot. Because you cannot update the same row simultaneously from multiple threads, this can lead to performance degradation. When using Percona XtraDB Cluster (PXC), some users try to solve this specific issue by writing on multiple nodes at the same time. Good idea or bad idea? Read on!

Simultaneous writes on a standalone InnoDB server

Say you have these 3 transactions being run simultaneously (id is the primary key of the table):

# T1
UPDATE t SET ... WHERE id = 100
# T2
UPDATE t SET ... WHERE id = 100
# T3
UPDATE t SET ... WHERE id = 101

All transactions will require a row lock on the record they want to modify. So T3 can commit at the same time than T1 and/or T2, because it will …

It seems these days if anyone knows anything about tuning InnoDB, it’s that you MUST tune your innodb_buffer_pool_size to 80% of your physical memory. This is such prolific tuning advice, it seems engrained in many a DBA’s mind.  The MySQL manual to this day refers to this rule, so who can blame the DBA?  The question is: does it makes sense?

What uses the memory on your server?

Before we question such advice, let’s consider what can take up RAM in a typical MySQL server in their broad categories.  This list isn’t necessarily complete, but I think it outlines the large areas a MySQL server could consume memory.

• OS Usage: Kernel, running processes, filesystem cache, etc.
• MySQL fixed usage: query cache, InnoDB …

Two days ago Oracle had released MySQL 5.6.25, so it's time to check what bugs reported by MySQL Community are fixed there. As usual, I'll mention both a bug reporter and engineer who verified the bug. Please, pay attention to fixes in replication and partitioning - if you use these features (or queries to INFORMATION_SCHEMA with a lot of complex tables in your database), please, consider upgrading ASAP.

The following InnoDB related bugs were fixed:

• Bug #69990 - CREATE_TIME and UPDATE_TIME are wrong for partitioned tables. Finally this bug reported by my colleague Justin Swanhart and verified by Umesh (almost …

The other day I was discussing new features of MySQL 5.7 with a Percona Support customer. After that conversation, I thought it would be a good idea to compile list of important features of MySQL 5.7. The latest MySQL 5.7.6 release candidate (RC) is out and is packed with nice features. Here’s a list of some MySQL 5.7 key features.

Replication Enhancements:

• One of the top features in MySQL 5.7 is multi-source replication. With multi-source replication you can point multiple master server’s to slave so limitation of slave having only one master is lift off. There is nice blog post written by my colleague on multi-source replication you will find useful.
• …

Part 1 of 2: (part two)
If you have used MySQL for a while, you have probably used mysqldump to backup your database. In part one of this blog, I am going to show you how to create a simple full and partial backup using mysqldump. In part two, I will show you how to use MySQL Enterprise Backup (which is the successor to the InnoDB Hot Backup product). MySQL …

We discussed in an earlier post how to design indexes for many types of queries using a single table. Here is a real-world example of the challenges you will face when trying to optimize queries: two similar queries, but one is performing a full table scan while the other one is using the index we specially created for these queries. Bug or expected behavior? Read on!

Our two similar queries

# Q1
mysql> explain select col1, col2 from t where ts >= '2015-04-30 00:00:00';
+----+-------------+---------------+------+---------------+------+---------+------+---------+-------------+
| id | select_type | table         | type | possible_keys | key  | key_len | ref  | rows    | Extra       |
+----+-------------+---------------+------+---------------+------+---------+------+---------+-------------+
|  1 | SIMPLE      | t …

An idea for a benchmark based on the “arrival request” rate that I wrote about in a post headlined “Introducing new type of benchmark” back in 2012 was implemented in Sysbench. However, Sysbench provides only a simple workload, so to be able to compare InnoDB with TokuDB, and later MongoDB with Percona TokuMX, I wanted to use more complicated scenarios. (Both TokuDB and TokuMX are part of Percona’s product line, in the case you missed Tokutek now part of the Percona family.)

Thanks to Facebook – they provide LinkBench, a benchmark that emulates the social graph …

I had not reviewed bug fixes in MySQL 5.6 for quite a some time, so I decided to check what bugs reported by MySQL Community were fixed in recently released MySQL 5.6.24. I'll mention both a bug reporter and engineer who verified the bug in the list below, because I still think that in MySQL world names should matter.

So, MySQL 5.6.24 includes fixes for the following bugs from http://bugs.mysql.com. I'd start with InnoDB and memcached-related fixes:

• Bug #72080 - truncate temporary table crash: !DICT_TF2_FLAG_IS_SET(table, DICT_TF2_TEMPORARY). Reported by …

For years it was very easy to defend InnoDB’s advantage over competition – covering index reads were saving I/O operations and CPU everywhere, table space and I/O management allowed to focus on database and not on file systems or virtual memory behaviors, and for past few years InnoDB compression was the way to have highly efficient OLTP (or in our case – SGTP – Social Graph Transaction Processing) environments. Until one day (for some it came sooner, for others later)…

InnoDB team announced that it will change how it is going to do compression in the future and that old ways (that we rely on) will be all gone. I’m not exactly sure if there was any definite messaging on the future of existing methods, but Oracle in public will never put out a roadmap, and there’s lots of uncertainty involved then. Unfortunately, with this uncertainty, we probably lost quite some momentum in InnoDB engineering efforts (we don’t get to see some …