You can get the default buffer sizes used by the
with this command:
shell> mysqld --help
This command produces a list of all
mysqld options and configurable
variables. The output includes the default values and looks something
Possible variables for option --set-variable (-O) are: back_log current value: 5 connect_timeout current value: 5 join_buffer current value: 131072 key_buffer current value: 1048540 long_query_time current value: 10 max_allowed_packet current value: 1048576 max_connections current value: 90 max_connect_errors current value: 10 max_join_size current value: 4294967295 max_sort_length current value: 1024 net_buffer_length current value: 16384 record_buffer current value: 131072 sort_buffer current value: 2097116 table_cache current value: 64 tmp_table_size current value: 1048576 thread_stack current value: 131072 wait_timeout current value: 28800
If there is a
mysqld server currently running, you can see what
values it actually is using for the variables by executing this command:
shell> mysqladmin variables
Each option is described below. Values for buffer sizes, lengths and stack
sizes are given in bytes. You can specify values with a suffix of `K'
or `M' to indicate kilobytes or megabytes. For example,
indicates 16 megabytes. Case of suffix letters does not matter;
16m are equivalent.
back_logvalue indicates how many requests can be stacked during this short time before MySQL momentarily stops answering new requests. You need to increase this only if you expect a large number of connections in a short period of time. In other words, this value is the size of the listen queue for incoming TCP/IP connections. Your operating system has its own limit on the size of this queue. The manual page for the Unix system call
listen(2)should have more details. Check your OS documentation for the maximum value for this variable. Attempting to set
back_loghigher than this maximum will be ineffective.
mysqldserver is waiting for a connect packet before responding with
key_bufferis the size of the buffer used for index blocks. You might want to increase this value when doing many
INSERToperations on a table with lots of indexes. To get even more speed, use
LOCK TABLES. See section 7.23
LOCK TABLES/UNLOCK TABLESsyntax.
net_buffer_lengthbytes, but can grow up to
max_allowed_packetbytes when needed. This value by default is small to catch big (possibly wrong) packets. You must increase this value if you are using big
BLOBcolumns. It should be as big as the biggest
BLOByou want to use.
mysqldrequires. See below for comments on file descriptor limits.
max_join_sizerecords return an error. Set this value if your users tend to perform joins without a
WHEREclause that take a long time and return millions of rows.
TEXTvalues (only the first
max_sort_lengthbytes of each value are used; the rest are ignored).
GROUP BYoperations. See section 16.4 Where MySQL stores temporary files.
mysqldrequires. MySQL needs two file descriptors for each unique open table. See below for comments on file descriptor limits. For information about how the table cache works, see section 10.6 How MySQL opens and closes tables.
The table tbl_name is full. Increase the value of
tmp_table_sizeif you do many advanced
crash-metest are dependent on this value. The default is normally large enough. See section 11 The MySQL benchmark suite.
max_connections affect the maximum
number of files the server keeps open. If you increase one or both of these
values, you may run up against a limit imposed by your operating system on
the per-process number of open file descriptors. However, you can increase
the limit on many systems. Consult your OS documentation to find out how to
do this, because the method for changing the limit varies widely from system
table_cache is related to
For example, for 200 open connections, you should have a table cache of
200 * n, where
n is the maximum number of tables in
MySQL uses algorithms that are very scalable, so you can usually run with very little memory or give MySQL more memory to get better performance.
If you have much memory and many tables and want maximum performance with a moderate number of clients, you should use something like this:
shell> safe_mysqld -O key_buffer=16M -O table_cache=128 \ -O sort_buffer=4M -O record_buffer=1M &
If you have little memory and lots of connections, use something like this:
shell> safe_mysqld -O key_buffer=512k -O sort_buffer=100k \ -O record_buffer=100k &
shell> safe_mysqld -O key_buffer=512k -O sort_buffer=16k \ -O table_cache=32 -O record_buffer=8k -O net_buffer=1K &
If there are very many connections, "swapping problems" may occur unless
mysqld has been configured to use very little memory for each
mysqld performs better if you have enough memory for all
connections, of course.
Note that if you change an option to
mysqld, it remains in effect only
for that instance of the server.
To see the effects of a parameter change, do something like this:
shell> mysqld -O key_buffer=32m --help
Make sure that the
--help option is last; otherwise, the effect of any
options listed after it on the command line will not be reflected in the
The list below indicates some of the ways that the
uses memory. Where applicable, the name of the server variable relevant
to the memory use is given.
key_buffer) is shared by all threads; Other buffers used by the server are allocated as needed.
thread_stack) a connection buffer (variable
net_buffer_length), and a result buffer (variable
net_buffer_length). The connection buffer and result buffer are dynamicly enlarged up to
max_allowed_packetwhen needed. When a query is running a copy of the current query string is also alloced.
BLOBcolumns are stored on disk. One current problem is that if a HEAP table exceeds the size of
tmp_table_size, you get the error
The table tbl_name is full. In the future, we will fix this by automatically changing the in-memory (HEAP) table to a disk-based (NISAM) table as necessary. To work around this problem, you can increase the temporary table size by setting the
mysqld, or by setting the SQL option
SQL_BIG_TABLESin the client program. See section 7.24
SET OPTIONsyntax. In MySQL 3.20, the maximum size of the temporary table was
record_buffer*16, so if you are using this version, you have to increase the value of
record_buffer. You can also start
--big-tablesoption to always store temporary tables on disk, however, this will affect the speed of all complicated queries.
3 * nis allocated (where
nis the maximum row length, not counting
BLOBuses 5 to 8 bytes plus the length of the
BLOBcolumns, a buffer is enlarged dynamically to read in larger
BLOBvalues. If you scan a table, a buffer as large as the largest
BLOBvalue is allocated.
mysqladmin flush-tablescommand closes all tables that are not in use and marks all in-use tables to be closed when the currently executing thread finishes. This will effectively free most in-use memory.
ps and other system status programs may report that
uses a lot of memory. This may be caused by thread-stacks on different
memory addresses. For example, the Solaris version of
the unused memory
between stacks as used memory. You can verify this by checking available
swap -s. We have tested
mysqld with commercial
memory-leakage detectors, so there should be no memory leaks.
Most of the following tests are done on Linux and with the MySQL benchmarks, but they should give some indication for other operating systems.
You get the fastest executable when you link with
-static. Using Unix
sockets rather than TCP/IP to connect to a database also gives better
On Linux, you will get the fastest code when compiling with
-O6. To compile `sql_yacc.cc' with these options, you need 180M
gcc/pgcc needs a lot of memory to make all functions inline.
You should also set
CXX=gcc when configuring MySQL to avoid
inclusion of the
pgccand compile everything with
mysqldserver is 11% faster than with
-static), the result is 13% slower.
gcc2.7.3 is 13% faster than Sun Pro C++ 4.2.
The MySQL-Linux distribution provided by TcX is compiled with
pgcc and linked statically.
All indexes (
INDEX()) are stored
in B-trees. Strings are automatically prefix- and end-space compressed.
See section 7.26
CREATE INDEX syntax (Compatibility function).
Indexes are used to:
MIN()value for a specific key.
ORDER BY key_part_1,key_part_2). The key is read in reverse order if all key parts are followed by
Suppose you issue the following
mysql> SELECT * FROM tbl_name WHERE col1=val1 AND col2=val2;
If a multiple-column index exists on
appropriate rows can be fetched directly. If separate single-column
indexes exist on
col2, the optimizer decides
which index will find fewer rows and uses that index to fetch the rows.
If the table has a multiple-column index, any leftmost prefix of the
index can be used by the optimizer to find rows. For example, if you
have a three-column index on
(col1,col2,col3), you have indexed search
MySQL can't use a partial index if the columns don't form a leftmost
prefix of the index.
Suppose you have the
SELECT statements shown below:
mysql> SELECT * FROM tbl_name WHERE col1=val1; mysql> SELECT * FROM tbl_name WHERE col2=val2; mysql> SELECT * FROM tbl_name WHERE col2=val2 AND col3=val3;
If an index exists on
(col1,col2,col3), only the first query shown
above uses the index. The second and third queries do involve indexed
(col2,col3) are not leftmost prefixes
MySQL also uses indexes for
LIKE comparisons if the argument
LIKE is a constant string that doesn't start with a wildcard
character. For example, the following
SELECT statements use indexes:
mysql> select * from tbl_name where key_col LIKE "Patrick%"; mysql> select * from tbl_name where key_col LIKE "Pat%_ck%";
In the first statement, only rows with
"Patrick" <= key_col <
"Patricl" are considered. In the second statement, only rows with
"Pat" <= key_col < "Pau" are considered.
SELECT statements will not use indexes:
mysql> select * from tbl_name where key_col LIKE "%Patrick%"; mysql> select * from tbl_name where key_col LIKE other_col;
In the first statement, the
LIKE value begins with a wildcard character.
In the second statement, the
LIKE value is not a constant.
(This section is incomplete; MySQL does many optimizations.)
when you want to make a slow
SELECT ... WHERE faster, the first thing
to check is whether or not you can add an index. All references between
different tables should usually be done with indexes. You can use
EXPLAIN command to determine which indexes are used for a
See section 7.21
EXPLAIN syntax (Get information about a
Some of the optimizations performed by MySQL are listed below:
((a AND b) AND c OR (((a AND b) AND (c AND d)))) -> (a AND b AND c) OR (a AND b AND c AND d)
(a<b AND b=c) AND a=5 -> b>5 AND b=c AND a=5
(B>=5 AND B=5) OR (B=6 AND 5=5) OR (B=7 AND 5=6) -> B=5 OR B=6
COUNT(*)on a single table without a
WHEREis retrieved directly from the table information. This is also done for any
NOT NULLexpression when used with only one table.
SELECTstatements are impossible and returns no rows.
HAVINGis merged with
WHEREif you don't use
GROUP BYor group functions (
WHEREis constructed to get a fast
WHEREevaluation for each sub join and also to skip records as soon as possible.
LIKEwith a non-wildcard prefix like
ANDlevels in the
WHEREclause is not used to optimize the query. The following
WHEREclauses use indexes:
... WHERE index_part1=1 AND index_part2=2 ... WHERE index=1 OR A=10 AND index=2 /* index = 1 OR index = 2 */ ... WHERE index_part1='hello' AND index_part_3=5 /* optimized like "index_part1='hello'" */These
WHEREclauses do NOT use indexes:
... WHERE index_part2=1 AND index_part3=2 /* index_part_1 is not used */ ... WHERE index=1 OR A=10 /* No index */ ... WHERE index_part1=1 OR index_part2=10 /* No index spans all rows */
WHEREclause on a
UNIQUEindex or a
PRIMARY KEY, where all index parts are used with constant expressions.
mysql> SELECT * FROM t WHERE primary_key=1; mysql> SELECT * FROM t1,t2 WHERE t1.primary_key=1 AND t2.primary_key=t1.id;
ORDER BYand in
GROUP BYcome from the same table, then this table is preferred first when joining.
ORDER BYclause and a different
GROUP BYclause, or if the
GROUP BYcontains columns from tables other than the first table in the join queue, a temporary table is created.
HAVINGclause are skipped.
Some examples of queries that are very fast:
mysql> SELECT COUNT(*) FROM tbl_name; mysql> SELECT MIN(key_part1),MAX(key_part1) FROM tbl_name; mysql> SELECT MAX(key_part2) FROM tbl_name WHERE key_part_1=constant; mysql> SELECT ... FROM tbl_name ORDER BY key_part1,key_part2,... LIMIT 10; mysql> SELECT ... FROM tbl_name ORDER BY key_part1 DESC,key_part2 DESC,... LIMIT 10;
The following queries are resolved using only the index tree (assuming the indexed columns are numeric):
mysql> SELECT key_part1,key_part2 FROM tbl_name WHERE key_part1=val; mysql> SELECT COUNT(*) FROM tbl_name WHERE key_part1=val1 and key_part2=val2; mysql> SELECT key_part2 FROM tbl_name GROUP BY key_part1;
The following queries use indexing to retrieve the rows in sorted order without a separate sorting pass:
mysql> SELECT ... FROM tbl_name ORDER BY key_part1,key_part2,... mysql> SELECT ... FROM tbl_name ORDER BY key_part1 DESC,key_part2 DESC,...
The cache of open tables can grow to a maximum of
64; this can be changed with with the
-O table_cache=# option to
mysqld). A table is never closed, except when the cache is full and
another thread tries to open a table or if you use
When the table cache fills up, the server uses the following procedure to locate a cache entry to use:
A table is opened for each concurrent access. This means that
if you have two threads accessing the same table or access the table
twice in the same query (with
AS) the table needs to be opened twice.
The first open of any table takes two file descriptors; each additional
use of the table takes only one file descriptor. The extra descriptor
for the first open is used for the index file; this descriptor is shared
among all threads.
If you have many files in a directory, open, close and create operations will
be slow. If you execute
SELECT statements on many different tables,
there will be a little overhead when the table cache is full, because for
every table that has to be opened, another must be closed. You can reduce
this overhead by making the table cache larger.
When you run
mysqladmin status, you'll see something like this:
Uptime: 426 Running threads: 1 Questions: 11082 Reloads: 1 Open tables: 12
This can be somewhat perplexing if you only have 6 tables.
MySQL is multithreaded, so it may have many queries on the same table at once. To minimize the problem with two threads having different states on the same file, the table is opened independently by each concurrent thread. This takes some memory and one extra file descriptor for the data file. The index file descriptor is shared between all threads.
You can move tables and databases from the database directory to other locations and replace them with symbolic links to the new locations. You might want to do this, for example, to move a database to a file system with more free space.
If MySQL notices that a table is a symbolically-linked, it will
resolve the symlink and use the table it points to instead. This works on all
systems that support the
realpath() call (at least Linux and Solaris
realpath())! On systems that don't support
you should not access the table through the real path and through the symlink
at the same time! If you do, the table will be inconsistent after any
MySQL doesn't support linking of databases by default.
Things will work fine as long as you don't make a symbolic link
between databases. Suppose you have a database
db1 under the
MySQL data directory, and then make a symlink
shell> cd /path/to/datadir shell> ln -s db1 db2
Now, for any table
db1, there also appears to be
db2. If one thread updates
and another thread updates
db2.tbl_a, there will be problems.
If you really need this, you must change the following code in `mysys/mf_format.c':
if (!lstat(to,&stat_buff)) /* Check if it's a symbolic link */ if (S_ISLNK(stat_buff.st_mode) && realpath(to,buff))
Change the code to this:
All locking in MySQL is deadlock-free. This is managed by always requesting all needed locks at once at the beginning of a query and always locking the tables in the same order.
The locking method MySQL uses for
WRITE locks works as follows:
The locking method MySQL uses for
READ locks works as follows:
When a lock is released, the lock is made available to the threads in the write lock queue, then to the threads in the read lock queue.
This means that if you have many updates on a table,
statements will wait until there are no more updates.
To work around this for the case where you want to do many
SELECT operations on a table, you can insert rows in a temporary
table and update the real table with the records from the temporary table
once in a while.
This can be done with the following code:
mysql> LOCK TABLES real_table WRITE, insert_table WRITE; mysql> insert into real_table select * from insert_table; mysql> delete from insert_table; mysql> UNLOCK TABLES;
You can use the
HIGH_PRIORITY options with
INSERT if you want to prioritize retrieval in some specific cases.
See section 7.13
You could also change the locking code in `mysys/thr_lock.c' to use a single queue. In this case, write locks and read locks would have the same priority, which might help some applications.
You can get better performance on a table and minimize storage space using the techniques listed below:
NOT NULLif possible. It makes everything faster and you save one bit per column.
TIMESTAMPcolumn or into an
AUTO_INCREMENTcolumn in an
INSERTstatement. See section 18.4.49 How can I get the unique ID for the last inserted row?.
MEDIUMINTis often better than
BLOBcolumns), a fixed-size record format is used. This is much faster but unfortunately may waste some space. See section 10.14 What are the different row formats? Or, when should
isamchk --analyzeon a table after it has been loaded with relevant data. This updates a value for each index that indicates the average number of rows that have the same value. (For unique indexes, this is always 1, of course.)
isamchk --sort-index --sort-records=1(if you want to sort on index 1). If you have a unique index from which you want to read all records in order according to that index, this is a good way to make that faster.
INSERTstatements, use multiple value lists if possible. This is much faster than using separate
LOAD DATA INFILE. This is usually 20 times faster than using a lot of
INSERTstatements. See section 7.15
LOAD DATA INFILEsyntax. You can even get more speed when loading data into a table with many indexes using the following procedure:
mysqlor Perl with
isamchk --keys-used=0 /path/to/db/tbl_name. This will remove all usage of all indexes from the table.
LOAD DATA INFILE.
pack_isamand want to compress the table, run
isamchk -r -q /path/to/db/tbl_name.
LOAD DATA INFILEand
INSERT, enlarge the key buffer. This can be done with the
-O key_buffer=#option to
safe_mysqld. For example, 16M should be a good value if you have much RAM. :)
SELECT ... INTO OUTFILE. See section 7.15
LOAD DATA INFILEsyntax.
LOAD DATA INFILEand
SELECT ...INTO OUTFILEare atomic, so you don't have to use
LOCK TABLESwhen using them. See section 7.23
LOCK TABLES/UNLOCK TABLESsyntax.
To check how fragmented your tables are, run
isamchk -evi on the
See section 13 Using
isamchk for table maintenance and crash recovery.
The time to insert a record consists of:
Where (number) is proportional time. This does not take into consideration the initial overhead to open tables (which is done once for each concurrently-running query).
The size of the table slows down the insertion of indexes by N log N (B-trees).
You can speed up insertions by locking your table and/or using multiple value
INSERT statements. Using multiple value lists can be up to
5 times faster than using separate inserts.
mysql> LOCK TABLES a WRITE; mysql> INSERT INTO a VALUES (1,23),(2,34),(4,33); mysql> INSERT INTO a VALUES (8,26),(6,29); mysql> UNLOCK TABLES;
The main speed difference is that the index buffer is flushed to disk only
once, after all
INSERT statements have completed. Normally there would
be as many index buffer flushes as there are different
statements. Locking is not needed if you can insert all rows with a single
Locking will also lower the total time of multi-connection tests, but the maximum wait time for some threads will go up (because they wait for locks). For example:
thread 1 does 1000 inserts thread 2, 3, and 4 does 1 insert thread 5 does 1000 inserts
If you don't use locking, 2, 3 and 4 will finish before 1 and 5. If you use locking, 2, 3 and 4 probably will not finish before 1 or 5, but the total time should be about 40% faster.
DELETE operations are very fast in
MySQL, you will obtain better overall performance by adding locks
around everything that does more than about 5 inserts or updates in a row.
If you do very many inserts in a row, you could do a
TABLES followed by a
UNLOCK TABLES once in a while (about each
1000 rows) to allow other threads access to the table. This would still
result in a nice performance gain.
LOAD DATA INFILE is much faster still.
The time to delete a record is exactly proportional to the number of indexes. To delete records more quickly, you can increase the size of the index cache. The default index cache is 1M; to get faster deletes, it should be increased by several factors (try 16M if you have enough memory).
Start by benchmarking your problem! You can take any program from the MySQL benchmark suite (normally found in the `sql-bench' directory) and modify it for your needs. By doing this, you can try different solutions to your problem and test which is really the fastest solution for you.
mysqldwith the correct options. More memory gives more speed if you have it. See section 10.1 Changing the size of MySQL buffers.
SELECTstatements faster. See section 10.4 How MySQL uses indexes.
NOT NULLif possible. See section 10.10 How to arrange a table to be as fast/small as possible.
--skip-lockingoption disables file locking between SQL requests. This gives greater speed but has the following consequences:
mysqladmin flush-tablesbefore you try to check or repair tables with
isamchk -d tbl_nameis always allowed, since that simply displays table information.)
--skip-lockingoption is on by default when compiling with MIT-pthreads, because
flock()isn't fully supported by MIT-pthreads on all platforms.
GRANTchecking on the table or column level will decrease performance.
MySQL dosen't have true SQL
Instead, MySQL has three different ways to store records and uses
these to emulate
If a table doesn't have any
columns, a fixed row size is used. Otherwise a dynamic row size is
VARCHAR columns are treated identically from
the application's point of view; both have trailing spaces removed
when the columns are retrieved.
You can check the format used in a table with
isamchk -d (
means "describe the table").
MySQL has three different table formats: fixed-length, dynamic and compressed. These are compared below.
DECIMALcolumns are space-padded to the column width.
isamchk) unless a huge number of records are deleted and you want to return free disk space to the operating system.
") for string columns, or zero for numeric columns (this isn't the same as columns containing
NULLvalues). If a string column has a length of zero after removal of trailing spaces, or a numeric column has a value of zero, it is marked in the bit map and not saved to disk. Non-empty strings are saved as a length byte plus the string contents.
isamchk -rfrom time to time to get better performance. Use
isamchk -ei tbl_namefor some statistics.
3 + (number of columns + 7) / 8 + (number of char columns) + packed size of numeric columns + length of strings + (number of NULL columns + 7) / 8There is a penalty of 6 bytes for each link. A dynamic record is linked whenever an update causes an enlargement of the record. Each new link will be at least 20 bytes, so the next enlargement will probably go in the same link. If not, there will be another link. You may check how many links there are with
isamchk -ed. All links may be removed with
pack_isamutility. All customers with extended MySQL email support are entitled to a copy of
pack_isamfor their internal usage.
pack_isamcan read tables that were compressed with
pack_isam(as long as the table was compressed on the same platform).
0are stored using 1 bit.
BIGINTcolumn (8 bytes) may be stored as a
TINYINTcolumn (1 byte) if all values are in the range
MySQL can support different index types, but the normal type is
NISAM. This is a B-tree index and you can roughly calculate the size for the
index file as
(key_length+4)*0.67, summed over all keys. (This is for
the worst case when all keys are inserted in sorted order.)
String indexes are space compressed. If the first index part is a string, it
will also be prefix compressed. Space compression makes the index file
smaller if the string column has a lot of trailing space or is a
column that is not always used to the full length. Prefix compression helps
if there are many strings with an identical prefix.
This document was generated on 3 January 1999 using the texi2html translator version 1.52 (extended by email@example.com).