You can get the default buffer sizes used by the mysqld
server
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
like this:
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, 16M
indicates 16 megabytes. Case of suffix letters does not matter;
16M
and 16m
are equivalent.
back_log
back_log
value 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_log
higher than this maximum will be
ineffective.
connect_timeout
mysqld
server is waiting for a connect
packet before responding with Bad handshake
.
join_buffer
key_buffer
key_buffer
is
the size of the buffer used for index blocks. You might want to increase this
value when doing many DELETE
or INSERT
operations on a table
with lots of indexes. To get even more speed, use LOCK TABLES
.
See section 7.23 LOCK TABLES/UNLOCK TABLES
syntax.
max_allowed_packet
net_buffer_length
bytes, but can grow up to max_allowed_packet
bytes when needed. This value by default is small to catch big (possibly
wrong) packets. You must increase this value if you are using big
BLOB
columns. It should be as big as the biggest BLOB
you want
to use.
max_connections
mysqld
requires. See below for
comments on file descriptor limits.
max_connect_errors
FLUSH HOSTS
.
max_join_size
max_join_size
records return an error. Set this value if your users tend to perform joins
without a WHERE
clause that take a long time and return
millions of rows.
max_sort_length
BLOB
or TEXT
values (only the first max_sort_length
bytes of each value
are used; the rest are ignored).
net_buffer_length
max_allowed_packet
bytes.)
record_buffer
sort_buffer
ORDER BY
or GROUP BY
operations.
See section 16.4 Where MySQL stores temporary files.
table_cache
mysqld
requires. 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.
tmp_table_size
The table tbl_name is full
. Increase the value of
tmp_table_size
if you do many advanced GROUP BY
queries.
thread_stack
crash-me
test are dependent on this value. The default is normally
large enough.
See section 11 The MySQL benchmark suite.
wait_timeout
table_cache
and 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
to system.
table_cache
is related to max_connections
.
For example, for 200 open connections, you should have a table cache of
at least 200 * n
, where n
is the maximum number of tables in
a join.
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 &
or even:
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
connection. 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
output.
The list below indicates some of the ways that the mysqld
server
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_packet
when needed. When a
query is running a copy of the current query string is also alloced.
record_buffer
).
BLOB
columns 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
tmp_table_size
option to mysqld
, or by setting the SQL option
SQL_BIG_TABLES
in the client program. See section 7.24 SET OPTION
syntax. 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 mysqld
with the --big-tables
option to always store temporary tables on disk,
however, this will affect the speed of all complicated queries.
malloc()
and
free()
).
3 * n
is
allocated (where n
is the maximum row length, not counting BLOB
columns). A BLOB
uses 5 to 8 bytes plus the length of the BLOB
data.
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.
mysqladmin flush-tables
command 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 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 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
performance.
On Linux, you will get the fastest code when compiling with pgcc
and
-O6
. To compile `sql_yacc.cc' with these options, you need 180M
memory because
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 libstdc++
library.
pgcc
and compile everything with -O6
, the
mysqld
server is 11% faster than with gcc
.
-static
), the result is 13% slower.
gcc
2.7.3 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 (PRIMARY
, UNIQUE
and 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:
WHERE
clause.
MAX()
or 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 DESC
.
Suppose you issue the following SELECT
statement:
mysql> SELECT * FROM tbl_name WHERE col1=val1 AND col2=val2;
If a multiple-column index exists on col1
and col2
, the
appropriate rows can be fetched directly. If separate single-column
indexes exist on col1
and 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
capabilities on (col1)
, (col1,col2)
and
(col1,col2,col3)
.
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
columns, but (col2)
and (col2,col3)
are not leftmost prefixes
of (col1,col2,col3)
.
MySQL also uses indexes for LIKE
comparisons if the argument
to 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.
The following 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.
MySQL normally uses the index that finds least number of rows. An
index is used for columns that you compare with the following operators:
=
, >
, >=
, <
, <=
, BETWEEN
and a
LIKE
with a non-wildcard prefix like 'something%'
.
Any index that doesn't span all AND
levels in the WHERE
clause
is not used to optimize the query.
The following WHERE
clauses 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 WHERE
clauses 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 */
WHERE
clauses(This section is incomplete; MySQL does many optimizations.)
In general,
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
the EXPLAIN
command to determine which indexes are used for a
SELECT
.
See section 7.21 EXPLAIN
syntax (Get information about a SELECT
).
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 WHERE
is retrieved
directly from the table information. This is also done for any NOT NULL
expression when used with only one table.
SELECT
statements are impossible and returns no rows.
HAVING
is merged with WHERE
if you don't use GROUP
BY
or group functions (COUNT()
, MIN()
...)
WHERE
is constructed to get a fast
WHERE
evaluation for each sub join and also to skip records as
soon as possible.
WHERE
clause on a UNIQUE
index 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 BY
and in GROUP BY
come from the same table, then this table is preferred first when joining.
ORDER BY
clause and a different GROUP BY
clause,
or if the ORDER BY
or GROUP BY
contains columns from tables other than the first table in the join
queue, a temporary table is created.
HAVING
clause
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 table_cache
(default
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 mysqladmin
refresh
or mysqladmin flush-tables
.
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
support realpath()
)! On systems that don't support realpath()
,
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
update.
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 db2
that
points to db1
:
shell> cd /path/to/datadir shell> ln -s db1 db2
Now, for any table tbl_a
in db1
, there also appears to be
a table tbl_a
in db2
. If one thread updates db1.tbl_a
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:
if (realpath(to,buff))
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, SELECT
statements will wait until there are no more updates.
To work around this for the case where you want to do many INSERT
and
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 LOW_PRIORITY
or HIGH_PRIORITY
options with
INSERT
if you want to prioritize retrieval in some specific cases.
See section 7.13 INSERT
syntax
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 NULL
if possible. It makes everything faster
and you save one bit per column.
TIMESTAMP
column or
into an AUTO_INCREMENT
column in an INSERT
statement.
See section 18.4.49 How can I get the unique ID for the last inserted row?.
MEDIUMINT
is often better than INT
.
VARCHAR
, TEXT
or
BLOB
columns), 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 VARCHAR/CHAR
be used?.
isamchk --analyze
on 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.
INSERT
statements, use multiple value lists if possible. This
is much faster than using separate INSERT
statements.
LOAD DATA INFILE
. This is usually
20 times faster than using a lot of INSERT
statements.
See section 7.15 LOAD DATA INFILE
syntax.
You can even get more speed when loading data into a table with many indexes
using the following procedure:
mysql
or Perl with CREATE TABLE
.
mysqladmin flush-tables
.
isamchk --keys-used=0 /path/to/db/tbl_name
. This will remove all
usage of all indexes from the table.
LOAD DATA INFILE
.
pack_isam
and want to compress the table, run
pack_isam
on it.
isamchk -r -q /path/to/db/tbl_name
.
mysqladmin flush-tables
.
LOAD DATA INFILE
and
INSERT
, enlarge the key buffer. This can be done with the
-O key_buffer=#
option to mysqld
or safe_mysqld
. For
example, 16M should be a good value if you have much RAM. :)
SELECT ... INTO OUTFILE
. See section 7.15 LOAD DATA INFILE
syntax.
LOCK TABLES
. LOAD DATA INFILE
and
SELECT ...INTO OUTFILE
are atomic, so you don't have to use LOCK
TABLES
when using them.
See section 7.23 LOCK TABLES/UNLOCK TABLES
syntax.
To check how fragmented your tables are, run isamchk -evi
on the
`.ISM' file.
See section 13 Using isamchk
for table maintenance and crash recovery.
INSERT
statementsThe 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
lists with 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 INSERT
statements. Locking is not needed if you can insert all rows with a single
statement.
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.
As INSERT
, UPDATE
and 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 LOCK
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.
Of course, LOAD DATA INFILE
is much faster still.
If you are insert a lot of rows from different clients, you can get higher
speed by using the INSERT DELAYED
statement. See section 7.13 INSERT
syntax
DELETE
statementsThe 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.
mysqld
with the correct options. More memory gives more speed
if you have it. See section 10.1 Changing the size of MySQL buffers.
SELECT
statements faster.
See section 10.4 How MySQL uses indexes.
NOT NULL
if possible.
See section 10.10 How to arrange a table to be as fast/small as possible.
--skip-locking
option disables file locking between SQL requests.
This gives greater speed but has the following consequences:
mysqladmin flush-tables
before
you try to check or repair tables with isamchk
. (isamchk -d
tbl_name
is always allowed, since that simply displays table information.)
--skip-locking
option is on by default when compiling with
MIT-pthreads, because flock()
isn't fully supported by MIT-pthreads on
all platforms.
GRANT
checking on the table or column level will decrease performance.
VARCHAR/CHAR
be used?
MySQL dosen't have true SQL VARCHAR
types.
Instead, MySQL has three different ways to store records and uses
these to emulate VARCHAR
.
If a table doesn't have any VARCHAR
, BLOB
or TEXT
columns, a fixed row size is used. Otherwise a dynamic row size is
used. CHAR
and 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
(-d
means "describe the table").
MySQL has three different table formats: fixed-length, dynamic and compressed. These are compared below.
Fixed-length tables
VARCHAR
,
BLOB
or TEXT
columns.
CHAR
, NUMERIC
and DECIMAL
columns 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.
Dynamic tables
VARCHAR
, BLOB
or TEXT
columns.
"
) for string columns, or zero for numeric columns (this isn't the
same as columns containing NULL
values). 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 -r
from
time to time to get better performance.
Use isamchk -ei tbl_name
for 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 isamchk -r
.
Compressed tables
pack_isam
utility. All customers
with extended MySQL email support are entitled to a copy of
pack_isam
for their internal usage.
pack_isam
can read tables that were compressed
with pack_isam
(as long as the table was compressed on the same
platform).
0
are stored using 1 bit.
BIGINT
column (8 bytes) may
be stored as a TINYINT
column (1 byte) if all values are in the range
0
to 255
.
ENUM
.
BLOB
or TEXT
columns.
isamchk
.
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 VARCHAR
column that is not always used to the full length. Prefix compression helps
if there are many strings with an identical prefix.
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