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b66cdbd1ea
This makes it easier to compare different costs and also allows
the optimizer to optimizer different storage engines more reliably.
- Added tests/check_costs.pl, a tool to verify optimizer cost calculations.
- Most engine costs has been found with this program. All steps to
calculate the new costs are documented in Docs/optimizer_costs.txt
- User optimizer_cost variables are given in microseconds (as individual
costs can be very small). Internally they are stored in ms.
- Changed DISK_READ_COST (was DISK_SEEK_BASE_COST) from a hard disk cost
(9 ms) to common SSD cost (400MB/sec).
- Removed cost calculations for hard disks (rotation etc).
- Changed the following handler functions to return IO_AND_CPU_COST.
This makes it easy to apply different cost modifiers in ha_..time()
functions for io and cpu costs.
- scan_time()
- rnd_pos_time() & rnd_pos_call_time()
- keyread_time()
- Enhanched keyread_time() to calculate the full cost of reading of a set
of keys with a given number of ranges and optional number of blocks that
need to be accessed.
- Removed read_time() as keyread_time() + rnd_pos_time() can do the same
thing and more.
- Tuned cost for: heap, myisam, Aria, InnoDB, archive and MyRocks.
Used heap table costs for json_table. The rest are using default engine
costs.
- Added the following new optimizer variables:
- optimizer_disk_read_ratio
- optimizer_disk_read_cost
- optimizer_key_lookup_cost
- optimizer_row_lookup_cost
- optimizer_row_next_find_cost
- optimizer_scan_cost
- Moved all engine specific cost to OPTIMIZER_COSTS structure.
- Changed costs to use 'records_out' instead of 'records_read' when
recalculating costs.
- Split optimizer_costs.h to optimizer_costs.h and optimizer_defaults.h.
This allows one to change costs without having to compile a lot of
files.
- Updated costs for filter lookup.
- Use a better cost estimate in best_extension_by_limited_search()
for the sorting cost.
- Fixed previous issues with 'filtered' explain column as we are now
using 'records_out' (min rows seen for table) to calculate filtering.
This greatly simplifies the filtering code in
JOIN_TAB::save_explain_data().
This change caused a lot of queries to be optimized differently than
before, which exposed different issues in the optimizer that needs to
be fixed. These fixes are in the following commits. To not have to
change the same test case over and over again, the changes in the test
cases are done in a single commit after all the critical change sets
are done.
InnoDB changes:
- Updated InnoDB to not divide big range cost with 2.
- Added cost for InnoDB (innobase_update_optimizer_costs()).
- Don't mark clustered primary key with HA_KEYREAD_ONLY. This will
prevent that the optimizer is trying to use index-only scans on
the clustered key.
- Disabled ha_innobase::scan_time() and ha_innobase::read_time() and
ha_innobase::rnd_pos_time() as the default engine cost functions now
works good for InnoDB.
Other things:
- Added --show-query-costs (\Q) option to mysql.cc to show the query
cost after each query (good when working with query costs).
- Extended my_getopt with GET_ADJUSTED_VALUE which allows one to adjust
the value that user is given. This is used to change cost from
microseconds (user input) to milliseconds (what the server is
internally using).
- Added include/my_tracker.h ; Useful include file to quickly test
costs of a function.
- Use handler::set_table() in all places instead of 'table= arg'.
- Added SHOW_OPTIMIZER_COSTS to sys variables. These are input and
shown in microseconds for the user but stored as milliseconds.
This is to make the numbers easier to read for the user (less
pre-zeros). Implemented in 'Sys_var_optimizer_cost' class.
- In test_quick_select() do not use index scans if 'no_keyread' is set
for the table. This is what we do in other places of the server.
- Added THD parameter to Unique::get_use_cost() and
check_index_intersect_extension() and similar functions to be able
to provide costs to called functions.
- Changed 'records' to 'rows' in optimizer_trace.
- Write more information to optimizer_trace.
- Added INDEX_BLOCK_FILL_FACTOR_MUL (4) and INDEX_BLOCK_FILL_FACTOR_DIV (3)
to calculate usage space of keys in b-trees. (Before we used numeric
constants).
- Removed code that assumed that b-trees has similar costs as binary
trees. Replaced with engine calls that returns the cost.
- Added Bitmap::find_first_bit()
- Added timings to join_cache for ANALYZE table (patch by Sergei Petrunia).
- Added records_init and records_after_filter to POSITION to remember
more of what best_access_patch() calculates.
- table_after_join_selectivity() changed to recalculate 'records_out'
based on the new fields from best_access_patch()
Bug fixes:
- Some queries did not update last_query_cost (was 0). Fixed by moving
setting thd->...last_query_cost in JOIN::optimize().
- Write '0' as number of rows for const tables with a matching row.
Some internals:
- Engine cost are stored in OPTIMIZER_COSTS structure. When a
handlerton is created, we also created a new cost variable for the
handlerton. We also create a new variable if the user changes a
optimizer cost for a not yet loaded handlerton either with command
line arguments or with SET
@@global.engine.optimizer_cost_variable=xx.
- There are 3 global OPTIMIZER_COSTS variables:
default_optimizer_costs The default costs + changes from the
command line without an engine specifier.
heap_optimizer_costs Heap table costs, used for temporary tables
tmp_table_optimizer_costs The cost for the default on disk internal
temporary table (MyISAM or Aria)
- The engine cost for a table is stored in table_share. To speed up
accesses the handler has a pointer to this. The cost is copied
to the table on first access. If one wants to change the cost one
must first update the global engine cost and then do a FLUSH TABLES.
This was done to be able to access the costs for an open table
without any locks.
- When a handlerton is created, the cost are updated the following way:
See sql/keycaches.cc for details:
- Use 'default_optimizer_costs' as a base
- Call hton->update_optimizer_costs() to override with the engines
default costs.
- Override the costs that the user has specified for the engine.
- One handler open, copy the engine cost from handlerton to TABLE_SHARE.
- Call handler::update_optimizer_costs() to allow the engine to update
cost for this particular table.
- There are two costs stored in THD. These are copied to the handler
when the table is used in a query:
- optimizer_where_cost
- optimizer_scan_setup_cost
- Simply code in best_access_path() by storing all cost result in a
structure. (Idea/Suggestion by Igor)
693 lines
18 KiB
Text
693 lines
18 KiB
Text
create table t0(a int);
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insert into t0 values (0),(1),(2),(3),(4),(5),(6),(7),(8),(9);
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create table t1(a int);
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insert into t1 select A.a + B.a* 10 + C.a * 100 from t0 A, t0 B, t0 C;
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create table t2 (
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a int,
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b int,
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key (a)
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);
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insert into t2 select A.a*1000 + B.a, A.a*1000 + B.a from t0 A, t1 B;
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#
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# Try an UPDATE that uses filesort:
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#
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explain
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update t2 set b=b+1 order by b limit 5;
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id select_type table type possible_keys key key_len ref rows Extra
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1 SIMPLE t2 ALL NULL NULL NULL NULL 10000 Using filesort
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explain format=json
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update t2 set b=b+1 order by b limit 5;
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EXPLAIN
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{
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"query_block": {
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"select_id": 1,
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"filesort": {
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"table": {
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"update": 1,
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"table_name": "t2",
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"access_type": "ALL",
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"rows": 10000
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}
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}
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}
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}
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analyze format=json
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update t2 set b=b+1 order by b limit 5;
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ANALYZE
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{
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"query_optimization": {
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"r_total_time_ms": "REPLACED"
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},
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"query_block": {
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"select_id": 1,
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"r_total_time_ms": "REPLACED",
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"filesort": {
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"r_loops": 1,
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"r_total_time_ms": "REPLACED",
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"r_limit": 5,
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"r_used_priority_queue": true,
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"r_output_rows": 6,
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"r_sort_mode": "sort_key,rowid",
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"table": {
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"update": 1,
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"table_name": "t2",
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"access_type": "ALL",
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"rows": 10000,
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"r_rows": 10000,
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"r_filtered": 100,
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"r_total_time_ms": "REPLACED"
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}
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}
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}
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}
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#
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# Try an UPDATE that uses buffering:
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#
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explain
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update t2 set a=a+1 where a<10;
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id select_type table type possible_keys key key_len ref rows Extra
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1 SIMPLE t2 range a a 5 NULL 9 Using where; Using buffer
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explain format=json
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update t2 set a=a+1 where a<10;
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EXPLAIN
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{
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"query_block": {
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"select_id": 1,
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"buffer": {
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"table": {
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"update": 1,
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"table_name": "t2",
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"access_type": "range",
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"possible_keys": ["a"],
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"key": "a",
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"key_length": "5",
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"used_key_parts": ["a"],
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"rows": 9,
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"attached_condition": "t2.a < 10"
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}
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}
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}
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}
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analyze format=json
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update t2 set a=a+1 where a<10;
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ANALYZE
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{
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"query_optimization": {
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"r_total_time_ms": "REPLACED"
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},
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"query_block": {
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"select_id": 1,
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"r_total_time_ms": "REPLACED",
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"buffer": {
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"table": {
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"update": 1,
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"table_name": "t2",
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"access_type": "range",
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"possible_keys": ["a"],
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"key": "a",
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"key_length": "5",
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"used_key_parts": ["a"],
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"rows": 9,
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"r_rows": 10,
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"r_filtered": 100,
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"r_total_time_ms": "REPLACED",
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"attached_condition": "t2.a < 10"
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}
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}
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}
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}
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#
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# Try a DELETE that uses filesort:
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#
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explain
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delete from t2 order by b limit 5;
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id select_type table type possible_keys key key_len ref rows Extra
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1 SIMPLE t2 ALL NULL NULL NULL NULL 10000 Using filesort
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explain format=json
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delete from t2 order by b limit 5;
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EXPLAIN
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{
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"query_block": {
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"select_id": 1,
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"filesort": {
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"table": {
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"delete": 1,
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"table_name": "t2",
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"access_type": "ALL",
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"rows": 10000
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}
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}
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}
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}
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analyze format=json
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delete from t2 order by b limit 5;
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ANALYZE
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{
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"query_optimization": {
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"r_total_time_ms": "REPLACED"
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},
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"query_block": {
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"select_id": 1,
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"r_total_time_ms": "REPLACED",
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"filesort": {
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"r_loops": 1,
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"r_total_time_ms": "REPLACED",
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"r_used_priority_queue": false,
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"r_output_rows": 10000,
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"r_buffer_size": "REPLACED",
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"r_sort_mode": "sort_key,rowid",
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"table": {
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"delete": 1,
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"table_name": "t2",
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"access_type": "ALL",
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"rows": 10000,
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"r_rows": 10000,
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"r_filtered": 100,
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"r_total_time_ms": "REPLACED"
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}
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}
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}
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}
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#
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# Try a SELECT with QEP in form: filesort { tmp_table { join } }
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#
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explain
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select * from t0,t2 where t2.a=t0.a order by t2.b limit 4;
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id select_type table type possible_keys key key_len ref rows Extra
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1 SIMPLE t0 ALL NULL NULL NULL NULL 10 Using where; Using temporary; Using filesort
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1 SIMPLE t2 ref a a 5 test.t0.a 1
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explain format=json
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select * from t0,t2 where t2.a=t0.a order by t2.b limit 4;
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EXPLAIN
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{
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"query_block": {
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"select_id": 1,
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"filesort": {
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"sort_key": "t2.b",
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"temporary_table": {
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"nested_loop": [
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{
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"table": {
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"table_name": "t0",
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"access_type": "ALL",
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"rows": 10,
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"filtered": 100,
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"attached_condition": "t0.a is not null"
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}
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},
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{
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"table": {
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"table_name": "t2",
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"access_type": "ref",
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"possible_keys": ["a"],
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"key": "a",
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"key_length": "5",
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"used_key_parts": ["a"],
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"ref": ["test.t0.a"],
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"rows": 1,
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"filtered": 100
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}
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}
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]
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}
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}
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}
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}
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analyze format=json
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select * from t0,t2 where t2.a=t0.a order by t2.b limit 4;
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ANALYZE
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{
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"query_optimization": {
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"r_total_time_ms": "REPLACED"
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},
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"query_block": {
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"select_id": 1,
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"r_loops": 1,
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"r_total_time_ms": "REPLACED",
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"filesort": {
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"sort_key": "t2.b",
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"r_loops": 1,
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"r_total_time_ms": "REPLACED",
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"r_limit": 4,
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"r_used_priority_queue": true,
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"r_output_rows": 4,
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"r_sort_mode": "sort_key,rowid",
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"temporary_table": {
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"nested_loop": [
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{
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"table": {
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"table_name": "t0",
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"access_type": "ALL",
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"r_loops": 1,
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"rows": 10,
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"r_rows": 10,
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"r_table_time_ms": "REPLACED",
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"r_other_time_ms": "REPLACED",
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"filtered": 100,
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"r_filtered": 100,
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"attached_condition": "t0.a is not null"
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}
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},
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{
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"table": {
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"table_name": "t2",
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"access_type": "ref",
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"possible_keys": ["a"],
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"key": "a",
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"key_length": "5",
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"used_key_parts": ["a"],
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"ref": ["test.t0.a"],
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"r_loops": 10,
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"rows": 1,
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"r_rows": 0.4,
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"r_table_time_ms": "REPLACED",
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"r_other_time_ms": "REPLACED",
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"filtered": 100,
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"r_filtered": 100
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}
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}
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]
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}
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}
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}
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}
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#
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# Try a SELECT with QEP in form: join { filesort { table0 }, table2 }
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#
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explain
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select * from t0,t2 where t2.a=t0.a order by t0.a limit 4;
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id select_type table type possible_keys key key_len ref rows Extra
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1 SIMPLE t0 ALL NULL NULL NULL NULL 10 Using where; Using filesort
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1 SIMPLE t2 ref a a 5 test.t0.a 1
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explain format=json
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select * from t0,t2 where t2.a=t0.a order by t0.a limit 4;
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EXPLAIN
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{
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"query_block": {
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"select_id": 1,
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"nested_loop": [
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{
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"read_sorted_file": {
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"filesort": {
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"sort_key": "t0.a",
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"table": {
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"table_name": "t0",
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"access_type": "ALL",
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"rows": 10,
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"filtered": 100,
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"attached_condition": "t0.a is not null"
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}
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}
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}
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},
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{
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"table": {
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"table_name": "t2",
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"access_type": "ref",
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"possible_keys": ["a"],
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"key": "a",
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"key_length": "5",
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"used_key_parts": ["a"],
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"ref": ["test.t0.a"],
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"rows": 1,
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"filtered": 100
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}
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}
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]
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}
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}
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analyze format=json
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select * from t0,t2 where t2.a=t0.a order by t0.a limit 4;
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ANALYZE
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{
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"query_optimization": {
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"r_total_time_ms": "REPLACED"
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},
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"query_block": {
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"select_id": 1,
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"r_loops": 1,
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"r_total_time_ms": "REPLACED",
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"nested_loop": [
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{
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"read_sorted_file": {
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"r_rows": 10,
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"filesort": {
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"sort_key": "t0.a",
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"r_loops": 1,
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"r_total_time_ms": "REPLACED",
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"r_used_priority_queue": false,
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"r_output_rows": 10,
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"r_buffer_size": "REPLACED",
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"r_sort_mode": "sort_key,addon_fields",
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"table": {
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"table_name": "t0",
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"access_type": "ALL",
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"r_loops": 1,
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"rows": 10,
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"r_rows": 10,
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"r_table_time_ms": "REPLACED",
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"r_other_time_ms": "REPLACED",
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"filtered": 100,
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"r_filtered": 100,
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"attached_condition": "t0.a is not null"
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}
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}
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}
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},
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{
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"table": {
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"table_name": "t2",
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"access_type": "ref",
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"possible_keys": ["a"],
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"key": "a",
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"key_length": "5",
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"used_key_parts": ["a"],
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"ref": ["test.t0.a"],
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"r_loops": 10,
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"rows": 1,
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"r_rows": 0.4,
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"r_table_time_ms": "REPLACED",
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"r_other_time_ms": "REPLACED",
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"filtered": 100,
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"r_filtered": 100
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}
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}
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]
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}
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}
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drop table t2;
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create table t2 (
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a int,
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b int,
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c int
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);
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insert into t2
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select
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a.a+10*b.a+100*c.a,
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b.a+10*c.a,
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c.a
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from t0 a, t0 b, t0 c;
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analyze format=json
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select MAX(b) from t2 where mod(a,2)=0 group by c;
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ANALYZE
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{
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"query_optimization": {
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"r_total_time_ms": "REPLACED"
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},
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"query_block": {
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"select_id": 1,
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"r_loops": 1,
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"r_total_time_ms": "REPLACED",
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"filesort": {
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"sort_key": "t2.c",
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"r_loops": 1,
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"r_total_time_ms": "REPLACED",
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"r_used_priority_queue": false,
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"r_output_rows": 10,
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"r_buffer_size": "REPLACED",
|
|
"r_sort_mode": "sort_key,rowid",
|
|
"temporary_table": {
|
|
"nested_loop": [
|
|
{
|
|
"table": {
|
|
"table_name": "t2",
|
|
"access_type": "ALL",
|
|
"r_loops": 1,
|
|
"rows": 1000,
|
|
"r_rows": 1000,
|
|
"r_table_time_ms": "REPLACED",
|
|
"r_other_time_ms": "REPLACED",
|
|
"filtered": 100,
|
|
"r_filtered": 50,
|
|
"attached_condition": "t2.a MOD 2 = 0"
|
|
}
|
|
}
|
|
]
|
|
}
|
|
}
|
|
}
|
|
}
|
|
drop table t2;
|
|
#
|
|
# MDEV-8282: crash in filesort() with simple ordered delete
|
|
#
|
|
create table t3(a int) engine=innodb;
|
|
delete from t3 order by a;
|
|
# EXPLAIN thinks it will use delete_all_rows():
|
|
explain
|
|
delete from t3 order by a;
|
|
id select_type table type possible_keys key key_len ref rows Extra
|
|
1 SIMPLE NULL NULL NULL NULL NULL NULL 1 Deleting all rows
|
|
# ANALYZE shows that delete_all_rows() didn't work and we deleted rows
|
|
# one-by-one:
|
|
analyze
|
|
delete from t3 order by a;
|
|
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
|
|
1 SIMPLE t3 ALL NULL NULL NULL NULL 1 0.00 100.00 100.00 Using filesort
|
|
drop table t3;
|
|
#
|
|
# A test for duplicate_removal()
|
|
#
|
|
create table t3 (a int, b int);
|
|
insert into t3 select a, 123 from t0;
|
|
analyze format=json
|
|
select distinct max(t3.b) Q from t0, t3 where t0.a=t3.a group by t0.a order by null;
|
|
ANALYZE
|
|
{
|
|
"query_optimization": {
|
|
"r_total_time_ms": "REPLACED"
|
|
},
|
|
"query_block": {
|
|
"select_id": 1,
|
|
"r_loops": 1,
|
|
"r_total_time_ms": "REPLACED",
|
|
"duplicate_removal": {
|
|
"temporary_table": {
|
|
"nested_loop": [
|
|
{
|
|
"table": {
|
|
"table_name": "t0",
|
|
"access_type": "ALL",
|
|
"r_loops": 1,
|
|
"rows": 10,
|
|
"r_rows": 10,
|
|
"r_table_time_ms": "REPLACED",
|
|
"r_other_time_ms": "REPLACED",
|
|
"filtered": 100,
|
|
"r_filtered": 100
|
|
}
|
|
},
|
|
{
|
|
"block-nl-join": {
|
|
"table": {
|
|
"table_name": "t3",
|
|
"access_type": "ALL",
|
|
"r_loops": 1,
|
|
"rows": 10,
|
|
"r_rows": 10,
|
|
"r_table_time_ms": "REPLACED",
|
|
"r_other_time_ms": "REPLACED",
|
|
"filtered": 100,
|
|
"r_filtered": 100
|
|
},
|
|
"buffer_type": "flat",
|
|
"buffer_size": "65",
|
|
"join_type": "BNL",
|
|
"attached_condition": "t3.a = t0.a",
|
|
"r_filtered": 10,
|
|
"r_unpack_time_ms": "REPLACED"
|
|
}
|
|
}
|
|
]
|
|
}
|
|
}
|
|
}
|
|
}
|
|
#
|
|
# A query with two filesort calls:
|
|
# - first is needed to do group-by-group grouping to calculate COUNT(DISTINCT)
|
|
# - the second is need to produce ORDER BY.
|
|
# (see MDEV-7836 for description of the query plan)
|
|
create table t5 (a int , b int) ;
|
|
create table t6 like t5 ;
|
|
create table t7 like t5 ;
|
|
insert into t5 values (0, 100), (1, 2), (1, 3), (2, 2), (2, 7),
|
|
(2, -1), (3, 10);
|
|
insert into t6 values (0, 0), (1, 1), (2, 1), (3, 1), (4, 1);
|
|
insert into t7 values (3, 3), (2, 2), (1, 1);
|
|
# TODO: This ANALYZE output doesn't make it clear what is used for what.
|
|
analyze format=json
|
|
select count(distinct t5.b) as sum from t5, t6
|
|
where t5.a=t6.a and t6.b > 0 and t5.a <= 5
|
|
group by t5.a order by sum limit 1;
|
|
ANALYZE
|
|
{
|
|
"query_optimization": {
|
|
"r_total_time_ms": "REPLACED"
|
|
},
|
|
"query_block": {
|
|
"select_id": 1,
|
|
"r_loops": 1,
|
|
"r_total_time_ms": "REPLACED",
|
|
"filesort": {
|
|
"sort_key": "count(distinct t5.b)",
|
|
"r_loops": 1,
|
|
"r_total_time_ms": "REPLACED",
|
|
"r_limit": 1,
|
|
"r_used_priority_queue": true,
|
|
"r_output_rows": 2,
|
|
"r_sort_mode": "sort_key,rowid",
|
|
"temporary_table": {
|
|
"filesort": {
|
|
"sort_key": "t5.a",
|
|
"r_loops": 1,
|
|
"r_total_time_ms": "REPLACED",
|
|
"r_used_priority_queue": false,
|
|
"r_output_rows": 6,
|
|
"r_buffer_size": "REPLACED",
|
|
"r_sort_mode": "sort_key,rowid",
|
|
"temporary_table": {
|
|
"nested_loop": [
|
|
{
|
|
"table": {
|
|
"table_name": "t6",
|
|
"access_type": "ALL",
|
|
"r_loops": 1,
|
|
"rows": 5,
|
|
"r_rows": 5,
|
|
"r_table_time_ms": "REPLACED",
|
|
"r_other_time_ms": "REPLACED",
|
|
"filtered": 100,
|
|
"r_filtered": 80,
|
|
"attached_condition": "t6.b > 0 and t6.a <= 5"
|
|
}
|
|
},
|
|
{
|
|
"block-nl-join": {
|
|
"table": {
|
|
"table_name": "t5",
|
|
"access_type": "ALL",
|
|
"r_loops": 1,
|
|
"rows": 7,
|
|
"r_rows": 7,
|
|
"r_table_time_ms": "REPLACED",
|
|
"r_other_time_ms": "REPLACED",
|
|
"filtered": 100,
|
|
"r_filtered": 100
|
|
},
|
|
"buffer_type": "flat",
|
|
"buffer_size": "119",
|
|
"join_type": "BNL",
|
|
"attached_condition": "t5.a = t6.a",
|
|
"r_filtered": 21.42857143,
|
|
"r_unpack_time_ms": "REPLACED"
|
|
}
|
|
}
|
|
]
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
explain format=json
|
|
select count(distinct t5.b) as sum from t5, t6
|
|
where t5.a=t6.a and t6.b > 0 and t5.a <= 5
|
|
group by t5.a order by sum limit 1;
|
|
EXPLAIN
|
|
{
|
|
"query_block": {
|
|
"select_id": 1,
|
|
"filesort": {
|
|
"sort_key": "count(distinct t5.b)",
|
|
"temporary_table": {
|
|
"filesort": {
|
|
"sort_key": "t5.a",
|
|
"temporary_table": {
|
|
"nested_loop": [
|
|
{
|
|
"table": {
|
|
"table_name": "t6",
|
|
"access_type": "ALL",
|
|
"rows": 5,
|
|
"filtered": 100,
|
|
"attached_condition": "t6.b > 0 and t6.a <= 5"
|
|
}
|
|
},
|
|
{
|
|
"block-nl-join": {
|
|
"table": {
|
|
"table_name": "t5",
|
|
"access_type": "ALL",
|
|
"rows": 7,
|
|
"filtered": 100
|
|
},
|
|
"buffer_type": "flat",
|
|
"buffer_size": "119",
|
|
"join_type": "BNL",
|
|
"attached_condition": "t5.a = t6.a"
|
|
}
|
|
}
|
|
]
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
drop table t5,t6,t7;
|
|
drop table t3;
|
|
#
|
|
# Tabular ANALYZE must get its data from execution tracker (and not from
|
|
# the query plan)
|
|
#
|
|
CREATE TABLE t2(
|
|
col1 int,
|
|
col2 int,
|
|
UNIQUE INDEX idx (col1, col2)) engine=myisam;
|
|
INSERT INTO t2(col1, col2) VALUES
|
|
(1,20),(2,19),(3,18),(4,17),(5,16),(6,15),(7,14),(8,13),(9,12),(10,11),
|
|
(11,10),(12,9),(13,8),(14,7),(15,6),(16,5),(17,4),(18,3),(19,2),(20,1);
|
|
flush status;
|
|
explain
|
|
select col1 f1, col2 f2, col1 f3 from t2 group by f1;
|
|
id select_type table type possible_keys key key_len ref rows Extra
|
|
1 SIMPLE t2 range NULL idx 5 NULL 7 Using index for group-by
|
|
analyze
|
|
select col1 f1, col2 f2, col1 f3 from t2 group by f1;
|
|
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
|
|
1 SIMPLE t2 range NULL idx 5 NULL 7 20.00 100.00 100.00 Using index for group-by
|
|
analyze format=json
|
|
select col1 f1, col2 f2, col1 f3 from t2 group by f1;
|
|
ANALYZE
|
|
{
|
|
"query_optimization": {
|
|
"r_total_time_ms": "REPLACED"
|
|
},
|
|
"query_block": {
|
|
"select_id": 1,
|
|
"r_loops": 1,
|
|
"r_total_time_ms": "REPLACED",
|
|
"nested_loop": [
|
|
{
|
|
"table": {
|
|
"table_name": "t2",
|
|
"access_type": "range",
|
|
"key": "idx",
|
|
"key_length": "5",
|
|
"used_key_parts": ["col1"],
|
|
"r_loops": 1,
|
|
"rows": 7,
|
|
"r_rows": 20,
|
|
"r_table_time_ms": "REPLACED",
|
|
"r_other_time_ms": "REPLACED",
|
|
"filtered": 100,
|
|
"r_filtered": 100,
|
|
"using_index_for_group_by": true
|
|
}
|
|
}
|
|
]
|
|
}
|
|
}
|
|
drop table t2;
|
|
drop table t0,t1;
|