We start with system-level factors, because some of these decisions must be made very early to achieve large performance gains. In other cases, a quick look at this section may suffice. However, it is always nice to have a sense of how much can be gained by changing factors that apply at this level.
The operating system to use is very important. To get the best use of multiple-CPU machines, you should use Solaris (because its threads implementation works well) or Linux (because the 2.4 and later kernels have good SMP support). Note that older Linux kernels have a 2GB filesize limit by default. If you have such a kernel and a need for files larger than 2GB, you should get the Large File Support (LFS) patch for the ext2 filesystem. Other filesystems such as ReiserFS and XFS do not have this 2GB limitation.
Before using MySQL in production, we advise you to test it on your intended platform.
Other tips:
If you have enough RAM, you could remove all swap devices. Some operating systems use a swap device in some contexts even if you have free memory.
Avoid external locking. Since MySQL 4.0, the default has
been for external locking to be disabled on all systems. The
--external-locking and
--skip-external-locking options explicitly
enable and disable external locking.
Note that disabling external locking does not affect MySQL's functionality as long as you run only one server. Just remember to take down the server (or lock and flush the relevant tables) before you run myisamchk. On some systems it is mandatory to disable external locking because it does not work, anyway.
The only case in which you cannot disable external locking is when you run multiple MySQL servers (not clients) on the same data, or if you run myisamchk to check (not repair) a table without telling the server to flush and lock the tables first. Note that using multiple MySQL servers to access the same data concurrently is generally not recommended, except when using MySQL Cluster.
The LOCK TABLES and UNLOCK
TABLES statements use internal locking, so you can
use them even if external locking is disabled.
You can determine the default buffer sizes used by the mysqld server using this command:
shell> mysqld --verbose --help
This command produces a list of all mysqld options and configurable system variables. The output includes the default variable values and looks something like this:
back_log 50 binlog_cache_size 32768 bulk_insert_buffer_size 8388608 connect_timeout 5 date_format (No default value) datetime_format (No default value) default_week_format 0 delayed_insert_limit 100 delayed_insert_timeout 300 delayed_queue_size 1000 expire_logs_days 0 flush_time 1800 ft_max_word_len 84 ft_min_word_len 4 ft_query_expansion_limit 20 ft_stopword_file (No default value) group_concat_max_len 1024 innodb_additional_mem_pool_size 1048576 innodb_autoextend_increment 8 innodb_buffer_pool_awe_mem_mb 0 innodb_buffer_pool_size 8388608 innodb_concurrency_tickets 500 innodb_file_io_threads 4 innodb_force_recovery 0 innodb_lock_wait_timeout 50 innodb_log_buffer_size 1048576 innodb_log_file_size 5242880 innodb_log_files_in_group 2 innodb_mirrored_log_groups 1 innodb_open_files 300 innodb_sync_spin_loops 20 innodb_thread_concurrency 8 innodb_thread_sleep_delay 10000 interactive_timeout 28800 join_buffer_size 131072 key_buffer_size 8388600 key_cache_age_threshold 300 key_cache_block_size 1024 key_cache_division_limit 100 long_query_time 10 lower_case_table_names 1 max_allowed_packet 1048576 max_binlog_cache_size 4294967295 max_binlog_size 1073741824 max_connect_errors 10 max_connections 100 max_delayed_threads 20 max_error_count 64 max_heap_table_size 16777216 max_join_size 4294967295 max_length_for_sort_data 1024 max_relay_log_size 0 max_seeks_for_key 4294967295 max_sort_length 1024 max_tmp_tables 32 max_user_connections 0 max_write_lock_count 4294967295 multi_range_count 256 myisam_block_size 1024 myisam_data_pointer_size 6 myisam_max_extra_sort_file_size 2147483648 myisam_max_sort_file_size 2147483647 myisam_repair_threads 1 myisam_sort_buffer_size 8388608 net_buffer_length 16384 net_read_timeout 30 net_retry_count 10 net_write_timeout 60 open_files_limit 0 optimizer_prune_level 1 optimizer_search_depth 62 preload_buffer_size 32768 query_alloc_block_size 8192 query_cache_limit 1048576 query_cache_min_res_unit 4096 query_cache_size 0 query_cache_type 1 query_cache_wlock_invalidate FALSE query_prealloc_size 8192 range_alloc_block_size 2048 read_buffer_size 131072 read_only FALSE read_rnd_buffer_size 262144 div_precision_increment 4 record_buffer 131072 relay_log_purge TRUE relay_log_space_limit 0 slave_compressed_protocol FALSE slave_net_timeout 3600 slave_transaction_retries 10 slow_launch_time 2 sort_buffer_size 2097144 sync-binlog 0 sync-frm TRUE sync-replication 0 sync-replication-slave-id 0 sync-replication-timeout 10 table_cache 64 thread_cache_size 0 thread_concurrency 10 thread_stack 196608 time_format (No default value) tmp_table_size 33554432 transaction_alloc_block_size 8192 transaction_prealloc_size 4096 updatable_views_with_limit 1 wait_timeout 28800
For a mysqld server that is currently running, you can see the current values of its system variables by connecting to it and issuing this statement:
mysql> SHOW VARIABLES;
You can also see some statistical and status indicators for a running server by issuing this statement:
mysql> SHOW STATUS;
System variable and status information also can be obtained using mysqladmin:
shell>mysqladmin variablesshell>mysqladmin extended-status
For a full description of all system and status variables, see Section 5.2.2, “Server System Variables”, and Section 5.2.4, “Server Status Variables”.
MySQL uses algorithms that are very scalable, so you can usually run with very little memory. However, normally you get better performance by giving MySQL more memory.
When tuning a MySQL server, the two most important variables to
configure are key_buffer_size and
table_cache. You should first feel confident
that you have these set appropriately before trying to change
any other variables.
The following examples indicate some typical variable values for different runtime configurations.
If you have at least 256MB of memory and many tables and want maximum performance with a moderate number of clients, you should use something like this:
shell>mysqld_safe --key_buffer_size=64M --table_cache=256 \--sort_buffer_size=4M --read_buffer_size=1M &
If you have only 128MB of memory and only a few tables, but you still do a lot of sorting, you can use something like this:
shell> mysqld_safe --key_buffer_size=16M --sort_buffer_size=1M
If there are very many simultaneous connections, swapping problems may occur unless mysqld has been configured to use very little memory for each connection. mysqld performs better if you have enough memory for all connections.
With little memory and lots of connections, use something like this:
shell>mysqld_safe --key_buffer_size=512K --sort_buffer_size=100K \--read_buffer_size=100K &
Or even this:
shell>mysqld_safe --key_buffer_size=512K --sort_buffer_size=16K \--table_cache=32 --read_buffer_size=8K \--net_buffer_length=1K &
If you are performing GROUP BY or
ORDER BY operations on tables that are much
larger than your available memory, you should increase the value
of read_rnd_buffer_size to speed up the
reading of rows following sorting operations.
You can make use of the example option files included with your MySQL distribution; see Section 4.3.2.1, “Preconfigured Option Files”.
If you specify an option on the command line for mysqld or mysqld_safe, it remains in effect only for that invocation of the server. To use the option every time the server runs, put it in an option file.
To see the effects of a parameter change, do something like this:
shell> mysqld --key_buffer_size=32M --verbose --help
The variable values are listed near the end of the output. Make
sure that the --verbose and
--help options are last. Otherwise, the effect
of any options listed after them on the command line are not
reflected in the output.
For information on tuning the InnoDB storage
engine, see Section 14.2.11, “InnoDB Performance Tuning Tips”.
The task of the query optimizer is to find an optimal plan for executing an SQL query. Because the difference in performance between “good” and “bad” plans can be orders of magnitude (that is, seconds versus hours or even days), most query optimizers, including that of MySQL, perform a more or less exhaustive search for an optimal plan among all possible query evaluation plans. For join queries, the number of possible plans investigated by the MySQL optimizer grows exponentially with the number of tables referenced in a query. For small numbers of tables (typically less than 7–10) this is not a problem. However, when larger queries are submitted, the time spent in query optimization may easily become the major bottleneck in the server's performance.
MySQL 5.0.1 introduces a more flexible method for query optimization that allows the user to control how exhaustive the optimizer is in its search for an optimal query evaluation plan. The general idea is that the fewer plans that are investigated by the optimizer, the less time it spends in compiling a query. On the other hand, because the optimizer skips some plans, it may miss finding an optimal plan.
The behavior of the optimizer with respect to the number of plans it evaluates can be controlled via two system variables:
The optimizer_prune_level variable tells
the optimizer to skip certain plans based on estimates of
the number of rows accessed for each table. Our experience
shows that this kind of “educated guess” rarely
misses optimal plans, and may dramatically reduce query
compilation times. That is why this option is on
(optimizer_prune_level=1) by default.
However, if you believe that the optimizer missed a better
query plan, this option can be switched off
(optimizer_prune_level=0) with the risk
that query compilation may take much longer. Note that, even
with the use of this heuristic, the optimizer still explores
a roughly exponential number of plans.
The optimizer_search_depth variable tells
how far into the “future” of each incomplete
plan the optimizer should look to evaluate whether it should
be expanded further. Smaller values of
optimizer_search_depth may result in
orders of magnitude smaller query compilation times. For
example, queries with 12, 13, or more tables may easily
require hours and even days to compile if
optimizer_search_depth is close to the
number of tables in the query. At the same time, if compiled
with optimizer_search_depth equal to 3 or
4, the optimizer may compile in less than a minute for the
same query. If you are unsure of what a reasonable value is
for optimizer_search_depth, this variable
can be set to 0 to tell the optimizer to determine the value
automatically.
Most of the following tests were performed on Linux with the MySQL benchmarks, but they should give some indication for other operating systems and workloads.
You obtain the fastest executables when you link with
-static.
On Linux, it is best to compile the server with
pgcc and -O3. You need about
200MB memory to compile sql_yacc.cc with
these options, because gcc or
pgcc needs a great deal of memory to make all
functions inline. You should also set CXX=gcc
when configuring MySQL to avoid inclusion of the
libstdc++ library, which is not needed. Note
that with some versions of pgcc, the
resulting binary runs only on true Pentium processors, even if
you use the compiler option indicating that you want the
resulting code to work on all x586-type processors (such as
AMD).
By using a better compiler and compilation options, you can obtain a 10–30% speed increase in applications. This is particularly important if you compile the MySQL server yourself.
When we tested both the Cygnus CodeFusion and Fujitsu compilers, neither was sufficiently bug-free to allow MySQL to be compiled with optimizations enabled.
The standard MySQL binary distributions are compiled with
support for all character sets. When you compile MySQL yourself,
you should include support only for the character sets that you
are going to use. This is controlled by the
--with-charset option to
configure.
Here is a list of some measurements that we have made:
If you use pgcc and compile everything
with -O6, the mysqld
server is 1% faster than with gcc 2.95.2.
If you link dynamically (without -static),
the result is 13% slower on Linux. Note that you still can
use a dynamically linked MySQL library for your client
applications. It is the server that is most critical for
performance.
For a connection from a client to a server running on the
same host, if you connect using TCP/IP rather than a Unix
socket file, performance is 7.5% slower. (On Unix, if you
connect to the hostname localhost, MySQL
uses a socket file by default.)
For TCP/IP connections from a client to a server, connecting to a remote server on another host is 8–11% slower than connecting to a server on the same host, even for connections over 100Mb/s Ethernet.
When running our benchmark tests using secure connections (all data encrypted with internal SSL support) performance was 55% slower than with unencrypted connections.
If you compile with --with-debug=full, most
queries are 20% slower. Some queries may take substantially
longer; for example, the MySQL benchmarks run 35% slower. If
you use --with-debug (without
=full), the speed decrease is only 15%.
For a version of mysqld that has been
compiled with --with-debug=full, you can
disable memory checking at runtime by starting it with the
--skip-safemalloc option. The execution
speed should then be close to that obtained when configuring
with --with-debug.
On a Sun UltraSPARC-IIe, a server compiled with Forte 5.0 is 4% faster than one compiled with gcc 3.2.
On a Sun UltraSPARC-IIe, a server compiled with Forte 5.0 is 4% faster in 32-bit mode than in 64-bit mode.
Compiling with gcc 2.95.2 for UltraSPARC
with the -mcpu=v8 -Wa,-xarch=v8plusa
options gives 4% more performance.
On Solaris 2.5.1, MIT-pthreads is 8–12% slower than Solaris native threads on a single processor. With greater loads or more CPUs, the difference should be larger.
Compiling on Linux-x86 using gcc without
frame pointers (-fomit-frame-pointer or
-fomit-frame-pointer -ffixed-ebp) makes
mysqld 1–4% faster.
Binary MySQL distributions for Linux that are provided by MySQL AB used to be compiled with pgcc. We had to go back to regular gcc due to a bug in pgcc that would generate binaries that do not run on AMD. We will continue using gcc until that bug is resolved. In the meantime, if you have a non-AMD machine, you can build a faster binary by compiling with pgcc. The standard MySQL Linux binary is linked statically to make it faster and more portable.
The following list indicates some of the ways that the mysqld server uses memory. Where applicable, the name of the system variable relevant to the memory use is given:
The key buffer (variable key_buffer_size)
is shared by all threads; other buffers used by the server
are allocated as needed. See
Section 7.5.2, “Tuning Server Parameters”.
Each connection uses some thread-specific space:
A stack (default 192KB, variable
thread_stack)
A connection buffer (variable
net_buffer_length)
A result buffer (variable
net_buffer_length)
The connection buffer and result buffer are dynamically
enlarged up to max_allowed_packet when
needed. While a query is running, a copy of the current
query string is also allocated.
All threads share the same base memory.
When a thread is no longer needed, the memory allocated to it is released and returned to the system unless the thread goes back into the thread cache. In that case, the memory remains allocated.
Only compressed MyISAM tables are memory
mapped. This is because the 32-bit memory space of 4GB is
not large enough for most big tables. When systems with a
64-bit address space become more common, we may add general
support for memory mapping.
Each request that performs a sequential scan of a table
allocates a read buffer (variable
read_buffer_size).
When reading rows in an arbitrary sequence (for example,
following a sort), a random-read
buffer (variable
read_rnd_buffer_size) may be allocated in
order to avoid disk seeks.
All joins are executed in a single pass, and most joins can
be done without even using a temporary table. Most temporary
tables are memory-based hash tables. Temporary tables with a
large row length (calculated as the sum of all column
lengths) or that contain BLOB columns are
stored on disk.
If an internal heap table exceeds the size of
tmp_table_size, MySQL handles this
automatically by changing the in-memory heap table to a
disk-based MyISAM table as necessary. You
can also increase the temporary table size by setting the
tmp_table_size option to
mysqld, or by setting the SQL option
SQL_BIG_TABLES in the client program. See
Section 13.5.3, “SET Syntax”.
Most requests that perform a sort allocate a sort buffer and zero to two temporary files depending on the result set size. See Section A.4.4, “Where MySQL Stores Temporary Files”.
Almost all parsing and calculating is done in a local memory
store. No memory overhead is needed for small items, so the
normal slow memory allocation and freeing is avoided. Memory
is allocated only for unexpectedly large strings. This is
done with malloc() and
free().
For each MyISAM table that is opened, the
index file is opened once; the data file is opened once for
each concurrently running thread. For each concurrent
thread, a table structure, column structures for each
column, and a buffer of size 3 ×
are allocated (where
NN is the maximum row length, not
counting BLOB columns). A
BLOB column requires five to eight bytes
plus the length of the BLOB data. The
MyISAM storage engine maintains one extra
row buffer for internal use.
For each table having BLOB columns, a
buffer is enlarged dynamically to read in larger
BLOB values. If you scan a table, a
buffer as large as the largest BLOB value
is allocated.
Handler structures for all in-use tables are saved in a cache and managed as a FIFO. By default, the cache has 64 entries. If a table has been used by two running threads at the same time, the cache contains two entries for the table. See Section 7.4.8, “How MySQL Opens and Closes Tables”.
A FLUSH TABLES statement or
mysqladmin flush-tables command closes
all tables that are not in use at once and marks all in-use
tables to be closed when the currently executing thread
finishes. This effectively frees most in-use memory.
FLUSH TABLES does not return until all
tables have been closed.
ps and other system status programs may
report that mysqld uses a lot of memory. This
may be caused by thread stacks on different memory addresses.
For example, the Solaris version of ps counts
the unused memory between stacks as used memory. You can verify
this by checking available swap with swap -s.
We test mysqld with several memory-leakage
detectors (both commercial and Open Source), so there should be
no memory leaks.
When a new client connects to mysqld, mysqld spawns a new thread to handle the request. This thread first checks whether the hostname is in the hostname cache. If not, the thread attempts to resolve the hostname:
If the operating system supports the thread-safe
gethostbyaddr_r() and
gethostbyname_r() calls, the thread uses
them to perform hostname resolution.
If the operating system does not support the thread-safe
calls, the thread locks a mutex and calls
gethostbyaddr() and
gethostbyname() instead. In this case, no
other thread can resolve hostnames that are not in the
hostname cache until the first thread unlocks the mutex.
You can disable DNS hostname lookups by starting
mysqld with the
--skip-name-resolve option. However, in this
case, you can use only IP numbers in the MySQL grant tables.
If you have a very slow DNS and many hosts, you can get more
performance by either disabling DNS lookups with
--skip-name-resolve or by increasing the
HOST_CACHE_SIZE define (default value: 128)
and recompiling mysqld.
You can disable the hostname cache by starting the server with
the --skip-host-cache option. To clear the
hostname cache, issue a FLUSH HOSTS statement
or execute the mysqladmin flush-hosts
command.
To disallow TCP/IP connections entirely, start
mysqld with the
--skip-networking option.