Query Optimization¶

USING INDEX¶

USING INDEX clause should be specified after WHERE clause of SELECT, DELETE or UPDATE statement. USING INDEX clause forces a sequential/index scan to be used or an index that can improve the performance to be included.

If USING INDEX clause is specified with the list of index names, query optimizer creates optimized execution plan by calculating the query execution cost based on the specified indexes only and comparing the index scan cost and the sequential scan cost of the specified indexes(CUBRID performs cost-based query optimization to select an execution plan).

The USING INDEX clause is useful to get the results in the desired order without ORDER BY. When index scan is performed by CUBRID, the results are created in the order they were saved in the index. When there are more than one indexes in one table, you can use USING INDEX to get the query results in a given order of indexes.

SELECT ... WHERE ...
[USING INDEX { NONE | [ ALL EXCEPT ] <index_spec> [ {, <index_spec> } ...] } ] [ ; ]

DELETE ... WHERE ...
[USING INDEX { NONE | [ ALL EXCEPT ] <index_spec> [ {, <index_spec> } ...] } ] [ ; ]

UPDATE ... WHERE ...
[USING INDEX { NONE | [ ALL EXCEPT ] <index_spec> [ {, <index_spec> } ...] } ] [ ; ]

<index_spec> ::=
  [table_spec.]index_name [(+) | (-)] |
  table_spec.NONE

• NONE : If NONE is specified, a sequential scan is used on all tables.
• ALL EXCEPT : All indexes except the specified indexes can be used when the query is executed.
• index_name(+) : If (+) is specified after the index_name, it is the first priority in index selection. IF this index is not proper to run the query, it is not selected.
• index_name(-) : If (-) is specified after the index_name, it is excluded from index selection.
• table_spec.NONE : All indexes are excluded from the selection, so sequential scan is used.

USE, FORCE, IGNORE INDEX¶

Index hints can be specified through USE, FORCE, IGNORE INDEX syntax after table specification of FROM clause.

FROM table_spec [ <index_hint_clause> ] ...

<index_hint_clause> ::=
  { USE | FORCE | IGNORE } INDEX  ( <index_spec> [, <index_spec>  ...] )

<index_spec> ::=
  [table_spec.]index_name

• USE INDEX ( <index_spec> ): Only specified indexes are considered when choose them.
• FORCE INDEX ( <index_spec> ): Specified indexes are chosen as the first priority.
• IGNORE INDEX ( <index_spec> ): Specified indexes are excluded from the choice.

USE, FORCE, IGNORE INDEX syntax is automatically rewritten as the proper USING INDEX syntax by the system.

Examples of index hint¶

CREATE TABLE athlete (
   code             SMALLINT PRIMARY KEY,
   name             VARCHAR(40) NOT NULL,
   gender           CHAR(1),
   nation_code      CHAR(3),
   event            VARCHAR(30)
);
CREATE UNIQUE INDEX athlete_idx1 ON athlete (code, nation_code);
CREATE INDEX athlete_idx2 ON athlete (gender, nation_code);

Below two queries do the same behavior and they select index scan if the specified index, athlete_idx2's scan cost is lower than sequential scan cost.

SELECT /*+ RECOMPILE */ *
FROM athlete USE INDEX (athlete_idx2)
WHERE gender='M' AND nation_code='USA';

SELECT /*+ RECOMPILE */ *
FROM athlete
WHERE gender='M' AND nation_code='USA'
USING INDEX athlete_idx2;

Below two queries do the same behavior and they always use athlete_idx2

SELECT /*+ RECOMPILE */ *
FROM athlete FORCE INDEX (athlete_idx2)
WHERE gender='M' AND nation_code='USA';

SELECT /*+ RECOMPILE */ *
FROM athlete
WHERE gender='M' AND nation_code='USA'
USING INDEX athlete_idx2(+);

Below two queries do the same behavior and they always don't use athlete_idx2

SELECT /*+ RECOMPILE */ *
FROM athlete IGNORE INDEX (athlete_idx2)
WHERE gender='M' AND nation_code='USA';

SELECT /*+ RECOMPILE */ *
FROM athlete
WHERE gender='M' AND nation_code='USA'
USING INDEX athlete_idx2(-);

Below query always do the sequential scan.

SELECT *
FROM athlete
WHERE gender='M' AND nation_code='USA'
USING INDEX NONE;

SELECT *
FROM athlete
WHERE gender='M' AND nation_code='USA'
USING INDEX athlete.NONE;

Below query forces to be possible to use all indexes except athlete_idx2 index.

SELECT *
FROM athlete
WHERE gender='M' AND nation_code='USA'
USING INDEX ALL EXCEPT athlete_idx2;

When two or more indexes have been specified in the USING INDEX clause, the query optimizer selects the proper one of the specified indexes.

SELECT *
FROM athlete USE INDEX (char_idx, athlete_idx)
WHERE gender='M' AND nation_code='USA';

SELECT *
FROM athlete
WHERE gender='M' AND nation_code='USA'
USING INDEX char_idx, athlete_idx;

When a query is run for several tables, you can specify a table to perform index scan by using a specific index and another table to perform sequential scan. The query has the following format.

SELECT *
FROM tab1, tab2
WHERE ...
USING INDEX tab1.idx1, tab2.NONE;

When executing a query with the index hint syntax, the query optimizer considers all available indexes on the table for which no index has been specified. For example, when the tab1 table includes idx1 and idx2 and the tab2 table includes idx3, idx4, and idx5, if indexes for only tab1 are specified but no indexes are specified for tab2, the query optimizer considers the indexes of tab2.

SELECT ...
FROM tab1, tab2 USE INDEX(tab1.idx1)
WHERE ... ;

SELECT ...
FROM tab1, tab2
WHERE ...
USING INDEX tab1.idx1;

The above query select the scan method of table tab1 after comparing the cost between the sequential scan of the table tab1 and the index scan of the index idx1, and select the scan method of table tab2 after comparing the cost between the sequential scan of the table tab2 and the index scan of the indexes idx3, idx4, idx5.

Filtered Index¶

The filtered index is used to sort, search, or operate a well-defined partials set for one table. It is called the partial index since only some data that satisfy the condition are kept in that index.

CREATE /*+ hints */ INDEX index_name
ON table_name (col1, col2, ...)
WHERE <filter_predicate>;

ALTER  /*+ hints */ INDEX index_name
[ ON table_name (col1, col2, ...)
[ WHERE <filter_predicate> ] ]
REBUILD;

<filter_predicate> ::= <filter_predicate> AND <expression> | <expression>

• <filter_predicate>: Condition to compare the column and the constant. When there are several conditions, filtering is available only when they are connected by using AND. The filter conditions can include most of the operators and functions supported by CUBRID. However, the date/time function that shows the current date/time (ex: SYS_DATETIME()) or random functions (ex: RAND()), which outputs different results for one input are not allowed.

If you apply the filtered index, that filtered index must be specified by USING INDEX clause or USE INDEX syntax.

SELECT *
FROM blogtopic
WHERE postDate>'2010-01-01'
USING INDEX my_filter_index;

The following example shows a bug tracking system that maintains bugs/issues. After a specified period of development, the bugs table records bugs. Most of the bugs have already been closed. The bug tracking system makes queries on the table to find new open bugs. In this case, the indexes on the bug table do not need to know the records on closed bugs. Then the filtered indexes allow indexing of open bugs only.

CREATE TABLE bugs
(
    bugID BIGINT NOT NULL,
    CreationDate TIMESTAMP NOT NULL,
    Author VARCHAR(255),
    Subject VARCHAR(255),
    Description VARCHAR(255),
    CurrentStatus INTEGER,
    Closed SMALLINT
);

Indexes for open bugs can be created by using the following sentence:

CREATE INDEX idx_open_bugs ON bugs(CreationDate) WHERE Closed = 0;

To process queries that are interested in open bugs, specify the index as an index hint. It will allow creating query results by accessing less index pages through filtered indexes.

SELECT *
FROM bugs  USE INDEX (idx_open_bugs)
WHERE CreationDate > CURRENT_DATE - 10 AND Closed = 0;

Constraints

Only generic indexes are allowed as filtered indexes. For example, the filtered unique index is not allowed. Also, it is not allowable that columns which compose an index are all NULLable. For example, below is not allowed because Author is NULLable.

CREATE INDEX idx_open_bugs ON bugs (Author) WHERE Closed = 0;

ERROR: before ' ; '
Invalid filter expression (bugs.Closed=0) for index.

However, below is allowed because Author is NULLable, but CreationDate is not NULLable.

CREATE INDEX idx_open_bugs ON bugs (Author, CreationDate) WHERE Closed = 0;

The following cases are not allowed as filtering conditions.

• Functions, which output different results with the same input, such as date/time function or random function

  CREATE INDEX idx ON bugs(creationdate) WHERE creationdate > SYS_DATETIME;
  
  ERROR: before ' ; '
  'sys_datetime ' is not allowed in a filter expression for index.
  
  CREATE INDEX idx ON bugs(bugID) WHERE bugID > RAND();
  
  ERROR: before ' ; '
  'rand ' is not allowed in a filter expression for index.
  

• In case of using the OR operator

  CREATE INDEX IDX ON bugs(bugID) WHERE bugID > 10 OR bugID = 3;
  
  In line 1, column 62,
  
  ERROR: before ' ; '
  ' or ' is not allowed in a filter expression for index.
  

• In case of including functions like INCR(), DECR() functions, which modify the data of a table.

• In case of Serial-related functions and including pseudo columns.

• In case of including aggregate functions such as MIN(), MAX(), STDDEV()

• In case of using the types where indexes cannot be created

  • The operators and functions where an argument is the SET type
  • The functions to use LOB file(CHAR_TO_BLOB(), CHAR_TO_CLOB(), BIT_TO_BLOB(), BLOB_FROM_FILE(), CLOB_FROM_FILE())

• The IS NULL operator can be used only when at least one column of an index is not NULL.

CREATE TABLE t (a INT, b INT);

-- IS NULL cannot be used with expressions
CREATE INDEX idx ON t (a) WHERE (not a) IS NULL;

ERROR: before ' ; '
Invalid filter expression (( not t.a<>0) is null ) for index.

CREATE INDEX idx ON t (a) WHERE (a+1) IS NULL;

ERROR: before ' ; '
Invalid filter expression ((t.a+1) is null ) for index.

-- At least one attribute must not be used with IS NULL
CREATE INDEX idx ON t(a,b) WHERE a IS NULL ;

ERROR: before '  ; '
Invalid filter expression (t.a is null ) for index.

CREATE INDEX idx ON t(a,b) WHERE a IS NULL and b IS NULL;

ERROR: before ' ; '
Invalid filter expression (t.a is null  and t.b is null ) for index.

CREATE INDEX idx ON t(a,b) WHERE a IS NULL and b IS NOT NULL;

• Index Skip Scan (ISS) is not allowed for the filtered indexes.

• The length of condition string used for the filtered index is limited to 128 characters.

  CREATE TABLE t(VeryLongColumnNameOfTypeInteger INT);
  
  CREATE INDEX idx ON t(VeryLongColumnNameOfTypeInteger)
  WHERE VeryLongColumnNameOfTypeInteger > 3 AND VeryLongColumnNameOfTypeInteger < 10 AND
  sqrt(VeryLongColumnNameOfTypeInteger) < 3 AND SQRT(VeryLongColumnNameOfTypeInteger) < 10;
  
  ERROR: before ' ; '
  The maximum length of filter predicate string must be 128.
  

Function-based Index¶

Function-based index is used to sort or find the data based on the combination of values of table rows by using a specific function. For example, to find the space-ignored string, it can be used to optimize the query by using the function that provides the feature. In addition, it is useful to search the non-case-sensitive names.

CREATE /*+ hints */ INDEX index_name
ON table_name (function_name (argument_list));

ALTER /*+ hints */ INDEX index_name
[ ON table_name (function_name (argument_list)) ]
REBUILD;

After the following indexes have been created, the SELECT query automatically uses the function-based index.

CREATE INDEX idx_trim_post ON posts_table(TRIM(keyword));

SELECT *
FROM posts_table
WHERE TRIM(keyword) = 'SQL';

If a function-based index is created by using the LOWER function, it can be used to search the non-case-sensitive names.

CREATE INDEX idx_last_name_lower ON clients_table(LOWER(LastName));

SELECT *
FROM clients_table
WHERE LOWER(LastName) = LOWER('Timothy');

To make an index selected while creating a query plan, the function used for the index should be used for the query condition in the same way. The SELECT query above uses the last_name_lower index created above. However, this index is not used for the following condition:

SELECT *
FROM clients_table
WHERE LOWER(CONCAT('Mr. ', LastName)) = LOWER('Mr. Timothy');

In addition, to make the function-based index used by force, use the USING INDEX syntax.

CREATE INDEX i_tbl_first_four ON tbl(LEFT(col, 4));
SELECT *
FROM clients_table
WHERE LEFT(col, 4) = 'CAT5'
USING INDEX i_tbl_first_four;

Functions with the function-based indexes are as follows:

ABS	ACOS	ADD_MONTHS	ADDDATE	ASIN
ATAN	ATAN2	BIT_COUNT	BIT_LENGTH	CEIL
CHAR_LENGTH	CHR	COS	COT	DATE
DATE_ADD	DATE_FORMAT	DATE_SUB	DATEDIFF	DAY
DAYOFMONTH	DAYOFWEEK	DAYOFYEAR	DEGREES	EXP
FLOOR	FORMAT	FROM_DAYS	FROM_UNIXTIME	GREATEST
HOUR	IFNULL	INET_ATON	INET_NTOA	INSTR
LAST_DAY	LEAST	LEFT	LN	LOCATE
LOG	LOG10	LOG2	LOWER	LPAD
LTRIM	MAKEDATE	MAKETIME	MD5	MID
MINUTE	MOD	MONTH	MONTHS_BETWEEN	NULLIF
NVL	NVL2	OCTET_LENGTH	POSITION	POWER
QUARTER	RADIANS	REPEAT	REPLACE	REVERSE
RIGHT	ROUND	RPAD	RTRIM	SECOND
SECTOTIME	SIN	SQRT	STR_TO_DATE	STRCMP
SUBDATE	SUBSTR	SUBSTRING	SUBSTRING_INDEX	TAN
TIME	TIME_FORMAT	TIMEDIFF	TIMESTAMP	TIMETOSEC
TO_CHAR	TO_DATE	TO_DATETIME	TO_DAYS	TO_NUMBER
TO_TIME	TO_TIMESTAMP	TRANSLATE	TRIM	TRUNC
UNIX_TIMESTAMP	UPPER	WEEK	WEEKDAY	YEAR

Arguments of functions which can be used in the function-based indexes, only column names and constants are allowed; nested expressions are not allowed. For example, a statement below will cause an error.

CREATE INDEX my_idx ON tbl (TRIM(LEFT(col, 3)));
CREATE INDEX my_idx ON tbl (LEFT(col1, col2 + 3));

However, implicit cast is allowed. In the example below, the first argument type of the LEFT () function should be VARCHAR and the second argument type should be INTEGER; it works normally.

CREATE INDEX my_idx ON tbl (LEFT(int_col, str_col));

Function-based indexes cannot be used with filtered indexes. The example will cause an error.

CREATE INDEX my_idx ON tbl ( TRIM(col) ) WHERE col > 'SQL';

Function-based indexes cannot become multiple-columns indexes. The example will cause an error.

CREATE INDEX my_idx ON tbl ( TRIM(col1), col2, LEFT(col3, 5) );

Covering Index¶

The covering index is the index including the data of all columns in the SELECT list and the WHERE, HAVING, GROUP BY, and ORDER BY clauses.

You only need to scan the index pages, as the covering index contains all the data necessary for executing a query, and it also reduces the I/O costs as it is not necessary to scan the data storage any further. To increase data search speed, you can consider creating a covering index but you should be aware that the INSERT and the DELETE processes may be slowed down due to the increase in index size.

The rules about the applicability of the covering index are as follows:

• If the covering index is applicable, you should use the CUBRID query optimizer first.
• For the join query, if the index includes columns of the table in the SELECT list, use this index.
• You cannot use the covering index if an index cannot be used.

CREATE TABLE t (col1 INT, col2 INT, col3 INT);
CREATE INDEX i_t_col1_col2_col3 ON t (col1,col2,col3);
INSERT INTO t VALUES (1,2,3),(4,5,6),(10,8,9);

The following example shows that the index is used as a covering index because columns of both SELECT and WHERE condition exist within the index.

csql> ;plan simple
SELECT * FROM t WHERE col1 < 6;

Query plan:
 Index scan(t t, i_t_col1_col2_col3, [(t.col1 range (min inf_lt t.col3))] (covers))

         col1         col2         col3
=======================================
            1            2            3
            4            5            6

CREATE TABLE tab(c VARCHAR(32));
INSERT INTO tab VALUES('abcd'),('abcd    '),('abcd ');
CREATE INDEX i_tab_c ON tab(c);

csql>;plan simple
SELECT * FROM tab where c='abcd    ' USING INDEX i_tab_c(+);

Query plan:
 Index scan(tab tab, i_tab_c, (tab.c='abcd    ') (covers))

 c
======================
'abcd'
'abcd'
'abcd'

SELECT * FROM tab WHERE c='abcd    ' USING INDEX tab.NONE;

Query plan:
 Sequential scan(tab tab)

 c
======================
'abcd'
'abcd    '
'abcd '

Optimizing ORDER BY Clause¶

The index including all columns in the ORDER BY clause is referred to as the ordered index. Optimizing the query with ORDER BY clause is no need for the additional sorting process(skip order by), because the query results are searched by the ordered index. In general, for an ordered index, the columns in the ORDER BY clause should be located at the front of the index.

SELECT *
FROM tab
WHERE col1 > 0
ORDER BY col1, col2

• The index consisting of tab (col1, col2) is an ordered index.
• The index consisting of tab (col1, col2, col3) is also an ordered index. This is because the col3, which is not referred by the ORDER BY clause comes after col1 and col2 .
• The index consisting of tab (col1) is not an ordered index.
• You can use the index consisting of tab (col3, col1, col2) or tab (col1, col3, col2) for optimization. This is because col3 is not located at the back of the columns in the ORDER BY clause.

Although the columns composing an index do not exist in the ORDER BY clause, you can use an ordered index if the column condition is a constant.

SELECT *
FROM tab
WHERE col2=val
ORDER BY col1,col3;

If the index consisting of tab (col1, col2, col3) exists and the index consisting of tab (col1, col2) do not exist when executing the above query, the query optimizer uses the index consisting of tab (col1, col2, col3) as an ordered index. You can get the result in the requested order when you execute an index scan, so you don't need to sort records.

If you can use the sorted index and the covering index, use the latter first. If you use the covering index, you don't need to retrieve additional data, because the data result requested is included in the index page, and you won't need to sort the result if you are satisfied with the index order.

If the query doesn't include any conditions and uses an ordered index, the ordered index will be used under the condition that the first column meets the NOT NULL condition.

CREATE TABLE tab (i INT, j INT, k INT);
CREATE INDEX i_tab_j_k on tab (j,k);
INSERT INTO tab VALUES (1,2,3),(6,4,2),(3,4,1),(5,2,1),(1,5,5),(2,6,6),(3,5,4);

The following example shows that indexes consisting of tab (j, k) become sorted indexes and no separate sorting process is required because GROUP BY is executed by j and k columns.

SELECT i,j,k
FROM tab
WHERE j > 0
ORDER BY j,k;

--  the  selection from the query plan dump shows that the ordering index i_tab_j_k was used and sorting was not necessary
--  (/* --> skip ORDER BY */)
Query plan:
iscan
    class: tab node[0]
    index: i_tab_j_k term[0]
    sort:  2 asc, 3 asc
    cost:  1 card 0
Query stmt:
select tab.i, tab.j, tab.k from tab tab where ((tab.j> ?:0 )) order by 2, 3
/* ---> skip ORDER BY */

            i            j            k
=======================================
            5            2            1
            1            2            3
            3            4            1
            6            4            2
            3            5            4
            1            5            5
            2            6            6

The following example shows that j and k columns execute ORDER BY and the index including all columns are selected so that indexes consisting of tab (j, k) are used as covering indexes; no separate process is required because the value is selected from the indexes themselves.

SELECT /*+ RECOMPILE */ j,k
FROM tab
WHERE j > 0
ORDER BY j,k;

--  in this case the index i_tab_j_k is a covering index and also respects the ordering index property.
--  Therefore, it is used as a covering index and sorting is not performed.

Query plan:
iscan
    class: tab node[0]
    index: i_tab_j_k term[0] (covers)
    sort:  1 asc, 2 asc
    cost:  1 card 0

Query stmt: select tab.j, tab.k from tab tab where ((tab.j> ?:0 )) order by 1, 2
/* ---> skip ORDER BY */

            j            k
==========================
            2            1
            2            3
            4            1
            4            2
            5            4
            5            5
            6            6

The following example shows that i column exists, ORDER BY is executed by j and k columns, and columns that perform SELECT are i, j, and k. Therefore, indexes consisting of tab (i, j, k) are used as covering indexes; separate sorting process is required for ORDER BY j, k even though the value is selected from the indexes themselves.

CREATE INDEX i_tab_j_k ON tab (i,j,k);
SELECT /*+ RECOMPILE */ i,j,k
FROM tab
WHERE i > 0
ORDER BY j,k;

-- since an index on (i,j,k) is now available, it will be used as covering index. However, sorting the results according to
-- the ORDER BY  clause is needed.
Query plan:
temp(order by)
    subplan: iscan
                 class: tab node[0]
                 index: i_tab_i_j_k term[0] (covers)
                 sort:  1 asc, 2 asc, 3 asc
                 cost:  1 card 1
    sort:  2 asc, 3 asc
    cost:  7 card 1

Query stmt: select tab.i, tab.j, tab.k from tab tab where ((tab.i> ?:0 )) order by 2, 3

            i            j            k
=======================================
            5            2            1
            1            2            3
            3            4            1
            6            4            2
            3            5            4
            1            5            5
            2            6            6

Index Scan in Descending Order¶

When a query is executed by sorting in descending order as follows, it usually creates a descending index. In this way, you do not have to go through addition procedure.

SELECT *
FROM tab
[WHERE ...]
ORDER BY a DESC

However, if you create an ascending index and an descending index in the same column, the possibility of deadlock increases. In order to decrease the possibility of such case, CUBRID supports the descending scan only with ascending index. Users can use the USE_DESC_IDX hint to specify the use of the descending scan. If the hint is not specified, the following three query executions should be considered, provided that the columns listed in the ORDER BY clause can use the index.

• Sequential scan + Sort in descending order
• Scan in general ascending order + sort in descending
• Scan in descending order that does not require a separate scan

Although the USE_DESC_IDX hint is omitted for the scan in descending order, the query optimizer decides the last execution plan of the three listed for an optimal plan.

CREATE TABLE di (i INT);
CREATE INDEX i_di_i on di (i);
INSERT INTO di VALUES (5),(3),(1),(4),(3),(5),(2),(5);

The query will be executed as an ascending scan without USE_DESC_IDX hint.

-- The same query, without the hint, will have a different output, since descending scan is not used.

SELECT  *
FROM di
WHERE i > 0
LIMIT 3;

Query plan:

Index scan(di di, i_di_i, (di.i range (0 gt_inf max) and inst_num() range (min inf_le 3)) (covers))

            i
=============
            1
            2
            3

If you add USE_DESC_IDX hint to the above query, a different result will be shown by descending scan.

-- We now run the following query, using the ''use_desc_idx'' SQL hint:

SELECT /*+ USE_DESC_IDX */ *
FROM di
WHERE i > 0
LIMIT 3;

Query plan:
 Index scan(di di, i_di_i, (di.i range (0 gt_inf max) and inst_num() range (min inf_le 3)) (covers) (desc_index))

            i
=============
            5
            5
            5

The following example requires descending order by ORDER BY clause. In this case, there is no USE_DESC_IDX but do the descending scan.

-- We also run the same query, this time asking that the results are displayed in descending order.
-- However, no hint is given.
-- Since ORDER BY...DESC clause exists, CUBRID will use descending scan, even though the hint is not given,
-- thus avoiding to sort the records.

SELECT *
FROM di
WHERE i > 0
ORDER BY i DESC LIMIT 3;

Query plan:
 Index scan(di di, i_di_i, (di.i range (0 gt_inf max)) (covers) (desc_index))

            i
=============
            5
            5
            5

Optimizing GROUP BY Clause¶

GROUP BY clause optimization works on the premise that if all columns in the GROUP BY clause are included in an index, you can use the index upon executing a query, so you don't execute a separate sorting job. The columns in the GROUP BY clause must exist in front side of the column forming the index.

SELECT *
FROM tab
WHERE col1 > 0
GROUP BY col1,col2

• You can use the index consisting of tab(col1, col2) for optimization.
• The index consisting of tab(col1, col2, col3) can be used because col3 no referred by GROUP BY comes after col1 and col2.
• You cannot use the index consisting of tab(col1) for optimization.
• You also cannot use the index consisting of tab(col3, col1, col2) or tab(col1, col3, col2), because col3 is not located at the back of the column in the GROUP BY clause.

You can use the index if the column condition is a constant although the column consisting of the index doesn't exist in the GROUP BY clause.

SELECT *
FROM tab
WHERE col2=val
GROUP BY col1,col3

If there is any index that consists of tab(col1, col2, col3) in the above example, use the index for optimizing GROUP BY.

Row sorting by GROUP BY is not required, because you can get the result as the requested order on the index scan.

If the index consisting of the GROUP BY column and the first column of the index is NOT NULL, even though there is no WHERE clause, the GROUP BY optimization will be applied.

GROUP BY optimization is applied only when MIN () or MAX () are used in an aggregate function, and to use the two aggregate functions together, an identical column must be used.

CREATE INDEX i_T_a_b_c ON T(a, b, c);
SELECT a, MIN(b), c, MAX(b) FROM T WHERE a > 18 GROUP BY a, b;

Example

CREATE TABLE tab (i INT, j INT, k INT);
CREATE INDEX i_tab_j_k ON tab (j, k);
INSERT INTO tab VALUES (1,2,3),(6,4,2),(3,4,1),(5,2,1),(1,5,5),(2,6,6),(3,5,4);

The following example shows that indexes consisting of tab(j,k) are used and no separate sorting process is required because GROUP BY is executed by j and k columns.

SELECT i,j,k
FROM tab
WHERE j > 0
GROUP BY j,k;

--  the  selection from the query plan dump shows that the index i_tab_j_k was used and sorting was not necessary
--  (/* ---> skip GROUP BY */)

Query plan:
iscan
    class: tab node[0]
    index: i_tab_j_k term[0]
    sort:  2 asc, 3 asc
    cost:  1 card 0

Query stmt:
select tab.i, tab.j, tab.k from tab tab where ((tab.j> ?:0 )) group by tab.j, tab.k
/* ---> skip GROUP BY */
            i            j            k
            5            2            1
            1            2            3
            3            4            1
            6            4            2
            3            5            4
            1            5            5
            2            6            6

The following example shows that an index consisting of tab(j,k) is used and no separate sorting process is required while GROUP BY is executed by j and k columns, no condition exists for j, and j column has NOT NULL attribute.

ALTER TABLE tab CHANGE COLUMN j j INT NOT NULL;

SELECT *
FROM tab
GROUP BY j,k;

--  the  selection from the query plan dump shows that the index i_tab_j_k was used (since j has the NOT NULL constraint )
--  and sorting was not necessary (/* ---> skip GROUP BY */)
Query plan:
iscan
    class: tab node[0]
    index: i_tab_j_k
    sort:  2 asc, 3 asc
    cost:  1 card 0

Query stmt: select tab.i, tab.j, tab.k from tab tab group by tab.j, tab.k
/* ---> skip GROUP BY */
=== <Result of SELECT Command in Line 1> ===
            i            j            k
=======================================
            5            2            1
            1            2            3
            3            4            1
            6            4            2
            3            5            4
            1            5            5
            2            6            6

Multiple Key Ranges Optimization¶

Optimizing the LIMIT clause is crucial for performance because the most queries have limit filter. A representative optimization of this case is Multiple Key Ranges Optimization.

Multiple Key Ranges Optimization generate the query result with Top N Sorting to scan only some key ranges in an index rather than doing a full index scan. Top N Sorting always keeps the best N tuples sorted rather than selecting all tuples and then sorting. Therefore, it shows the outstanding performance.

For example, when you search only the recent 10 posts which your friends wrote, CUBRID which applied Multiple KEY Ranges Optimization finds the result not by sorting after finding all your friends' posts, but by scanning the index which keeps the recent 10 sorted posts of each friends.

An example of Multiple Key Ranges Optimization is as follows.

CREATE TABLE t (a int, b int);
CREATE INDEX i_t_a_b ON t (a,b);

-- Multiple key range optimization
SELECT *
FROM t
WHERE a IN (1,2,3)
ORDER BY b
LIMIT 2;

Query plan:
iscan
class: t node[0]
index: i_t_a_b term[0] (covers) (multi_range_opt)
sort: 1 asc, 2 asc
cost: 1 card 0

On a single table, multiple key range optimization can be applied if below conditions are satisfied.

SELECT /*+ hints */ …
FROM table
WHERE col_1 = ? AND col_2 = ? AND … AND col(j-1) = ?
AND col_(j) IN (?, ?, … )
AND col_(j+1) = ? AND … AND col_(p-1) = ?
AND key_filter_terms
ORDER BY col_(p) [ASC|DESC], col_(p+1) [ASC|DESC],… col_(p+k-1) [ASC|DESC]
FOR orderbynum_pred | LIMIT n;

Firstly, if orderbynum_pred condition is specified, it should be valid. And upper limit(n) for ORDERBY_NUM or LIMIT should be less than or equal to the value of multi_range_optimization_limit system parameter.

And you need the proper index to the multiple key range optimization, this index should cover all k columns specified in the ORDER BY clause. In other words, this index should include all k columns specified in the ORDER BY clause and the sorting order should be the same as the columns' order. Also this index should include all columns used in WHERE clause.

Among columns that comprise the index,

• Columns in front of range condition(e.g. IN condition) are represented as equivalent condition(=).
• Only one column with range condition exists.
• Columns after range condition exist as key filters.
• There should be no data filtering condition. In other words, the index should include all columns used in WHERE clause.
• There should be no data filtering condition. In other words, the index should include all columns used in WHERE clause.
• Columns after the key filter exist in ORDER BY clause.
• Columns of key filter condition always should not the column of ORDER BY clause.
• If key filter condition with correlated subquery exists, related columns to this should be included into WHERE clause with no range condition.

On the below example, Multiple Key Ranges Optimization can be applied.

CREATE TABLE t (a INT, b INT, c INT, d INT, e INT);
CREATE INDEX i_t_a_b ON t (a,b,c,d,e);

SELECT *
FROM t
WHERE a = 1 AND b = 3 AND c IN (1,2,3) AND d = 3
ORDER BY e
LIMIT 2;

Queries with multiple joined tables can also support Multiple Key Ranges Optimization:

SELECT /*+ hints */ ...
FROM table_1, table_2, ... table_(sort), ...
WHERE col_1 = ? AND col_2 = ? AND ...
AND col_(j) IN (?, ?, ... )
AND col_(j+1) = ? AND ... AND col_(p-1) = ?
AND key_filter_terms
AND join_terms
ORDER BY col_(p) [ASC|DESC], col_(p+1) [ASC|DESC], ... col_(p+k-1) [ASC|DESC]
FOR ordbynum_pred | LIMIT n;

If queries with multiple joined tables can support Multiple Key Ranges Optimization, below conditions should be satisfied:

• Columns in ORDER BY clause only exist on one table, and this table should satisfy all required conditions by Multiple Key Ranges Optimization on a single table query. Let the "sort table" be the table that contains all sorting columns.
• All columns of "sort table" specified in a JOIN condition between "sort table" and "outer tables" should be included on an index. In other words, there should be no data filtering condition.
• All columns of "sort table" specified in a JOIN condition between "sort table" and "outer tables" should be included on the WHERE clause with no range condition.

Index Skip Scan¶

Index Skip Scan (also known as ISS) is an optimization method that allows ignoring the first column of an index when the first column of the index is not included in the condition but the following column is included in the condition (in most cases, =). Generally, ISS should consider several columns (C1, C2, ..., Cn). Here, a query has the conditions for the consecutive columns and the conditions are started from the second column (C2) of the index.

INDEX (C1, C2, ..., Cn);

SELECT ... WHERE C2 = x and C3 = y and ... and Cp = z; -- p <= n
SELECT ... WHERE C2 < x and C3 >= y and ... and Cp BETWEEN (z and w); -- other conditions than equal

The query optimizer eventually determines whether ISS is the most optimum access method based on the cost. ISS is applied under very specific situations, such as when the first column of an index has a very small number of DISTINCT values compared to the number of records. In this case, ISS provides higher performance compared to Index Full Scan. For example, when the first column of index columns has very low cardinality, such as the value of men/women or millions of records with the value of 1~100, it may be inefficient to perform index scan by using the first column value. So ISS is useful in this case.

ISS skips reading most of the index pages in the disk and uses range search which is dynamically readjusted. Generally, ISS can be applied to a specific scenario when the number of DISTINCT values in the first column is very small. If ISS is applied to this case, ISS provides significantly higher performance than the index full scan. However, it means improper index creation that ISS is applied to a lot queries. So DBA should consider whether readjusting the indexes or not.

CREATE TABLE t (name string, gender char (1), birthday datetime);

CREATE INDEX idx_t_gen_name on t (gender, name);
-- Note that gender can only have 2 values, 'M' and 'F' (low cardinality)

-- this would qualify to use Index Skip Scanning:
SELECT *
FROM t
WHERE name = 'SMITH';

ISS is not applied in the following cases:

• Filtered index
• The first column of an index is a range filter or key filter
• Hierarchical query
• Aggregate function included