3. Elements of SQL Statements : SQL Functions : Analytical Functions
 
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Analytical Functions
Analytical functions compute an aggregate value based on a group of rows, and can return multiple rows for each group. Analytical functions can be used to calculate percentages or top-N results in a group.
Analytical functions can appear only in the select list of a query or in the ORDER BY clause. They cannot appear in WHERE, ON, HAVING, or GROUP BY clauses. Analytical functions can appear in the select lists of views and derived tables.
Analytical functions are window functions, and thus require an OVER clause.
Note:  The ORDER BY clause within the OVER clause supports the NULLS FIRST / NULLS LAST syntax. The default is NULLS LAST.
DENSE_RANK
DENSE_RANK()
Returns the ordinal position of each result row within a partition, based on the sequence defined by the ordering definition for the window. Rows with the same values of their sort specification have the same RANK() value and result in no gaps in the list of ranks. For example: 1, 2, 2, 3, 4, 4, 4, 5.
The following query ranks each employee in a department based on his salary. When two employees have the same salary they are assigned the same rank. When multiple rows have the same rank, the next rank in the sequence is consecutive.
SELECT empno, deptno, sal,
       DENSE_RANK() OVER (PARTITION BY deptno ORDER BY sal DESC) AS rank
FROM   emp;
 
     EMPNO     DEPTNO        SAL       RANK
----------  --------- ---------- ----------
       839        100       4900          1
       782        100       2350          2
       934        100       1200          3
       788        200       2900          1
       902        200       2900          1
       566        200       2875          2
       876        200       1000          3
       369        200        700          4
       900        300       2750          1
       654        300       1500          2
       521        300       1400          3
       844        300       1150          4
       499        300       1150          4
       698        300        850          5
The following query uses the DENSE_RANK function and then gets only the rows ranked 1 from each group. You must provide a correlation name (in this case, x) for the subquery:
SELECT fname, address FROM (SELECT fname, address,
       DENSE_RANK() OVER (PARTITION BY fname ORDER BY timestamp DESC) AS rank
FROM tab1) x WHERE rank = 1;
 
     fname                address 
---------- ------------‑‑‑‑‑‑‑‑‑-
      Mary   1600 Pennsylvania Av
FIRST_VALUE() OVER() and LAST_VALUE() OVER()
FIRST_VALUE (scalar_value_expression) [null_spec] OVER([partition_by_clause] order_by_clause [frame_spec])
LAST_VALUE (scalar_value_expression) [null_spec] OVER([partition_by_clause] order_by_clause frame_spec)
Produces one row per input row. The same value is returned for every row in the partition, or if there is no partition_by_clause, every row in the result.
where:
scalar_value_expr
Specifies any scalar expression that can appear in the select list of a query. Can contain constants, row values, operators, scalar functions, and scalar subqueries.
null_spec
Indicates whether to include null values in the selection of a first_value or last_value. Valid values are:
RESPECT NULLS
(Default) Uses the expression value in the first or last row.
IGNORE NULLS
Uses the first or last non-null expression value.
OVER ([partition_by_clause] order_by_clause  frame_spec)
Defines the window as described in Window Function Syntax.
For FIRST_VALUE a frame specification is required if using IGNORE NULLS and must be ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING.
For LAST_VALUE a frame specification is required and must be ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING.
The following query ranks each employee in a department based on his salary:
SELECT empno, deptno, sal,
FIRST_VALUE(empno) OVER (PARTITION BY deptno ORDER BY sal DESC)
FROM emp;
 
EMPNO      DEPTNO     SAL        FIRST_VALUE
---------- ---------- ---------- ----------
       839        100       4900        839
       782        100       2350        839
       934        100       1200        839
       788        200       2900        788
       902        200       2900        788
       566        200       2875        788
       876        200       1000        788
       369        200        700        788
       900        300       2750        900
       654        300       1500        900
       521        300       1400        900
       844        300       1150        900
       499        300       1150        900
       698        300        850        900
LAG and LEAD
LAG | LEAD (scalar_expression [,offset] [,default]) [RESPECT NULLS | IGNORE NULLS]
Returns a scalar column value from a row before (LAG) or after (LEAD) the current row. Use LAG to compare values in the current row with values in a previous row. Use LEAD to compare values in the current row with values in a following row.
LAG and LEAD are useful for comparing values across multiple rows—for example, across time periods.
where:
scalar_expression
Is an expression that returns a single value. The expression can be a constant, row value, operator, scalar function, and scalar subquery.
offset
Specifies the number of rows of lag or lead from the current row. Must be an expression that resolves to a positive integer. Default is 1.
default
Returns the specified value if no lagging or leading row is present (for example, lag of the first value in an ordered set). Default is NULL.
RESPECT NULLS | IGNORE NULLS
Indicates whether to include null values in the selection of a lag or lead value. Default is RESPECT NULLS.
IGNORE NULLS and offset N returns the N-th previous/following not-NULL value.
RESPECT NULLS and offset N returns the N-th previous/following value, counting NULL values.
The following query shows the date, the weather, and the previous day's weather:
SELECT wdate, forecast, LAG(forecast) OVER(ORDER BY wdate) AS lag
FROM weather ORDER BY wdate;
 
wdate         forecast      lag
---------------------------------
2012-06-12    overcast      NULL
2012-06-13    sunny         overcast
2012-06-14    rain          sunny
 
The following query finds the salary of each employee in department 300 and lists the next higher salary:
SELECT deptno, empno, sal,
   LEAD(sal) OVER(ORDER BY sal) AS next_sal
FROM salary WHERE deptno=300;
 
deptno   empno      sal   next_sal
----------------------------------
   300     698     1150       1150
   300     844     1150       1450
   300     499     1450       1500
   300     521     1500       2750
   300     654     2750 
   300     900 
The following example demonstrates the use of IGNORE NULLS:
lead_table(c1 INT , c2 INT , c3 INT);
INSERT INTO lead_table VALUES (1,10,1), (2, 20,2), (NULL, 30,1), (NULL,40,2), (5,50,1);
 
   SELECT
       c1, c2, c3,
       LEAD(c1             , 1,100) OVER (ORDER BY c2) AS lead1,
       LEAD(c1 IGNORE NULLS, 1,200) OVER (ORDER BY c2) AS lead1ign,
       LAG (c1             , 2,300) OVER (ORDER BY c2) AS lag2,
       LAG (c1 IGNORE NULLS, 2,400) OVER (ORDER BY c2) AS lag2ign
   FROM lead_table;
 
   c1     c2    c3   lead1  lead1ign   lag2    lag2ign
------  ----    --   -----  --------   -----   --------
    1      10    1       2         2    300        400
    2      20    2    NULL         5    300        400 
 NULL      30    1    NULL         5      1          1 
 NULL      40    2       5         5      2          1 
    5      50    1     100       200   NULL          1 
Note the difference in results between the lag2 and lag2ign columns.
For the fourth row, for RESPECT NULLS the value two rows above is 2.
However, for IGNORE NULLS the second non-null value above is 1.
   SELECT
   c1, c2, c3,
   LEAD(c1             , 1,100) OVER (PARTITION BY c3 ORDER BY c2) AS lead1,
   LEAD(c1 IGNORE NULLS, 1,200) OVER (PARTITION BY c3 ORDER BY c2) AS lead1ign,
   LAG (c1             , 1,300) OVER (PARTITION BY c3 ORDER BY c2) AS lag1,
   LAG (c1 IGNORE NULLS, 1,400) OVER (PARTITION BY c3 ORDER BY c2) AS lag1ign
   FROM lead_table;
 
   c1   c2   c3   lead1   lead1ign   lag1    lag1ign 
 ----   ---  ---  -----  ---------   ----    -------
    1   10    1    NULL          5    300        400
 NULL   30    1       5          5      1          1
    5   50    1     100        200   NULL          1
    2   20    2    NULL        200    300        400
 NULL   40    2     100        200      2          2
NTILE
NTILE(n)
Divides the rows in an ordered partition into n groups. The groups are numbered, starting at one. For each row, NTILE returns the number of the group to which the row belongs.
NTILE can be used, for example, to see what quartile, decile, or percentile a row is in.
The following query divides the employees in Department 400 into 4 groups by salary:
SELECT Department_ID, Employee_ID, Salary, NTILE(4)
OVER (PARTITION BY Department_ID ORDER BY Salary DESC) AS Quartile
FROM employees WHERE Department_ID = 400;
 
Department_ID    Employee_ID    Salary    Quartile
------------- -------------- --------- -----------
          400             50      9000           1
          400             48      8000           1
          400             51      7500           1
          400             54      7000           1
          400             53      6500           2
          400             47      6000           2
          400             44      5000           2
          400             46      4500           2
          400             52      4300           3
          400             45      4000           3
          400             43      3500           3
          400             42      3000           4
          400             41      3000           4
          400             49      2800           4
When the number of rows is not divisible by n, the later rows will have the smaller number of rows, so the first and second quartiles have 4 rows whereas the third and fourth have only 3.
PERCENT_RANK
PERCENT_RANK()
Calculates the relative rank of a row within a group of rows. PERCENT_RANK returns a number between 0 and 1, which represents the percentage of rows in the group that are less than the current row. If a partition has exactly one row, its percent_rank() is 0. Percent_rank() for the highest value in the group will always be 1.
Use this function to determine the relative standing of a value within a result set.
The following query calculates, for each employee, the percent rank of the employee's salary in the department:
SELECT deptno, empno, sal,
PERCENT_RANK() OVER (PARTITION BY deptno ORDER BY sal DESC) AS pr
FROM emp
ORDER BY deptno, pr;
 
       DEPTNO         EMPNO       SAL         PR
------------- ------------- ------------ ----------
          100           840         4400      0.000
 
          300           900         2750      0.000
          300           654         1500      0.200
          300           521         1400      0.400
          300           844         1150      0.600
          300           499         1150      0.600
          300           698          850      1.000
 
          400           789         6500      0.000
 
          500           299         3900      0.000
          500           473         2200      0.333
          500           371         2200      0.333
          500           900         2100      1.000
 
          800             5        10500      0.000
          800           854         6200      1.000
RANK
RANK()
Returns the ordinal position of each result row within a partition, based on the sequence defined by the ordering definition for the window. Rows with the same values of their sort specification have the same RANK() value and result in gaps in the list of ranks. For example: 1, 2, 2, 4, 5, 5, 5, 8.
The following query ranks each employee in a department based on his salary. When two employees have the same salary they are assigned the same rank. When multiple rows have the same rank, the next rank in the sequence is not consecutive.
SELECT empno, deptno, sal,
       RANK() OVER (PARTITION BY deptno ORDER BY sal DESC) AS rank
FROM   emp;
 
     EMPNO     DEPTNO        SAL       RANK
---------- ---------- ---------- ----------
       839        100       4900          1
       782        100       2350          2
       934        100       1200          3
       788        200       2900          1
       902        200       2900          1
       566        200       2875          3
       876        200       1000          4
       369        200        700          5
       698        300       2750          1
       499        300       1500          2
       844        300       1400          3
       521        300       1150          4
       654        300       1150          4
       900        300        850          6
ROW_NUMBER
ROW_NUMBER()
Returns the ordinal position of each result row within a partition, based on the sequence defined by the ordering definition for the window. Rows with the same values in their sort specification are ordered arbitrarily. For example: 1, 2, 3, 4, 5.
The following query assigns a consecutive number to each row. Rows with matching numbers are ordered arbitrarily.
SELECT empno, deptno, sal,
       ROW_NUMBER() OVER (PARTITION BY deptno ORDER BY sal) AS rownum
FROM emp;
 
     EMPNO     DEPTNO        SAL     ROWNUM
---------- ---------- ---------- ----------
       934        100       1200          1
       782        100       2350          2
       839        100       4900          3
       369        200        700          1
       876        200       1000          2
       566        200       2875          3
       788        200       2900          4
       902        200       2900          5
       900        300        850          1
       654        300       1150          2
       521        300       1150          3
       844        300       1400          4
       499        300       1500          5
       698        300       2750          6