This bug could affect queries with IN subqueries in WHERE clause and using
derived tables to which split optimization potentially could be applied.
When looking for the best split of a splittable derived table T any key
access from a semi-join materialized table used for lookups S to table T
must be excluded from consideration because in the current implementation
of such tables as S the values from its records cannot be used to access
other tables.
Approved by Oleksandr Byelkin <sanja@mariadb.com>
The code in choose_best_splitting() assumed that the join prefix is
in join->positions[].
This is not necessarily the case. This function might be called when
the join prefix is in join->best_positions[], too.
Follow the approach from best_access_path(), which calls this function:
pass the current join prefix as an argument,
"const POSITION *join_positions" and use that.
This bug could affect queries containing a subquery over splittable derived
tables and having an outer references in its WHERE clause. If such subquery
contained an equality condition whose left part was a reference to a column
of the derived table and the right part referred only to outer columns
then the server crashed in the function st_join_table::choose_best_splitting()
The crashing code was added in the commit ce7ffe61d8
that made the code of the function sensitive to presence of the flag
OUTER_REF_TABLE_BIT in the KEYUSE_EXT::needed_in_prefix fields.
The field needed_in_prefix of the KEYUSE_EXT structure should not contain
table maps with OUTER_REF_TABLE_BIT or RAND_TABLE_BIT.
Note that this fix is quite conservative: for affected queries it just
returns the query plans that were used before the above mentioned commit.
In fact the equalities causing crashes should be pushed into derived tables
without any usage of split optimization.
Approved by Sergei Petrunia <sergey@mariadb.com>
This bug could affect queries containing a subquery over splittable derived
tables and having an outer references in its WHERE clause. If such subquery
contained an equality condition whose left part was a reference to a column
of the derived table and the right part referred only to outer columns
then the server crashed in the function st_join_table::choose_best_splitting()
The crashing code was added in the commit ce7ffe61d8
that made the code of the function sensitive to presence of the flag
OUTER_REF_TABLE_BIT in the KEYUSE_EXT::needed_in_prefix fields.
The field needed_in_prefix of the KEYUSE_EXT structure should not contain
table maps with OUTER_REF_TABLE_BIT or RAND_TABLE_BIT.
Note that this fix is quite conservative: for affected queries it just
returns the query plans that were used before the above mentioned commit.
In fact the equalities causing crashes should be pushed into derived tables
without any usage of split optimization.
Approved by Sergei Petrunia <sergey@mariadb.com>
This patch optimizes the number of refills for the lateral derived table
to which a materialized derived table subject to split optimization is
is converted. This optimized number of refills is now considered as the
expected number of refills of the materialized derived table when searching
for the best possible splitting of the table.
The crash happened due to rows=2 vs rows=1 difference between how the
estimate of number of rows in a derived table is computed in
TABLE_LIST::fetch_number_of_rows() and JOIN::add_keyuses_for_splitting().
Made JOIN::add_keyuses_for_splitting() use the result of computations in
TABLE_LIST::fetch_number_of_rows().
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)
One effect of this change in the test suite is that tests with very few
rows changed to use sub queries instead of materialization. This is
correct and expected as for these the materialization overhead is too high.
A lot of tests where fixed to still use materialization by adding a
few rows to the tables (most tests has only 2-3 rows and are thus easily
affected when cost computations are changed).
Other things:
- Added more variables to TMPTABLE_COSTS for better cost calculation
- Added cost of copying rows to TMPTABLE_COSTS lookup and write
- Added THD::optimizer_cache_hit_ratio for easier cost calculations
- Added DISK_FAST_READ_SIZE to be used when calculating costs when
reading big blocks from a disk
This cleans up the interface for choose_plan() as it is not depending
on setting join->emb_sj_nest.
choose_plan() now sets up join->emb_sj_nest and join->allowed_tables before
calling optimize_straight_join() and best_extension_by_limited_search().
Other things:
- Converted some 'if' to DBUG_ASSERT() as these should always be true.
- Calculate 'allowed_tables' in choose_plan() as this never changes in
the childs.
- Added assert to check that next_emb->nested_join->n_tables doesn't
get to a wrong value.
- Documented some variables in sql_select.h
Before this patch, when calculating the cost of fetching and using a
row/key from the engine, we took into account the cost of finding a
row or key from the engine, but did not consistently take into account
index only accessed, clustered key or covered keys for all access
paths.
The cost of the WHERE clause (TIME_FOR_COMPARE) was not consistently
considered in best_access_path(). TIME_FOR_COMPARE was used in
calculation in other places, like greedy_search(), but was in some
cases (like scans) done an a different number of rows than was
accessed.
The cost calculation of row and index scans didn't take into account
the number of rows that where accessed, only the number of accepted
rows.
When using a filter, the cost of index_only_reads and cost of
accessing and disregarding 'filtered rows' where not taken into
account, which made filters cost less than there actually where.
To remedy the above, the following key & row fetch related costs
has been added:
- The cost of fetching and using a row is now split into different costs:
- key + Row fetch cost (as before) but multiplied with the variable
'optimizer_cache_cost' (default to 0.5). This allows the user to
tell the optimizer the likehood of finding the key and row in the
engine cache.
- ROW_COPY_COST, The cost copying a row from the engine to the
sql layer or creating a row from the join_cache to the record
buffer. Mostly affects table scan costs.
- ROW_LOOKUP_COST, the cost of fetching a row by rowid.
- KEY_COPY_COST the cost of finding the next key and copying it from
the engine to the SQL layer. This is used when we calculate the cost
index only reads. It makes index scans more expensive than before if
they cover a lot of rows. (main.index_merge_myisam)
- KEY_LOOKUP_COST, the cost of finding the first key in a range.
This replaces the old define IDX_LOOKUP_COST, but with a higher cost.
- KEY_NEXT_FIND_COST, the cost of finding the next key (and rowid).
when doing a index scan and comparing the rowid to the filter.
Before this cost was assumed to be 0.
All of the above constants/variables are now tuned to be somewhat in
proportion of executing complexity to each other. There is tuning
need for these in the future, but that can wait until the above are
made user variables as that will make tuning much easier.
To make the usage of the above easy, there are new (not virtual)
cost calclation functions in handler:
- ha_read_time(), like read_time(), but take optimizer_cache_cost into
account.
- ha_read_and_copy_time(), like ha_read_time() but take into account
ROW_COPY_TIME
- ha_read_and_compare_time(), like ha_read_and_copy_time() but take
TIME_FOR_COMPARE into account.
- ha_rnd_pos_time(). Read row with row id, taking ROW_COPY_COST
into account. This is used with filesort where we don't need
to execute the WHERE clause again.
- ha_keyread_time(), like keyread_time() but take
optimizer_cache_cost into account.
- ha_keyread_and_copy_time(), like ha_keyread_time(), but add
KEY_COPY_COST.
- ha_key_scan_time(), like key_scan_time() but take
optimizer_cache_cost nto account.
- ha_key_scan_and_compare_time(), like ha_key_scan_time(), but add
KEY_COPY_COST & TIME_FOR_COMPARE.
I also added some setup costs for doing different types of scans and
creating temporary tables (on disk and in memory). This encourages
the optimizer to not use these for simple 'a few row' lookups if
there are adequate key lookup strategies.
- TABLE_SCAN_SETUP_COST, cost of starting a table scan.
- INDEX_SCAN_SETUP_COST, cost of starting an index scan.
- HEAP_TEMPTABLE_CREATE_COST, cost of creating in memory
temporary table.
- DISK_TEMPTABLE_CREATE_COST, cost of creating an on disk temporary
table.
When calculating cost of fetching ranges, we had a cost of
IDX_LOOKUP_COST (0.125) for doing a key div for a new range. This is
now replaced with 'io_cost * KEY_LOOKUP_COST (1.0) *
optimizer_cache_cost', which matches the cost we use for 'ref' and
other key lookups. The effect is that the cost is now a bit higher
when we have many ranges for a key.
Allmost all calculation with TIME_FOR_COMPARE is now done in
best_access_path(). 'JOIN::read_time' now includes the full
cost for finding the rows in the table.
In the result files, many of the changes are now again close to what
they where before the "Update cost for hash and cached joins" commit,
as that commit didn't fix the filter cost (too complex to do
everything in one commit).
The above changes showed a lot of a lot of inconsistencies in
optimizer cost calculation. The main objective with the other changes
was to do calculation as similar (and accurate) as possible and to make
different plans more comparable.
Detailed list of changes:
- Calculate index_only_cost consistently and correctly for all scan
and ref accesses. The row fetch_cost and index_only_cost now
takes into account clustered keys, covered keys and index
only accesses.
- cost_for_index_read now returns both full cost and index_only_cost
- Fixed cost calculation of get_sweep_read_cost() to match other
similar costs. This is bases on the assumption that data is more
often stored on SSD than a hard disk.
- Replaced constant 2.0 with new define TABLE_SCAN_SETUP_COST.
- Some scan cost estimates did not take into account
TIME_FOR_COMPARE. Now all scan costs takes this into
account. (main.show_explain)
- Added session variable optimizer_cache_hit_ratio (default 50%). By
adjusting this on can reduce or increase the cost of index or direct
record lookups. The effect of the default is that key lookups is now
a bit cheaper than before. See usage of 'optimizer_cache_cost' in
handler.h.
- JOIN_TAB::scan_time() did not take into account index only scans,
which produced a wrong cost when index scan was used. Changed
JOIN_TAB:::scan_time() to take into consideration clustered and
covered keys. The values are now cached and we only have to call
this function once. Other calls are changed to use the cached
values. Function renamed to JOIN_TAB::estimate_scan_time().
- Fixed that most index cost calculations are done the same way and
more close to 'range' calculations. The cost is now lower than
before for small data sets and higher for large data sets as we take
into account how many keys are read (main.opt_trace_selectivity,
main.limit_rows_examined).
- Ensured that index_scan_cost() ==
range(scan_of_all_rows_in_table_using_one_range) +
MULTI_RANGE_READ_INFO_CONST. One effect of this is that if there
is choice of doing a full index scan and a range-index scan over
almost the whole table then index scan will be preferred (no
range-read setup cost). (innodb.innodb, main.show_explain,
main.range)
- Fixed the EQ_REF and REF takes into account clustered and covered
keys. This changes some plans to use covered or clustered indexes
as these are much cheaper. (main.subselect_mat_cost,
main.state_tables_innodb, main.limit_rows_examined)
- Rowid filter setup cost and filter compare cost now takes into
account fetching and checking the rowid (KEY_NEXT_FIND_COST).
(main.partition_pruning heap.heap_btree main.log_state)
- Added KEY_NEXT_FIND_COST to
Range_rowid_filter_cost_info::lookup_cost to account of the time
to find and check the next key value against the container
- Introduced ha_keyread_time(rows) that takes into account finding
the next row and copying the key value to 'record'
(KEY_COPY_COST).
- Introduced ha_key_scan_time() for calculating an index scan over
all rows.
- Added IDX_LOOKUP_COST to keyread_time() as a startup cost.
- Added index_only_fetch_cost() as a convenience function to
OPT_RANGE.
- keyread_time() cost is slightly reduced to prefer shorter keys.
(main.index_merge_myisam)
- All of the above caused some index_merge combinations to be
rejected because of cost (main.index_intersect). In some cases
'ref' where replaced with index_merge because of the low
cost calculation of get_sweep_read_cost().
- Some index usage moved from PRIMARY to a covering index.
(main.subselect_innodb)
- Changed cost calculation of filter to take KEY_LOOKUP_COST and
TIME_FOR_COMPARE into account. See sql_select.cc::apply_filter().
filter parameters and costs are now written to optimizer_trace.
- Don't use matchings_records_in_range() to try to estimate the number
of filtered rows for ranges. The reason is that we want to ensure
that 'range' is calculated similar to 'ref'. There is also more work
needed to calculate the selectivity when using ranges and ranges and
filtering. This causes filtering column in EXPLAIN EXTENDED to be
100.00 for some cases where range cannot use filtering.
(main.rowid_filter)
- Introduced ha_scan_time() that takes into account the CPU cost of
finding the next row and copying the row from the engine to
'record'. This causes costs of table scan to slightly increase and
some test to changed their plan from ALL to RANGE or ALL to ref.
(innodb.innodb_mysql, main.select_pkeycache)
In a few cases where scan time of very small tables have lower cost
than a ref or range, things changed from ref/range to ALL.
(main.myisam, main.func_group, main.limit_rows_examined,
main.subselect2)
- Introduced ha_scan_and_compare_time() which is like ha_scan_time()
but also adds the cost of the where clause (TIME_FOR_COMPARE).
- Added small cost for creating temporary table for
materialization. This causes some very small tables to use scan
instead of materialization.
- Added checking of the WHERE clause (TIME_FOR_COMPARE) of the
accepted rows to ROR costs in get_best_ror_intersect()
- Removed '- 0.001' from 'join->best_read' and optimize_straight_join()
to ensure that the 'Last_query_cost' status variable contains the
same value as the one that was calculated by the optimizer.
- Take avg_io_cost() into account in handler::keyread_time() and
handler::read_time(). This should have no effect as it's 1.0 by
default, except for heap that overrides these functions.
- Some 'ref_or_null' accesses changed to 'range' because of cost
adjustments (main.order_by)
- Added scan type "scan_with_join_cache" for optimizer_trace. This is
just to show in the trace what kind of scan was used.
- When using 'scan_with_join_cache' take into account number of
preceding tables (as have to restore all fields for all previous
table combination when checking the where clause)
The new cost added is:
(row_combinations * ROW_COPY_COST * number_of_cached_tables).
This increases the cost of join buffering in proportion of the
number of tables in the join buffer. One effect is that full scans
are now done earlier as the cost is then smaller.
(main.join_outer_innodb, main.greedy_optimizer)
- Removed the usage of 'worst_seeks' in cost_for_index_read as it
caused wrong plans to be created; It prefered JT_EQ_REF even if it
would be much more expensive than a full table scan. A related
issue was that worst_seeks only applied to full lookup, not to
clustered or index only lookups, which is not consistent. This
caused some plans to use index scan instead of eq_ref (main.union)
- Changed federated block size from 4096 to 1500, which is the
typical size of an IO packet.
- Added costs for reading rows to Federated. Needed as there is no
caching of rows in the federated engine.
- Added ha_innobase::rnd_pos_time() cost function.
- A lot of extra things added to optimizer trace
- More costs, especially for materialization and index_merge.
- Make lables more uniform
- Fixed a lot of minor bugs
- Added 'trace_started()' around a lot of trace blocks.
- When calculating ORDER BY with LIMIT cost for using an index
the cost did not take into account the number of row retrivals
that has to be done or the cost of comparing the rows with the
WHERE clause. The cost calculated would be just a fraction of
the real cost. Now we calculate the cost as we do for ranges
and 'ref'.
- 'Using index for group-by' is used a bit more than before as
now take into account the WHERE clause cost when comparing
with 'ref' and prefer the method with fewer row combinations.
(main.group_min_max).
Bugs fixed:
- Fixed that we don't calculate TIME_FOR_COMPARE twice for some plans,
like in optimize_straight_join() and greedy_search()
- Fixed bug in save_explain_data where we could test for the wrong
index when displaying 'Using index'. This caused some old plans to
show 'Using index'. (main.subselect_innodb, main.subselect2)
- Fixed bug in get_best_ror_intersect() where 'min_cost' was not
updated, and the cost we compared with was not the one that was
used.
- Fixed very wrong cost calculation for priority queues in
check_if_pq_applicable(). (main.order_by now correctly uses priority
queue)
- When calculating cost of EQ_REF or REF, we added the cost of
comparing the WHERE clause with the found rows, not all row
combinations. This made ref and eq_ref to be regarded way to cheap
compared to other access methods.
- FORCE INDEX cost calculation didn't take into account clustered or
covered indexes.
- JT_EQ_REF cost was estimated as avg_io_cost(), which is half the
cost of a JT_REF key. This may be true for InnoDB primary key, but
not for other unique keys or other engines. Now we use handler
function to calculate the cost, which allows us to handle
consistently clustered, covered keys and not covered keys.
- ha_start_keyread() didn't call extra_opt() if keyread was already
enabled but still changed the 'keyread' variable (which is wrong).
Fixed by not doing anything if keyread is already enabled.
- multi_range_read_info_cost() didn't take into account io_cost when
calculating the cost of ranges.
- fix_semijoin_strategies_for_picked_join_order() used the wrong
record_count when calling best_access_path() for SJ_OPT_FIRST_MATCH
and SJ_OPT_LOOSE_SCAN.
- Hash joins didn't provide correct best_cost to the upper level, which
means that the cost for hash_joins more expensive than calculated
in best_access_path (a difference of 10x * TIME_OF_COMPARE).
This is fixed in the new code thanks to that we now include
TIME_OF_COMPARE cost in 'read_time'.
Other things:
- Added some 'if (thd->trace_started())' to speed up code
- Removed not used function Cost_estimate::is_zero()
- Simplified testing of HA_POS_ERROR in get_best_ror_intersect().
(No cost changes)
- Moved ha_start_keyread() from join_read_const_table() to join_read_const()
to enable keyread for all types of JT_CONST tables.
- Made a few very short functions inline in handler.h
Notes:
- In main.rowid_filter the join order of order and lineitem is swapped.
This is because the cost of doing a range fetch of lineitem(98 rows) is
almost as big as the whole join of order,lineitem. The filtering will
also ensure that we only have to do very small key fetches of the rows
in lineitem.
- main.index_merge_myisam had a few changes where we are now using
less keys for index_merge. This is because index scans are now more
expensive than before.
- handler->optimizer_cache_cost is updated in ha_external_lock().
This ensures that it is up to date per statements.
Not an optimal solution (for locked tables), but should be ok for now.
- 'DELETE FROM t1 WHERE t1.a > 0 ORDER BY t1.a' does not take cost of
filesort into consideration when table scan is chosen.
(main.myisam_explain_non_select_all)
- perfschema.table_aggregate_global_* has changed because an update
on a table with 1 row will now use table scan instead of key lookup.
TODO in upcomming commits:
- Fix selectivity calculation for ranges with and without filtering and
when there is a ref access but scan is chosen.
For this we have to store the lowest known value for
'accepted_records' in the OPT_RANGE structure.
- Change that records_read does not include filtered rows.
- test_if_cheaper_ordering() needs to be updated to properly calculate
costs. This will fix tests like main.order_by_innodb,
main.single_delete_update
- Extend get_range_limit_read_cost() to take into considering
cost_for_index_read() if there where no quick keys. This will reduce
the computed cost for ORDER BY with LIMIT in some cases.
(main.innodb_ext_key)
- Fix that we take into account selectivity when counting the number
of rows we have to read when considering using a index table scan to
resolve ORDER BY.
- Add new calculation for rnd_pos_time() where we take into account the
benefit of reading multiple rows from the same page.
- Before any multiple add() calls, always use (if trace_started()).
- Add unlikely() around all tests of trace_started().
- Change trace.add(); trace.add(); to trace.add().add();
- When trace.add() goes over several line, use the following formating:
trace.
add(xxx).
add(yyy).
add(zzz);
This format was choosen after a discussion between Sergei Petrunia and
me as it looks similar indepedent if 'trace' is an object or a
pointer. It also more suitable for an editors auto-indentation.
Other things:
Added DBUG_ASSERT(thd->trace_started()) to a few functions that should
only be called if trace is enabled.
"use_roworder_index_merge: true" changed to "use_sort_index_merge: false"
As the original output was often not correct.
Also fixed the related 'cause' to be correct.
In best_access_path() print the cost (and number of rows) before
checking if it the plan should be used. This removes the need to print
the cost in two places.
Changed a few "read_time" tags to "cost".
MDEV-28073 Slow query performance in MariaDB when using many table
The idea is to prefer and chain EQ_REF tables (tables that uses an
unique key to find a row) when searching for the best table combination.
This significantly reduces row combinations that has to be examined.
This is optimization is enabled when setting optimizer_prune_level=2
(which is now default).
Implementation:
- optimizer_prune_level has a new level, 2, which enables EQ_REF
optimization in addition to the pruning done by level 1.
Level 2 is now default.
- Added JOIN::eq_ref_tables that contains bits of tables that could use
potentially use EQ_REF access in the query. This is calculated
in sort_and_filter_keyuse()
Under optimizer_prune_level=2:
- When the greedy_optimizer notices that the preceding table was an
EQ_REF table, it tries to add an EQ_REF table next. If an EQ_REF
table exists, only this one will be considered at this level.
We also collect all EQ_REF tables chained by the next levels and these
are ignored on the starting level as we have already examined these.
If no EQ_REF table exists, we continue as normal.
This optimization speeds up the greedy_optimizer combination test with
~25%
Other things:
- I ported the changes in MySQL 5.7 to greedy_optimizer.test to MariaDB
to be able to ensure we can handle all cases that MySQL can do.
- I have run all tests with --mysqld=--optimizer_prune_level=1 to verify that
there where no test changes.
This bug may affect the queries that uses a grouping derived table with
grouping list containing references to columns from different tables if
the optimizer decides to employ the split optimization for the derived
table. In some very specific cases it may affect queries with a grouping
derived table that refers only one base table.
This bug was caused by an improper fix for the bug MDEV-25128. The fix
tried to get rid of the equality conditions pushed into the where clause
of the grouping derived table T to which the split optimization had been
applied. The fix erroneously assumed that only those pushed equalities
that were used for ref access of the tables referenced by T were needed.
In fact the function remove_const() that figures out what columns from the
group list can be removed if the split optimization is applied can uses
other pushed equalities as well.
This patch actually provides a proper fix for MDEV-25128. Rather than
trying to remove invalid pushed equalities referencing the fields of SJM
tables with a look-up access the patch attempts not to push such equalities.
Approved by Oleksandr Byelkin <sanja@mariadb.com>
This bug could affect queries with a grouping derived table containing
equalities in the where clause of its specification if the optimizer
chose to apply split optimization to access the derived table. In such
cases wrong results could be returned from the queries.
When the optimizer considers a possibility of using split optimization
to a derived table it injects equalities joining the derived table with
other tables into the where condition of the derived table. After the join
order for the execution using split optimization has been chosen as the
cheapest the injected equalities that are not used to access the derived
table are removed from the where condition of the derived table.
For this removal the optimizer looks through the conjuncts of the where
condition of the derived table, fetches the equalities and checks whether
they belong to the list of injected equalities.
As the injection of the list was performed just by the insertion of it
into the list of top level AND condition of the where condition some extra
conjuncts from the where condition could be automatically attached to the
end of the list of injected equalities. If such attached conjunct happened
to be an equality predicate it was removed from the where condition of the
derived table and thus lost for checking at the execution phase.
The bug has been fixed by injecting of a shallow copy of the list of the
pushed equalities rather than the list itself leaving the latter intact.
Approved by Oleksandr Byelkin <sanja@mariadb.com>
Disable LATERAL DERIVED optimization for subqueries that have WITH ROLLUP.
This bug could affect queries with grouping derived tables / views / CTEs
with ROLLUP. The bug could manifest itself if the corresponding
materialized derived tables are subject to split optimization.
The current implementation of the split optimization produces rows
from the derived table in an arbitrary order. So these rows must be
accumulated in another temporary table and sorted according to the
used GROUP BY clause in order to be able to generate the additional
ROLLUP rows.
This patch prohibits to use split optimization for grouping derived
tables / views / CTEs with ROLLUP.
https://jira.mariadb.org/browse/MDEV-26221
my_sys DYNAMIC_ARRAY and DYNAMIC_STRING inconsistancy
The DYNAMIC_STRING uses size_t for sizes, but DYNAMIC_ARRAY used uint.
This patch adjusts DYNAMIC_ARRAY to use size_t like DYNAMIC_STRING.
As the MY_DIR member number_of_files is copied from a DYNAMIC_ARRAY,
this is changed to be size_t.
As MY_TMPDIR members 'cur' and 'max' are copied from a DYNAMIC_ARRAY,
these are also changed to be size_t.
The lists of plugins and stored procedures use DYNAMIC_ARRAY,
but their APIs assume a size of 'uint'; these are unchanged.
If a join query uses a derived table (view / CTE) with GROUP BY clause then
the execution plan for such join may employ split optimization. When this
optimization is employed the derived table is not materialized. Rather only
some partitions of the derived table are subject to grouping. Split
optimization can be applied only if:
- there are some indexes over the tables used in the join specifying the
derived table whose prefixes partially cover the field items used in the
GROUP BY list (such indexes are called splitting indexes)
- the WHERE condition of the join query contains conjunctive equalities
between columns of the derived table that comprise major parts of
splitting indexes and columns of the other join tables.
When the optimizer evaluates extending of a partial join by the rows of the
derived table it always considers a possibility of using split optimization.
Different splitting indexes can be used depending on the extended partial
join. At some rare conditions, for example, when there is a non-splitting
covering index for a table joined in the join specifying the derived table
usage of a splitting index to produce rows needed for grouping may be still
less beneficial than usage of such covering index without any splitting
technique. The function JOIN_TAB::choose_best_splitting() must take this
into account.
Approved by Oleksandr Byelkin <sanja@mariadb.com>
If a join query uses a derived table (view / CTE) with GROUP BY clause then
the execution plan for such join may employ split optimization. When this
optimization is employed the derived table is not materialized. Rather only
some partitions of the derived table are subject to grouping. Split
optimization can be applied only if:
- there are some indexes over the tables used in the join specifying the
derived table whose prefixes partially cover the field items used in the
GROUP BY list (such indexes are called splitting indexes)
- the WHERE condition of the join query contains conjunctive equalities
between columns of the derived table that comprise major parts of
splitting indexes and columns of the other join tables.
When the optimizer evaluates extending of a partial join by the rows of the
derived table it always considers a possibility of using split optimization.
Different splitting indexes can be used depending on the extended partial
join. At some rare conditions, for example, when there is a non-splitting
covering index for a table joined in the join specifying the derived table
usage of a splitting index to produce rows needed for grouping may be still
less beneficial than usage of such covering index without any splitting
technique. The function JOIN_TAB::choose_best_splitting() must take this
into account.
Approved by Oleksandr Byelkin <sanja@mariadb.com>
