EXPLAIN returns a row of
information for each table used in the
SELECT statement. The tables are
listed in the output in the order that MySQL would read them
while processing the query. MySQL resolves all joins using a
nested-loop join method. This means that MySQL reads a row from
the first table, and then finds a matching row in the second
table, the third table, and so on. When all tables are
processed, MySQL outputs the selected columns and backtracks
through the table list until a table is found for which there
are more matching rows. The next row is read from this table and
the process continues with the next table.
When the EXTENDED keyword is used,
EXPLAIN produces extra
information that can be viewed by issuing a
SHOW WARNINGS statement following
the EXPLAIN statement. This
information displays how the optimizer qualifies table and
column names in the SELECT
statement, what the SELECT looks
like after the application of rewriting and optimization rules,
and possibly other notes about the optimization process.
EXPLAIN
EXTENDED also displays the filtered
column.
You cannot use the EXTENDED and
PARTITIONS keywords together in the same
EXPLAIN statement.
Each output row from EXPLAIN
provides information about one table, and each row contains the
following columns:
idThe
SELECTidentifier. This is the sequential number of theSELECTwithin the query.select_typeThe type of
SELECT, which can be any of those shown in the following table.select_typeValueMeaning SIMPLESimple SELECT(not usingUNIONor subqueries)PRIMARYOutermost SELECTUNIONSecond or later SELECTstatement in aUNIONDEPENDENT UNIONSecond or later SELECTstatement in aUNION, dependent on outer queryUNION RESULTResult of a UNION.SUBQUERYFirst SELECTin subqueryDEPENDENT SUBQUERYFirst SELECTin subquery, dependent on outer queryDERIVEDDerived table SELECT(subquery inFROMclause)UNCACHEABLE SUBQUERYA subquery for which the result cannot be cached and must be re-evaluated for each row of the outer query UNCACHEABLE UNIONThe second or later select in a UNIONthat belongs to an uncacheable subquery (seeUNCACHEABLE SUBQUERY)DEPENDENTtypically signifies the use of a correlated subquery. See Section 12.2.10.7, “Correlated Subqueries”.DEPENDENT SUBQUERYevaluation differs fromUNCACHEABLE SUBQUERYevaluation. ForDEPENDENT SUBQUERY, the subquery is re-evaluated only once for each set of different values of the variables from its outer context. ForUNCACHEABLE SUBQUERY, the subquery is re-evaluated for each row of the outer context. Cacheability of subqueries is subject to the restrictions detailed in Section 7.9.3.1, “How the Query Cache Operates”. For example, referring to user variables makes a subquery uncacheable.tableThe table to which the row of output refers.
typeThe join type. The different join types are listed here, ordered from the best type to the worst:
The table has only one row (= system table). This is a special case of the
constjoin type.The table has at most one matching row, which is read at the start of the query. Because there is only one row, values from the column in this row can be regarded as constants by the rest of the optimizer.
consttables are very fast because they are read only once.constis used when you compare all parts of aPRIMARY KEYorUNIQUEindex to constant values. In the following queries,tbl_namecan be used as aconsttable:SELECT * FROM
tbl_nameWHEREprimary_key=1; SELECT * FROMtbl_nameWHEREprimary_key_part1=1 ANDprimary_key_part2=2;One row is read from this table for each combination of rows from the previous tables. Other than the
systemandconsttypes, this is the best possible join type. It is used when all parts of an index are used by the join and the index is aPRIMARY KEYorUNIQUE NOT NULLindex.eq_refcan be used for indexed columns that are compared using the=operator. The comparison value can be a constant or an expression that uses columns from tables that are read before this table. In the following examples, MySQL can use aneq_refjoin to processref_table:SELECT * FROM
ref_table,other_tableWHEREref_table.key_column=other_table.column; SELECT * FROMref_table,other_tableWHEREref_table.key_column_part1=other_table.columnANDref_table.key_column_part2=1;All rows with matching index values are read from this table for each combination of rows from the previous tables.
refis used if the join uses only a leftmost prefix of the key or if the key is not aPRIMARY KEYorUNIQUEindex (in other words, if the join cannot select a single row based on the key value). If the key that is used matches only a few rows, this is a good join type.refcan be used for indexed columns that are compared using the=or<=>operator. In the following examples, MySQL can use arefjoin to processref_table:SELECT * FROM
ref_tableWHEREkey_column=expr; SELECT * FROMref_table,other_tableWHEREref_table.key_column=other_table.column; SELECT * FROMref_table,other_tableWHEREref_table.key_column_part1=other_table.columnANDref_table.key_column_part2=1;The join is performed using a
FULLTEXTindex.This join type is like
ref, but with the addition that MySQL does an extra search for rows that containNULLvalues. This join type optimization is used most often in resolving subqueries. In the following examples, MySQL can use aref_or_nulljoin to processref_table:SELECT * FROM
ref_tableWHEREkey_column=exprORkey_columnIS NULL;This join type indicates that the Index Merge optimization is used. In this case, the
keycolumn in the output row contains a list of indexes used, andkey_lencontains a list of the longest key parts for the indexes used. For more information, see Section 7.13.2, “Index Merge Optimization”.This type replaces
reffor someINsubqueries of the following form:valueIN (SELECTprimary_keyFROMsingle_tableWHEREsome_expr)unique_subqueryis just an index lookup function that replaces the subquery completely for better efficiency.This join type is similar to
unique_subquery. It replacesINsubqueries, but it works for nonunique indexes in subqueries of the following form:valueIN (SELECTkey_columnFROMsingle_tableWHEREsome_expr)Only rows that are in a given range are retrieved, using an index to select the rows. The
keycolumn in the output row indicates which index is used. Thekey_lencontains the longest key part that was used. Therefcolumn isNULLfor this type.rangecan be used when a key column is compared to a constant using any of the=,<>,>,>=,<,<=,IS NULL,<=>,BETWEEN, orIN()operators:SELECT * FROM
tbl_nameWHEREkey_column= 10; SELECT * FROMtbl_nameWHEREkey_columnBETWEEN 10 and 20; SELECT * FROMtbl_nameWHEREkey_columnIN (10,20,30); SELECT * FROMtbl_nameWHEREkey_part1= 10 ANDkey_part2IN (10,20,30);This join type is the same as
ALL, except that only the index tree is scanned. This usually is faster thanALLbecause the index file usually is smaller than the data file.MySQL can use this join type when the query uses only columns that are part of a single index.
A full table scan is done for each combination of rows from the previous tables. This is normally not good if the table is the first table not marked
const, and usually very bad in all other cases. Normally, you can avoidALLby adding indexes that enable row retrieval from the table based on constant values or column values from earlier tables.
possible_keysThe
possible_keyscolumn indicates which indexes MySQL can choose from use to find the rows in this table. Note that this column is totally independent of the order of the tables as displayed in the output fromEXPLAIN. That means that some of the keys inpossible_keysmight not be usable in practice with the generated table order.If this column is
NULL, there are no relevant indexes. In this case, you may be able to improve the performance of your query by examining theWHEREclause to check whether it refers to some column or columns that would be suitable for indexing. If so, create an appropriate index and check the query withEXPLAINagain. See Section 12.1.6, “ALTER TABLESyntax”.To see what indexes a table has, use
SHOW INDEX FROM.tbl_namekeyThe
keycolumn indicates the key (index) that MySQL actually decided to use. If MySQL decides to use one of thepossible_keysindexes to look up rows, that index is listed as the key value.It is possible that
keywill name an index that is not present in thepossible_keysvalue. This can happen if none of thepossible_keysindexes are suitable for looking up rows, but all the columns selected by the query are columns of some other index. That is, the named index covers the selected columns, so although it is not used to determine which rows to retrieve, an index scan is more efficient than a data row scan.For
InnoDB, a secondary index might cover the selected columns even if the query also selects the primary key becauseInnoDBstores the primary key value with each secondary index. IfkeyisNULL, MySQL found no index to use for executing the query more efficiently.To force MySQL to use or ignore an index listed in the
possible_keyscolumn, useFORCE INDEX,USE INDEX, orIGNORE INDEXin your query. See Section 12.2.9.2, “Index Hint Syntax”.For
MyISAMtables, runningANALYZE TABLEhelps the optimizer choose better indexes. ForMyISAMtables, myisamchk --analyze does the same. See Section 12.4.2.1, “ANALYZE TABLESyntax”, and Section 6.6, “MyISAMTable Maintenance and Crash Recovery”.key_lenThe
key_lencolumn indicates the length of the key that MySQL decided to use. The length isNULLif thekeycolumn saysNULL. Note that the value ofkey_lenenables you to determine how many parts of a multiple-part key MySQL actually uses.refThe
refcolumn shows which columns or constants are compared to the index named in thekeycolumn to select rows from the table.rowsThe
rowscolumn indicates the number of rows MySQL believes it must examine to execute the query.For
InnoDBtables, this number is an estimate, and may not always be exact.filteredThe
filteredcolumn indicates an estimated percentage of table rows that will be filtered by the table condition. That is,rowsshows the estimated number of rows examined androws×filtered/100shows the number of rows that will be joined with previous tables. This column is displayed if you useEXPLAIN EXTENDED.ExtraThis column contains additional information about how MySQL resolves the query. The following list explains the values that can appear in this column. If you want to make your queries as fast as possible, look out for
Extravalues ofUsing filesortandUsing temporary.const row not foundFor a query such as
SELECT ... FROM, the table was empty.tbl_nameDistinctMySQL is looking for distinct values, so it stops searching for more rows for the current row combination after it has found the first matching row.
Full scan on NULL keyThis occurs for subquery optimization as a fallback strategy when the optimizer cannot use an index-lookup access method.
Impossible HAVINGThe
HAVINGclause is always false and cannot select any rows.Impossible WHEREThe
WHEREclause is always false and cannot select any rows.Impossible WHERE noticed after reading const tablesMySQL has read all
const(andsystem) tables and notice that theWHEREclause is always false.No matching min/max rowNo row satisfies the condition for a query such as
SELECT MIN(...) FROM ... WHERE.conditionno matching row in const tableFor a query with a join, there was an empty table or a table with no rows satisfying a unique index condition.
No tables usedThe query has no
FROMclause, or has aFROM DUALclause.Not existsMySQL was able to do a
LEFT JOINoptimization on the query and does not examine more rows in this table for the previous row combination after it finds one row that matches theLEFT JOINcriteria. Here is an example of the type of query that can be optimized this way:SELECT * FROM t1 LEFT JOIN t2 ON t1.id=t2.id WHERE t2.id IS NULL;
Assume that
t2.idis defined asNOT NULL. In this case, MySQL scanst1and looks up the rows int2using the values oft1.id. If MySQL finds a matching row int2, it knows thatt2.idcan never beNULL, and does not scan through the rest of the rows int2that have the sameidvalue. In other words, for each row int1, MySQL needs to do only a single lookup int2, regardless of how many rows actually match int2.Range checked for each record (index map:N)MySQL found no good index to use, but found that some of indexes might be used after column values from preceding tables are known. For each row combination in the preceding tables, MySQL checks whether it is possible to use a
rangeorindex_mergeaccess method to retrieve rows. This is not very fast, but is faster than performing a join with no index at all. The applicability criteria are as described in Section 7.13.1, “Range Optimization”, and Section 7.13.2, “Index Merge Optimization”, with the exception that all column values for the preceding table are known and considered to be constants.Indexes are numbered beginning with 1, in the same order as shown by
SHOW INDEXfor the table. The index map valueNis a bitmask value that indicates which indexes are candidates. For example, a value of0x19(binary 11001) means that indexes 1, 4, and 5 will be considered.ScannedNdatabasesThis indicates how many directory scans the server performs when processing a query for
INFORMATION_SCHEMAtables, as described in Section 7.2.4, “OptimizingINFORMATION_SCHEMAQueries”. The value ofNcan be 0, 1, orall.Select tables optimized awayThe query contained only aggregate functions (
MIN(),MAX()) that were all resolved using an index, orCOUNT(*)forMyISAM, and noGROUP BYclause. The optimizer determined that only one row should be returned.Skip_open_table,Open_frm_only,Open_trigger_only,Open_full_tableThese values indicate file-opening optimizations that apply to queries for
INFORMATION_SCHEMAtables, as described in Section 7.2.4, “OptimizingINFORMATION_SCHEMAQueries”.Skip_open_table: Table files do not need to be opened. The information has already become available within the query by scanning the database directory.Open_frm_only: Only the table's.frmfile need be opened.Open_trigger_only: Only the table's.TRGfile need be opened.Open_full_table: The unoptimized information lookup. The.frm,.MYD, and.MYIfiles must be opened.
unique row not foundFor a query such as
SELECT ... FROM, no rows satisfy the condition for atbl_nameUNIQUEindex orPRIMARY KEYon the table.Using filesortMySQL must do an extra pass to find out how to retrieve the rows in sorted order. The sort is done by going through all rows according to the join type and storing the sort key and pointer to the row for all rows that match the
WHEREclause. The keys then are sorted and the rows are retrieved in sorted order. See Section 7.13.9, “ORDER BYOptimization”.Using indexThe column information is retrieved from the table using only information in the index tree without having to do an additional seek to read the actual row. This strategy can be used when the query uses only columns that are part of a single index.
For
InnoDBtables that have a user-defined clustered index, that index can be used even whenUsing indexis absent from theExtracolumn. This is the case iftypeisindexandkeyisPRIMARY.Using index for group-bySimilar to the
Using indextable access method,Using index for group-byindicates that MySQL found an index that can be used to retrieve all columns of aGROUP BYorDISTINCTquery without any extra disk access to the actual table. Additionally, the index is used in the most efficient way so that for each group, only a few index entries are read. For details, see Section 7.13.10, “GROUP BYOptimization”.Using join bufferTables from earlier joins are read in portions into the join buffer, and then their rows are used from the buffer to perform the join with the current table.
Using sort_union(...),Using union(...),Using intersect(...)These indicate how index scans are merged for the
index_mergejoin type. See Section 7.13.2, “Index Merge Optimization”.Using temporaryTo resolve the query, MySQL needs to create a temporary table to hold the result. This typically happens if the query contains
GROUP BYandORDER BYclauses that list columns differently.Using whereA
WHEREclause is used to restrict which rows to match against the next table or send to the client. Unless you specifically intend to fetch or examine all rows from the table, you may have something wrong in your query if theExtravalue is notUsing whereand the table join type isALLorindex. Even if you are using an index for all parts of aWHEREclause, you may seeUsing whereif the column can beNULL.Using where with pushed conditionThis item applies to
NDBCLUSTERtables only. It means that MySQL Cluster is using the Condition Pushdown optimization to improve the efficiency of a direct comparison between a nonindexed column and a constant. In such cases, the condition is “pushed down” to the cluster's data nodes and is evaluated on all data nodes simultaneously. This eliminates the need to send nonmatching rows over the network, and can speed up such queries by a factor of 5 to 10 times over cases where Condition Pushdown could be but is not used. For more information, see Section 7.13.3, “Engine Condition Pushdown Optimization”.
You can get a good indication of how good a join is by taking
the product of the values in the rows column
of the EXPLAIN output. This
should tell you roughly how many rows MySQL must examine to
execute the query. If you restrict queries with the
max_join_size system variable,
this row product also is used to determine which multiple-table
SELECT statements to execute and
which to abort. See Section 7.11.2, “Tuning Server Parameters”.
The following example shows how a multiple-table join can be
optimized progressively based on the information provided by
EXPLAIN.
Suppose that you have the SELECT
statement shown here and that you plan to examine it using
EXPLAIN:
EXPLAIN SELECT tt.TicketNumber, tt.TimeIn,
tt.ProjectReference, tt.EstimatedShipDate,
tt.ActualShipDate, tt.ClientID,
tt.ServiceCodes, tt.RepetitiveID,
tt.CurrentProcess, tt.CurrentDPPerson,
tt.RecordVolume, tt.DPPrinted, et.COUNTRY,
et_1.COUNTRY, do.CUSTNAME
FROM tt, et, et AS et_1, do
WHERE tt.SubmitTime IS NULL
AND tt.ActualPC = et.EMPLOYID
AND tt.AssignedPC = et_1.EMPLOYID
AND tt.ClientID = do.CUSTNMBR;
For this example, make the following assumptions:
The columns being compared have been declared as follows.
Table Column Data Type ttActualPCCHAR(10)ttAssignedPCCHAR(10)ttClientIDCHAR(10)etEMPLOYIDCHAR(15)doCUSTNMBRCHAR(15)The tables have the following indexes.
Table Index ttActualPCttAssignedPCttClientIDetEMPLOYID(primary key)doCUSTNMBR(primary key)The
tt.ActualPCvalues are not evenly distributed.
Initially, before any optimizations have been performed, the
EXPLAIN statement produces the
following information:
table type possible_keys key key_len ref rows Extra
et ALL PRIMARY NULL NULL NULL 74
do ALL PRIMARY NULL NULL NULL 2135
et_1 ALL PRIMARY NULL NULL NULL 74
tt ALL AssignedPC, NULL NULL NULL 3872
ClientID,
ActualPC
Range checked for each record (index map: 0x23)
Because type is
ALL for each table, this
output indicates that MySQL is generating a Cartesian product of
all the tables; that is, every combination of rows. This takes
quite a long time, because the product of the number of rows in
each table must be examined. For the case at hand, this product
is 74 × 2135 × 74 × 3872 = 45,268,558,720
rows. If the tables were bigger, you can only imagine how long
it would take.
One problem here is that MySQL can use indexes on columns more
efficiently if they are declared as the same type and size. In
this context, VARCHAR and
CHAR are considered the same if
they are declared as the same size.
tt.ActualPC is declared as
CHAR(10) and et.EMPLOYID
is CHAR(15), so there is a length mismatch.
To fix this disparity between column lengths, use
ALTER TABLE to lengthen
ActualPC from 10 characters to 15 characters:
mysql> ALTER TABLE tt MODIFY ActualPC VARCHAR(15);
Now tt.ActualPC and
et.EMPLOYID are both
VARCHAR(15). Executing the
EXPLAIN statement again produces
this result:
table type possible_keys key key_len ref rows Extra
tt ALL AssignedPC, NULL NULL NULL 3872 Using
ClientID, where
ActualPC
do ALL PRIMARY NULL NULL NULL 2135
Range checked for each record (index map: 0x1)
et_1 ALL PRIMARY NULL NULL NULL 74
Range checked for each record (index map: 0x1)
et eq_ref PRIMARY PRIMARY 15 tt.ActualPC 1
This is not perfect, but is much better: The product of the
rows values is less by a factor of 74. This
version executes in a couple of seconds.
A second alteration can be made to eliminate the column length
mismatches for the tt.AssignedPC =
et_1.EMPLOYID and tt.ClientID =
do.CUSTNMBR comparisons:
mysql>ALTER TABLE tt MODIFY AssignedPC VARCHAR(15),->MODIFY ClientID VARCHAR(15);
After that modification, EXPLAIN
produces the output shown here:
table type possible_keys key key_len ref rows Extra
et ALL PRIMARY NULL NULL NULL 74
tt ref AssignedPC, ActualPC 15 et.EMPLOYID 52 Using
ClientID, where
ActualPC
et_1 eq_ref PRIMARY PRIMARY 15 tt.AssignedPC 1
do eq_ref PRIMARY PRIMARY 15 tt.ClientID 1
At this point, the query is optimized almost as well as
possible. The remaining problem is that, by default, MySQL
assumes that values in the tt.ActualPC column
are evenly distributed, and that is not the case for the
tt table. Fortunately, it is easy to tell
MySQL to analyze the key distribution:
mysql> ANALYZE TABLE tt;
With the additional index information, the join is perfect and
EXPLAIN produces this result:
table type possible_keys key key_len ref rows Extra
tt ALL AssignedPC NULL NULL NULL 3872 Using
ClientID, where
ActualPC
et eq_ref PRIMARY PRIMARY 15 tt.ActualPC 1
et_1 eq_ref PRIMARY PRIMARY 15 tt.AssignedPC 1
do eq_ref PRIMARY PRIMARY 15 tt.ClientID 1
Note that the rows column in the output from
EXPLAIN is an educated guess from
the MySQL join optimizer. Check whether the numbers are even
close to the truth by comparing the rows
product with the actual number of rows that the query returns.
If the numbers are quite different, you might get better
performance by using STRAIGHT_JOIN in your
SELECT statement and trying to
list the tables in a different order in the
FROM clause.
It is possible in some cases to execute statements that modify
data when EXPLAIN
SELECT is used with a subquery; for more information,
see Section 12.2.10.8, “Subqueries in the FROM Clause”.