As you transition away from
lower the value of the
option to free memory no longer needed for caching results.
Increase the value of the
configuration option, which performs a similar role of allocating
cache memory for
InnoDB tables. The
pool caches both table data and index data, speeding up
lookups for queries and keeping query results in memory for reuse.
For guidance regarding buffer pool size configuration, see
Section 188.8.131.52, “How MySQL Uses Memory”.
On a busy server, run benchmarks with the query cache turned off.
InnoDB buffer pool provides similar
benefits, so the query cache might be tying up memory
unnecessarily. For information about the query cache, see
Section 8.10.3, “The MySQL Query Cache”.
MyISAM tables do not support
transactions, you might
not have paid much attention to the
autocommit configuration option
statements. These keywords are important to allow multiple
sessions to read and write
concurrently, providing substantial scalability benefits in
While a transaction is open, the system keeps a snapshot of the data as seen at the beginning of the transaction, which can cause substantial overhead if the system inserts, updates, and deletes millions of rows while a stray transaction keeps running. Thus, take care to avoid transactions that run for too long:
If you are using a mysql session for interactive experiments, always
COMMIT(to finalize the changes) or
ROLLBACK(to undo the changes) when finished. Close down interactive sessions rather than leave them open for long periods, to avoid keeping transactions open for long periods by accident.
ROLLBACKis a relatively expensive operation, because
DELETEoperations are written to
InnoDBtables prior to the
COMMIT, with the expectation that most changes are committed successfully and rollbacks are rare. When experimenting with large volumes of data, avoid making changes to large numbers of rows and then rolling back those changes.
When loading large volumes of data with a sequence of
COMMITthe results to avoid having transactions that last for hours. In typical load operations for data warehousing, if something goes wrong, you truncate the table (using
TRUNCATE TABLE) and start over from the beginning rather than doing a
The preceding tips save memory and disk space that can be wasted
during too-long transactions. When transactions are shorter than
they should be, the problem is excessive I/O. With each
COMMIT, MySQL makes sure each
change is safely recorded to disk, which involves some I/O.
For most operations on
InnoDBtables, you should use the setting
autocommit=0. From an efficiency perspective, this avoids unnecessary I/O when you issue large numbers of consecutive
DELETEstatements. From a safety perspective, this allows you to issue a
ROLLBACKstatement to recover lost or garbled data if you make a mistake on the mysql command line, or in an exception handler in your application.
The time when
autocommit=1is suitable for
InnoDBtables is when running a sequence of queries for generating reports or analyzing statistics. In this situation, there is no I/O penalty related to
InnoDBcan automatically optimize the read-only workload.
If you make a series of related changes, finalize all the changes at once with a single
COMMITat the end. For example, if you insert related pieces of information into several tables, do a single
COMMITafter making all the changes. Or if you run many consecutive
INSERTstatements, do a single
COMMITafter all the data is loaded; if you are doing millions of
INSERTstatements, perhaps split up the huge transaction by issuing a
COMMITevery ten thousand or hundred thousand records, so the transaction does not grow too large.
You might see warning messages referring to
“deadlocks” in the MySQL error log, or the output of
SHOW ENGINE INNODB
STATUS. Despite the scary-sounding name, a
deadlock is not a serious
InnoDB tables, and often does not
require any corrective action. When two transactions start
modifying multiple tables, accessing the tables in a different
order, they can reach a state where each transaction is waiting
for the other and neither can proceed. MySQL immediately detects
this condition and cancels (rolls
back) the “smaller” transaction, allowing the
other to proceed.
Your applications do need error-handling logic to restart a transaction that is forcibly cancelled like this. When you re-issue the same SQL statements as before, the original timing issue no longer applies. Either the other transaction has already finished and yours can proceed, or the other transaction is still in progress and your transaction waits until it finishes.
If deadlock warnings occur constantly, you might review the application code to reorder the SQL operations in a consistent way, or to shorten the transactions.
For more information, see Section 14.8.5, “Deadlocks in InnoDB”.
To get the best performance from
you can adjust a number of parameters related to storage layout.
When you convert
MyISAM tables that are large,
frequently accessed, and hold vital data, investigate and consider
options, and the
KEY_BLOCK_SIZE clauses of the
CREATE TABLE statement.
During your initial experiments, the most important setting is
innodb_file_per_table. When this
setting is enabled, new
InnoDB tables are
implicitly created in
tablespaces. In contrast with the
tablespace, file-per-table tablespaces allow disk space to be
reclaimed by the operating system when a table is truncated or
dropped. File-per-table tablespaces also support the
Barracuda file format and
associated features such as table compression and efficient
off-page storage for long variable-length columns. For more
information, see Section 14.10.4, “InnoDB File-Per-Table Tablespaces”.
To convert a non-
InnoDB table to use
ALTER TABLE table_name ENGINE=InnoDB;
Do not convert MySQL system tables in the
mysql database (such as
host) to the
InnoDB type. This is an unsupported
operation. The system tables must always be of the
You might make an
InnoDB table that is a clone
of a MyISAM table, rather than using
TABLE to perform conversion, to test the old and new
table side-by-side before switching.
Create an empty
InnoDB table with identical
column and index definitions. Use
SHOW CREATE TABLE
to see the full
CREATE TABLE statement to use.
ENGINE clause to
To transfer a large volume of data into an empty
InnoDB table created as shown in the previous
section, insert the rows with
innodb_table SELECT * FROM
myisam_table ORDER BY
You can also create the indexes for the
table after inserting the data. Historically, creating new
secondary indexes was a slow operation for InnoDB, but now you can
create the indexes after the data is loaded with relatively little
overhead from the index creation step.
If you have
UNIQUE constraints on secondary
keys, you can speed up a table import by turning off the
uniqueness checks temporarily during the import operation:
SET unique_checks=0; ... import operation ... SET unique_checks=1;
For big tables, this saves disk I/O because
InnoDB can use its
change buffer to write
secondary index records as a batch. Be certain that the data
contains no duplicate keys.
unique_checks permits but does
not require storage engines to ignore duplicate keys.
For better control over the insertion process, you can insert big tables in pieces:
INSERT INTO newtable SELECT * FROM oldtable WHERE yourkey > something AND yourkey <= somethingelse;
After all records are inserted, you can rename the tables.
During the conversion of big tables, increase the size of the
InnoDB buffer pool to reduce disk I/O, to a
maximum of 80% of physical memory. You can also increase the size
InnoDB log files.
If you intend to make several temporary copies of your data in
InnoDB tables during the conversion process, it
is recommended that you create the tables in file-per-table
tablespaces so that you can reclaim the disk space when you drop
the tables. When the
configuration option is enabled (the default), newly created
InnoDB tables are implicitly created in
Whether you convert the
MyISAM table directly
or create a cloned
InnoDB table, make sure that
you have sufficient disk space to hold both the old and new tables
during the process.
InnoDB tables require
more disk space than
ALTER TABLE operation runs
out of space, it starts a rollback, and that can take hours if it
is disk-bound. For inserts,
InnoDB uses the
insert buffer to merge secondary index records to indexes in
batches. That saves a lot of disk I/O. For rollback, no such
mechanism is used, and the rollback can take 30 times longer than
In the case of a runaway rollback, if you do not have valuable data in your database, it may be advisable to kill the database process rather than wait for millions of disk I/O operations to complete. For the complete procedure, see Section 14.23.2, “Forcing InnoDB Recovery”.
PRIMARY KEY clause is a critical factor
affecting the performance of MySQL queries and the space usage for
tables and indexes. The primary key uniquely identifies a row in a
table. Every row in the table must have a primary key value, and
no two rows can have the same primary key value.
These are guidelines for the primary key, followed by more detailed explanations.
PRIMARY KEYfor each table. Typically, it is the most important column that you refer to in
WHEREclauses when looking up a single row.
Choose the column and its data type carefully. Prefer numeric columns over character or string ones.
Consider using an auto-increment column if there is not another stable, unique, non-null, numeric column to use.
An auto-increment column is also a good choice if there is any doubt whether the value of the primary key column could ever change. Changing the value of a primary key column is an expensive operation, possibly involving rearranging data within the table and within each secondary index.
Consider adding a primary key to any table that does not already have one. Use the smallest practical numeric type based on the maximum projected size of the table. This can make each row slightly more compact, which can yield substantial space savings for large tables. The space savings are multiplied if the table has any secondary indexes, because the primary key value is repeated in each secondary index entry. In addition to reducing data size on disk, a small primary key also lets more data fit into the buffer pool, speeding up all kinds of operations and improving concurrency.
If the table already has a primary key on some longer column, such
VARCHAR, consider adding a new unsigned
AUTO_INCREMENT column and switching the primary
key to that, even if that column is not referenced in queries.
This design change can produce substantial space savings in the
secondary indexes. You can designate the former primary key
UNIQUE NOT NULL to enforce the same
constraints as the
PRIMARY KEY clause, that is,
to prevent duplicate or null values across all those columns.
If you spread related information across multiple tables, typically each table uses the same column for its primary key. For example, a personnel database might have several tables, each with a primary key of employee number. A sales database might have some tables with a primary key of customer number, and other tables with a primary key of order number. Because lookups using the primary key are very fast, you can construct efficient join queries for such tables.
If you leave the
PRIMARY KEY clause out
entirely, MySQL creates an invisible one for you. It is a 6-byte
value that might be longer than you need, thus wasting space.
Because it is hidden, you cannot refer to it in queries.
The reliability and scalability features of
InnoDB require more disk storage than
MyISAM tables. You might change the
column and index definitions slightly, for better space
utilization, reduced I/O and memory consumption when processing
result sets, and better query optimization plans making efficient
use of index lookups.
If you do set up a numeric ID column for the primary key, use that
value to cross-reference with related values in any other tables,
particularly for join queries.
For example, rather than accepting a country name as input and
doing queries searching for the same name, do one lookup to
determine the country ID, then do other queries (or a single join
query) to look up relevant information across several tables.
Rather than storing a customer or catalog item number as a string
of digits, potentially using up several bytes, convert it to a
numeric ID for storing and querying. A 4-byte unsigned
INT column can index over 4 billion
items (with the US meaning of billion: 1000 million). For the
ranges of the different integer types, see
Section 11.2.1, “Integer Types (Exact Value) - INTEGER, INT, SMALLINT, TINYINT,
InnoDB files require more care and planning
MyISAM files do.
Methods of moving or copying
InnoDBtables to a different server are described in Section 184.108.40.206, “Moving or Copying InnoDB Tables”.