John Russell is the InnoDB documentation lead for MySQL. He lives in Berkeley, California and hails from Newfoundland, Canada. He comes to MySQL from the documentation group at Oracle, where he has worked since 1999. Prior to Oracle, he worked at IBM in the programming languages and DB2 groups.
It's been a busy year for MySQL. Perhaps you've heard. Here are some recent improvements to the speed, scalability, and user-friendliness of the MySQL database and the InnoDB storage engine that we think deserve their own headlines. Now is a great time to beta test the 5.5 release and give feedback to the MySQL engineering team.
MySQL sometimes gets knocked about features such as as ACID-compliant transactions, foreign key support, and crash recovery. These features are strongest in the InnoDB storage engine, but MyISAM has always been the default, so new users could get the wrong impression. Starting in MySQL 5.5, InnoDB is the default storage engine, so that everyone can see this reliability and stability out of the box. As a bonus, the level of InnoDB in MySQL 5.5 is InnoDB 1.1, a rearchitected InnoDB with many performance and scalability features over and above the built-in InnoDB in 5.1 and before. (Since we are unifying the InnoDB within MySQL using the best and fastest technology, we are phasing out the
Built-In distinction; MySQL 5.5 comes with the latest and greatest InnoDB 1.1.) Read more about the latest InnoDB enhancements below.
If a table is referenced within a transaction, no other transaction can perform DDL such as DROP TABLE or ALTER TABLE until the first transaction commits. Previously, the lock was released at the end of a statement rather than the whole transaction. Read more about metadata locking within transactions.
If your company uses Windows by itself or in a mixed environment, you probably want to deploy MySQL databases on Windows. To make that a reality, the MySQL team has incorporated a number of Windows-specific features for speeding up and scaling up.
This feature improves the reliability of failover, to avoid failing over to a slave that is missing some committed changes from the master. You can choose to have commits on the master node wait until at least one slave has logged the relevant events for the transaction. The
semi-synchronous aspect is because the master does not wait for all the slaves to acknowledge, and there is a protocol to avoid the master waiting too long if the slaves fall behind. Read more about semisynchronous replication.
In replication, the
heartbeat is a message sent at regular intervals from a master node to the slave nodes. You can configure the heartbeat period. If the message is not received, the slave knows that the master node has failed. You can now avoid the spurious relay log rotation when the master is idle, rely on an more precise failure detection mechanism, and have an accurate estimation for seconds behind master. (This is a different feature than
Linux heartbeat, which is a similar health-checking system for cluster nodes.) To use this feature, you issue commands like:
STOP SLAVE; CHANGE MASTER TO master_heartbeat_period= milliseconds; START SLAVE; SHOW STATUS like 'slave_heartbeat period' SHOW STATUS like 'slave_received_heartbeats'
The SIGNAL and RESIGNAL statements allow you to implement familiar exception-handling logic in your stored procedures, stored functions, triggers, events, and database applications that call those things. SIGNAL passes execution back to an error handler, like THROW or RAISE statements in other languages. You can encode the error number, SQLSTATE value, and a message in a consistent way that can be interpreted by an error handler in the calling program. RESIGNAL lets you propagate the exception after doing some amount of error handling and cleanup yourself. With RESIGNAL, you can pass along the original error information or modify it. Read more about SIGNAL/RESIGNAL.
With the new RANGE COLUMNS and LIST COLUMNS clauses of the CREATE TABLE statement, partitioning is now more flexible and also can optimize queries better. Instead of expressions, you specify the names of one or more columns. Both of these clauses let you partition based on DATE, DATETIME, or string values (such as CHAR or VARCHAR). Partition pruning can optimize queries on tables that use RANGE COLUMNS or LIST COLUMMS partitioning, and WHERE conditions that compare different columns and constants, such as
a = 10 AND b > 5
a < "2005-11-25" AND b = 10 AND c = 50
The Performance Schema feature involves an optional schema, named performance_schema, with tables that you can query to see intimate details of low-level MySQL performance. You can get information about performance right at that moment, or various amounts of historical performance data. You can clear the data to reset the figures, filter and format the data using WHERE clauses, and generally interact with it using all sorts of SQL goodness. Performance Schema data now also includes details about the InnoDB storage engine. Read more about Performance Schema.
To make a long story short: it's all about performance and scalability! To those who enjoy trying all permutations of configuration settings, we apologize in advance for making so many of these improvements take no thought or effort at all.
At this year's MySQL Conference & Expo, you'll hear about the InnoDB Plugin 1.0.7, the first production-ready (GA) release of the InnoDB Plugin. Most of the enhancements listed here are from InnoDB 1.1, which is part of MySQL 5.5 and thus is still in beta. Download MySQL 5.5 and try them out.
One of InnoDB's great strengths is its ability to reliably recover data after any type of crash that affects the database. But this cleanup and checking makes the next restart take longer. Well, cover up your sundial. Put away your hourglass. The enterprising InnoDB team has improved the algorithms involved in recovery by a huge amount -- in computer science terms, it's a better
big-O number. Now you will need to keep your finger ready on the stopwatch to see how long recovery takes. This feature is available both in InnoDB 1.1 and the InnoDB Plugin 1.0.7. Read more about faster recovery.
With today's buffer pools frequently in the multi-gigabyte range, pages are constantly being read and updated by different database threads. This enhancement removes the
bottleneck that makes all the other threads wait when one thread is updating the buffer pool. All the structures normally associated with the buffer pool can now be multiplied, such as the mutex that protects it, the LRU information, and the flush list. You control how many buffer pool instances are used; the default is still 1. This feature works best with combined buffer pool sizes of several gigabytes, where each buffer pool instance can be a gigabyte or more. Read more about multiple buffer pool instances.
This feature is both a performance and a scalability improvement. By dividing the single rollback segment into multiple parts, InnoDB allows concurrent transactions to create undo data (from insert, update, and delete operations) without making each other wait. A happy consequence is that the old limit of 1023 simultaneous inserting / updating / deleting transactions is now much higher, for a total of approximately 128K concurrent writer transactions. This feature does not introduce any incompatibility in the InnoDB file format, and does not require using the newer
Barracuda file format. However, the setup within the system tablespace only takes place when the system tablespace is created, so to take advantage of this feature, you must create a new instance (not just a new table or a new database) and import the data into it. Read more about multiple rollback segments.
This feature enables better concurrency of I/O requests on Linux systems. With asynchronous I/O, an I/O request can be sent off and the thread servicing the query does not need to wait for the I/O to complete; that aspect is delegated to the I/O helper threads. InnoDB already supported asynchronous I/O on Windows systems. On platforms other than Windows, InnoDB internally arranged its I/O calls as if they were asynchronous (leading to the term
simulated asynchronous I/O), but behind the scenes the query thread really would block until the request finished. Now true asynchronous I/O support (called
native asynchronous I/O so it won't be confused with references to
asynchronous already in the source) is available on Linux as well as Windows. This feature requires the libaio userspace library to be installed on Linux. It comes with a configuration option innodb_use_native_aio that you can turn off in case of any startup problems related to the I/O subsystem. Read more about asynchronous I/O for Linux.
InnoDB uses indexes to make queries faster. Secondary indexes, those on columns other than the primary key, require work (meaning disk writes) to keep them up to date when those those columns are inserted, deleted, or updated. For example, if you run the command DELETE FROM t WHERE c1 = 'something';, and you have a secondary index on column c2, what's the rush to update that secondary index? Its contents might not be in the buffer pool, and maybe the index won't be read for a long time.
InnoDB has had an optimization for a while now to delay disk writes for secondary index maintenance when the changes are due to inserts. This delay waits for the index contents to be read into the buffer pool for some other reason, such as a query, where the changes can be made quickly in memory and then flushed back to disk using the normal schedule for writing dirty blocks. When the changes in the buffer pool affect a group of sequential disk blocks, they can be flushed more efficiently than if the data was written piece by piece. Very clever!
In InnoDB 1.1, this technique is extended to include the different kinds of writes caused by deletes (an initial
delete marking operation, followed later by a
purge operation that garbage-collects all the deleted records). This optimization is under your control through the innodb_change_buffering configuration option, which has a new default of all. (We call the optimization
change buffering rather than the old name
insert buffering; the actual memory structure is still called the
insert buffer.) Read more about enhanced change buffering.
The scalability improvements in InnoDB 1.1 revolve around better isolation of threads and mutex contention. These are performance-type improvements that really kick in when the database server is heavily loaded. (For those of you who are not yet experts on InnoDB performance,
mutexes are in-memory structures that prevent different threads from interfering with each others' changes to important memory areas like the buffer pool.)
Previously, a single mutex protected different memory areas related to the undo and logging information. In particular, this mutex blocked access to the buffer pool, while changes were being written there by DDL operations making changes to the data dictionary. Splitting the old log_sys mutex to create a separate log_flush_order mutex means that all of this internal processing can happen with less waiting and less blocking of other operations involving the buffer pool, without any configuration needed on your part. Read more about improved log sys mutex.
Along the same lines, operations involving the buffer pool and the flush list previously were protected by a single mutex, which could cause unnecessary delays. (The buffer pool mutex has historically been very
hot, so any other operation that tied up the buffer pool was adding fuel to the fire.) Now the flush list has its own mutex, reducing contention with buffer pool operations and making InnoDB faster without any configuration needed on your part. Read more about separate flush list mutex.
The InnoDB purge operation is a type of garbage collection that runs periodically. Previously, the purge was part of the master thread, meaning that it could block some other database operations. Now, this operation can run in its own thread, allowing for more concurrency. You can control whether the purge operation is split into its own thread with the innodb_purge_threads configuration option, which can be set to 0 (the default) or 1 (for a single separate purge thread). This architectural change might not cause a big speedup with this single purge thread, but it lays the groundwork to tune other bottlenecks related to purge operations, so that in the future multiple purge threads could provide a bigger performance gain. The configuration option innodb_purge_batch_size can be set from 1 to 5000, with default of 20, although typical users should not need to change that setting. Read more about improved purge scheduling.
The Performance Schema has been part of MySQL 5.5 for a while now. InnoDB 1.1 is instrumented for the first time for Performance Schema monitoring, with statistics available for InnoDB-specific mutexes, rw-locks, threads, and I/O operations. The data is structured so that you can see everything, or filter to see just the InnoDB items. The information in the performance_schema tables lets you see how these items factor into overall database performance, which ones are the
hottest under various workloads and system configurations, and trace issues back to the relevant file and line in the source code so you can really see what's happening behind the scenes. Read more about InnoDB integration with Performance Schema.
Now that you have read about all the exciting new performance and scalability improvements, it's your turn to take MySQL 5.5 for a spin: