MySQL Enterprise Monitor collects a huge amount of information about MySQL and the systems that it runs on. To do this, it employs an “Agent” to collect these statistics.

This can either sit locally to the database server, or on a remote host – perhaps even the same host as the Dashboard server if you decide you don’t want to distribute it to many boxes – and checks when it is local or remote, to decide whether to collect OS statistics or not. A single agent can monitor either a single or multiple instances from the same process.

Not all of the information that it can collect is fully exposed within the UI yet however (there are so many things …

Following up to my previous blog on graphing statement execution in performance_schema, Sunny Bains on the InnoDB team pointed out that in looking at the INSERT graph, he didn’t think I had atomic operations enabled within my build.

Particularly here (from trunk):

225 /******************************************************************//**
226 Increments lock_word the specified amount and returns new value.
227 @return lock->lock_word after increment */
228 UNIV_INLINE
229 lint
230 rw_lock_lock_word_incr(
231 /*===================*/
232         rw_lock_t*      lock,           /*!< in/out: rw-lock */
233         ulint           amount)         /*!< in: amount of increment */
234 {
235 #ifdef …

The ever increasing performance demands of web-based services has generated significant interest in providing NoSQL access methods to MySQL - enabling users to maintain all of the advantages of their existing relational database infrastructure, while providing blazing fast performance for simple queries, using an API to complement regular SQL access to their data.

The HandlerSocket development at DeNA is a great example of community innovation, with a solution implemented as a custom plug-in and protocol for the MySQL server daemon.

We are hearing the community say they want NotOnly SQL - they want their trusted SQL RDBMS - plus, they want NoSQL techniques to access that data. So, we are previewing our NotOnlySQL solution for MySQL - delivered via memcached - with implementations to access both the InnoDB and MySQL Cluster (NDB) storage …

The ever increasing performance demands of web-based services has generated significant interest in providing NoSQL access methods to MySQL - enabling users to maintain all of the advantages of their existing relational database infrastructure, while providing blazing fast performance for simple queries, using an API to complement regular SQL access to their data.

The HandlerSocket development at DeNA is a great example of community innovation, with a solution implemented as a custom plug-in and protocol for the MySQL server daemon.

We are hearing the community say they want NotOnly SQL - they want their trusted SQL RDBMS - plus, they want NoSQL techniques to access that data. So, we are previewing our NotOnlySQL solution for MySQL - delivered via memcached - with implementations to access both the InnoDB and MySQL Cluster (NDB) storage …

I had a quick look at the source tree (I haven’t compiled it, just read the source – that’s what I do. I challenge any C/C++ compiler to keep up with my brain!) that’s got a tarball up on labs.mysql.com for the memcached interface to innodb. A few quick thoughts:

• Where’s the Bazaar tree on launchpad? I hate pulling tarballs, following the dev tree is much more interesting from a tech perspective (especially for early development releases). I note that the NDB memcached stuff is up on launchpad now, so yay there. I would love it if the InnoDB team in general was much more open with development, especially with having source trees up on launchpad.
• It embeds a copy of the memcached server engines branch into the MySQL tree. This is probably the correct way to go. There is no real sense in re-implementing the protocol and network stack (this is about half what memcached is anyway).
• The copy of the …

MySQL is the most popular open source SQL database. The ever-increasing performance demands of web-based services have generated significant interest in providing NoSQL access methods to MySQL. Today, MySQL is announcing the preview of the NoSQL to InnoDB via memcached. This offering provides users with the best of both worlds – maintain all of the advantages of rich SQL query language, while providing better performance for simple queries via direct access to shared data.

In this preview release, memcached is implemented as a MySQL plugin daemon, accessing InnoDB directly via the native InnoDB API:

Features provided in the current release:

• Memcached as a daemon plugin of mysqld: both mysqld and memcached are running in the same process space, with very low latency access to data
…

In MySQL 5.6.2 we have introduced a new background thread named the page_cleaner in InnoDB. Adaptive flushing of modified buffer pool pages in the main background thread, async flushing by a foreground query thread if the log files are near to wrapping around, idle flushing and shutdown flushing are now moved to this thread, leaving only the last resort sync flushing in foreground query threads. We’ve also added counters for these activities.

As page_cleaner is all about the flushing of dirty pages to disk it’ll do you a world of good if you can go through this post where I have explained different types of flushing that happen inside InnoDB and the conditions that trigger flushing. The page_cleaner thread is only concerned with flush_list flushing (this may change in future releases). So let us dig a bit deeper into why …

I recently worked on a customer case where at seemingly random times, inserts would fail with Innodb error 139. This is a rather simple problem, but due to it’s nature, it may only affect you after you already have a system running in production for a while.

Suppose you have the following table structure:

CREATE TABLE example (
id INT UNSIGNED NOT NULL AUTO_INCREMENT,
fname TEXT NOT NULL,
fcomment TEXT,
ftitle TEXT NOT NULL,
fsubtitle TEXT NOT NULL,
fcontent TEXT NOT NULL,
fheader TEXT,
ffooter TEXT,
fdisclaimer TEXT,
fcopyright TEXT,
fstylesheet TEXT,
fterms TEXT,
PRIMARY KEY (id)
) Engine=InnoDB;

Now you insert some test data into it:
mysql> INSERT INTO example
-> VALUES (
->   NULL,
->   'First example',
->   'First comment',
->   'First title',
->   'First subtitle',
->   'First …

Purpose

What does purge exactly do and why is it needed? If you have ever wondered then read on. It is really a type of garbage collector. When a user issues a DML like “DELETE FROM t WHERE c = 1;”, InnoDB doesn’t remove the matching record. This is what happens under the hood:

1. It marks the record as deleted by setting a bit in the control bits of the record.
2. Stores the before image of the modified columns to the UNDO log
3. Updates the system columns DB_TRX_ID and DB_ROLL_PTR in the clustered index record. DB_TRX_ID identifies the transaction that made the last change, and DB_ROLL_PTR points to the new UNDO log record. This UNDO log record contains the old values of DB_TRX_ID and DB_ROLL_PTR, possibly pointing to an older transaction and undo log entry.

From …

Why use PBMS?

I have talked to people about why they should use PBMS to handle BLOB data often enough, so I was surprised when someone asked me where they could find this information and I discovered I had never actually written it down anywhere.  So here it is.
If you are unfamiliar with PBMS, PBMS stands for PrimeBase Media Streaming. For details please have a look at the home page for BLOB Streaming.
  Both MySQL and Drizzle are not designed to handle BLOB data efficiently. This is not a storage engine problem, most storage engines can store BLOB data reasonably efficiently, but the problem is in the server architecture itself. The problem is that the BLOB data is transferred to and from the server as part of the regular result set. To do this both the server and the client must allocate a buffer large enough to hold the entire BLOB. DBMSs …