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Analytic functions by Example

Shouvik Basu's picture

This article provides a clear, thorough concept of analytic functions and its various options by a series of simple yet concept building examples. The article is intended for SQL coders, who for might be not be using analytic functions due to unfamiliarity with its cryptic syntax or uncertainty about its logic of operation. Often I see that people tend to reinvent the feature provided by analytic functions by native join and sub-query SQL. This article assumes familiarity with basic Oracle SQL, sub-query, join and group function from the reader. Based on that familiarity, it builds the concept of analytic functions through a series of examples.

It is true that whatever an analytic function does can be done by native SQL, with join and sub-queries. But the same routine done by analytic function is always faster, or at least as fast, when compared to native SQL. Moreover, I am not considering here the amount of time that is spent in coding the native SQLs, testing, debugging and tuning them.

The general syntax of analytic function is:

Function(arg1,..., argn) OVER ( [PARTITION BY <...>] [ORDER BY <....>] [<window_clause>] )

<window_clause> is like "ROW <?>" or "RANK <?>"
All the keywords will be dealt in details as we walk through the examples. The script for creating the schema (SCOTT) on which the example queries of this article are run can be obtained in ORACLE_HOME/sqlplus/demo/demobld.sql of any standard Oracle installation.

How are analytic functions different from group or aggregate functions?

SELECT deptno,
COUNT(*) DEPT_COUNT
FROM emp
WHERE deptno IN (20, 30)
GROUP BY deptno;

DEPTNO                 DEPT_COUNT             
---------------------- ---------------------- 
20                     5                      
30                     6                      

2 rows selected
Query-1

Consider the Query-1 and its result. Query-1 returns departments and their employee count. Most importantly it groups the records into departments in accordance with the GROUP BY clause. As such any non-"group by" column is not allowed in the select clause.

SELECT empno, deptno, 
COUNT(*) OVER (PARTITION BY 
deptno) DEPT_COUNT
FROM emp
WHERE deptno IN (20, 30);

     EMPNO     DEPTNO DEPT_COUNT
---------- ---------- ----------
      7369         20          5
      7566         20          5
      7788         20          5
      7902         20          5
      7876         20          5
      7499         30          6
      7900         30          6
      7844         30          6
      7698         30          6
      7654         30          6
      7521         30          6

11 rows selected.
Query-2

Now consider the analytic function query (Query-2) and its result. Note the repeating values of DEPT_COUNT column.

This brings out the main difference between aggregate and analytic functions. Though analytic functions give aggregate result they do not group the result set. They return the group value multiple times with each record. As such any other non-"group by" column or expression can be present in the select clause, for example, the column EMPNO in Query-2.

Analytic functions are computed after all joins, WHERE clause, GROUP BY and HAVING are computed on the query. The main ORDER BY clause of the query operates after the analytic functions. So analytic functions can only appear in the select list and in the main ORDER BY clause of the query.

In absence of any PARTITION or <window_clause> inside the OVER( ) portion, the function acts on entire record set returned by the where clause. Note the results of Query-3 and compare it with the result of aggregate function query Query-4.

SELECT empno, deptno, 
COUNT(*) OVER ( ) CNT
FROM emp
WHERE deptno IN (10, 20)
ORDER BY 2, 1;

     EMPNO     DEPTNO        CNT
---------- ---------- ----------
      7782         10          8
      7839         10          8
      7934         10          8
      7369         20          8
      7566         20          8
      7788         20          8
      7876         20          8
      7902         20          8
Query-3

SELECT COUNT(*) FROM emp
WHERE deptno IN (10, 20);

  COUNT(*)
----------
         8
Query-4

How to break the result set in groups or partitions?

It might be obvious from the previous example that the clause PARTITION BY is used to break the result set into groups. PARTITION BY can take any non-analytic SQL expression.

Some functions support the <window_clause> inside the partition to further limit the records they act on. In the absence of any <window_clause> analytic functions are computed on all the records of the partition clause.

The functions SUM, COUNT, AVG, MIN, MAX are the common analytic functions the result of which does not depend on the order of the records.

Functions like LEAD, LAG, RANK, DENSE_RANK, ROW_NUMBER, FIRST, FIRST VALUE, LAST, LAST VALUE depends on order of records. In the next example we will see how to specify that.

How to specify the order of the records in the partition?

The answer is simple, by the "ORDER BY" clause inside the OVER( ) clause. This is different from the ORDER BY clause of the main query which comes after WHERE. In this section we go ahead and introduce each of the very useful functions LEAD, LAG, RANK, DENSE_RANK, ROW_NUMBER, FIRST, FIRST VALUE, LAST, LAST VALUE and show how each depend on the order of the record.

The general syntax of specifying the ORDER BY clause in analytic function is:

ORDER BY <sql_expr> [ASC or DESC] NULLS [FIRST or LAST]

The syntax is self-explanatory.

ROW_NUMBER, RANK and DENSE_RANK

All the above three functions assign integer values to the rows depending on their order. That is the reason of clubbing them together.

ROW_NUMBER( ) gives a running serial number to a partition of records. It is very useful in reporting, especially in places where different partitions have their own serial numbers. In Query-5, the function ROW_NUMBER( ) is used to give separate sets of running serial to employees of departments 10 and 20 based on their HIREDATE.

SELECT empno, deptno, hiredate,
ROW_NUMBER( ) OVER (PARTITION BY
deptno ORDER BY hiredate
NULLS LAST) SRLNO
FROM emp
WHERE deptno IN (10, 20)
ORDER BY deptno, SRLNO;

EMPNO  DEPTNO HIREDATE       SRLNO
------ ------- --------- ----------
  7782      10 09-JUN-81          1
  7839      10 17-NOV-81          2
  7934      10 23-JAN-82          3
  7369      20 17-DEC-80          1
  7566      20 02-APR-81          2
  7902      20 03-DEC-81          3
  7788      20 09-DEC-82          4
  7876      20 12-JAN-83          5

8 rows selected.
Query-5 (ROW_NUMBER example)

RANK and DENSE_RANK both provide rank to the records based on some column value or expression. In case of a tie of 2 records at position N, RANK declares 2 positions N and skips position N+1 and gives position N+2 to the next record. While DENSE_RANK declares 2 positions N but does not skip position N+1.

Query-6 shows the usage of both RANK and DENSE_RANK. For DEPTNO 20 there are two contenders for the first position (EMPNO 7788 and 7902). Both RANK and DENSE_RANK declares them as joint toppers. RANK skips the next value that is 2 and next employee EMPNO 7566 is given the position 3. For DENSE_RANK there are no such gaps.

SELECT empno, deptno, sal,
RANK() OVER (PARTITION BY deptno
ORDER BY sal DESC NULLS LAST) RANK,
DENSE_RANK() OVER (PARTITION BY
deptno ORDER BY sal DESC NULLS
LAST) DENSE_RANK
FROM emp
WHERE deptno IN (10, 20)
ORDER BY 2, RANK;

EMPNO  DEPTNO   SAL  RANK DENSE_RANK
------ ------- ----- ----- ----------
  7839      10  5000     1          1
  7782      10  2450     2          2
  7934      10  1300     3          3
  7788      20  3000     1          1
  7902      20  3000     1          1
  7566      20  2975     3          2
  7876      20  1100     4          3
  7369      20   800     5          4

8 rows selected.
Query-6 (RANK and DENSE_RANK example)

LEAD and LAG

LEAD has the ability to compute an expression on the next rows (rows which are going to come after the current row) and return the value to the current row. The general syntax of LEAD is shown below:

LEAD (<sql_expr>, <offset>, <default>) OVER (<analytic_clause>)

<sql_expr> is the expression to compute from the leading row.
<offset> is the index of the leading row relative to the current row.
<offset> is a positive integer with default 1.
<default> is the value to return if the <offset> points to a row outside the partition range.

The syntax of LAG is similar except that the offset for LAG goes into the previous rows.
Query-7 and its result show simple usage of LAG and LEAD function.

SELECT deptno, empno, sal,
LEAD(sal, 1, 0) OVER (PARTITION BY dept ORDER BY sal DESC NULLS LAST) NEXT_LOWER_SAL,
LAG(sal, 1, 0) OVER (PARTITION BY dept ORDER BY sal DESC NULLS LAST) PREV_HIGHER_SAL
FROM emp
WHERE deptno IN (10, 20)
ORDER BY deptno, sal DESC;

 DEPTNO  EMPNO   SAL NEXT_LOWER_SAL PREV_HIGHER_SAL
------- ------ ----- -------------- ---------------
     10   7839  5000           2450               0
     10   7782  2450           1300            5000
     10   7934  1300              0            2450
     20   7788  3000           3000               0
     20   7902  3000           2975            3000
     20   7566  2975           1100            3000
     20   7876  1100            800            2975
     20   7369   800              0            1100

8 rows selected.
Query-7 (LEAD and LAG)

FIRST VALUE and LAST VALUE function

The general syntax is:

FIRST_VALUE(<sql_expr>) OVER (<analytic_clause>)

The FIRST_VALUE analytic function picks the first record from the partition after doing the ORDER BY. The <sql_expr> is computed on the columns of this first record and results are returned. The LAST_VALUE function is used in similar context except that it acts on the last record of the partition.

-- How many days after the first hire of each department were the next
-- employees hired?

SELECT empno, deptno, hiredate ? FIRST_VALUE(hiredate)
OVER (PARTITION BY deptno ORDER BY hiredate) DAY_GAP
FROM emp
WHERE deptno IN (20, 30)
ORDER BY deptno, DAY_GAP;

     EMPNO     DEPTNO    DAY_GAP
---------- ---------- ----------
      7369         20          0
      7566         20        106
      7902         20        351
      7788         20        722
      7876         20        756
      7499         30          0
      7521         30          2
      7698         30         70
      7844         30        200
      7654         30        220
      7900         30        286

11 rows selected.
Query-8 (FIRST_VALUE)

FIRST and LAST function

The FIRST function (or more properly KEEP FIRST function) is used in a very special situation. Suppose we rank a group of record and found several records in the first rank. Now we want to apply an aggregate function on the records of the first rank. KEEP FIRST enables that.

The general syntax is:

Function( ) KEEP (DENSE_RANK FIRST ORDER BY <expr>) OVER (<partitioning_clause>)

Please note that FIRST and LAST are the only functions that deviate from the general syntax of analytic functions. They do not have the ORDER BY inside the OVER clause. Neither do they support any <window> clause. The ranking done in FIRST and LAST is always DENSE_RANK. The query below shows the usage of FIRST function. The LAST function is used in similar context to perform computations on last ranked records.

-- How each employee's salary compare with the average salary of the first
-- year hires of their department?

SELECT empno, deptno, TO_CHAR(hiredate,'YYYY') HIRE_YR, sal,
TRUNC(
AVG(sal) KEEP (DENSE_RANK FIRST
ORDER BY TO_CHAR(hiredate,'YYYY') )
OVER (PARTITION BY deptno)
     ) AVG_SAL_YR1_HIRE
FROM emp
WHERE deptno IN (20, 10)
ORDER BY deptno, empno, HIRE_YR;

     EMPNO     DEPTNO HIRE        SAL AVG_SAL_YR1_HIRE
---------- ---------- ---- ---------- ----------------
      7782         10 1981       2450             3725
      7839         10 1981       5000             3725
      7934         10 1982       1300             3725
      7369         20 1980        800              800
      7566         20 1981       2975              800
      7788         20 1982       3000              800
      7876         20 1983       1100              800
      7902         20 1981       3000              800

8 rows selected.
Query-9 (KEEP FIRST)

How to specify the Window clause (ROW type or RANGE type windows)?

Some analytic functions (AVG, COUNT, FIRST_VALUE, LAST_VALUE, MAX, MIN and SUM among the ones we discussed) can take a window clause to further sub-partition the result and apply the analytic function. An important feature of the windowing clause is that it is dynamic in nature.

The general syntax of the <window_clause> is

[ROW or RANGE] BETWEEN <start_expr> AND <end_expr>

<start_expr> can be any one of the following

  1. UNBOUNDED PECEDING
  2. CURRENT ROW
  3. <sql_expr> PRECEDING or FOLLOWING.

    <end_expr> can be any one of the following
  1. UNBOUNDED FOLLOWING or
  2. CURRENT ROW or
  3. <sql_expr> PRECEDING or FOLLOWING.

For ROW type windows the definition is in terms of row numbers before or after the current row. So for ROW type windows <sql_expr> must evaluate to a positive integer.

For RANGE type windows the definition is in terms of values before or after the current ORDER. We will take this up in details latter.

The ROW or RANGE window cannot appear together in one OVER clause. The window clause is defined in terms of the current row. But may or may not include the current row. The start point of the window and the end point of the window can finish before the current row or after the current row. Only start point cannot come after the end point of the window. In case any point of the window is undefined the default is UNBOUNDED PRECEDING for <start_expr> and UNBOUNDED FOLLOWING for <end_expr>.

If the end point is the current row, syntax only in terms of the start point can be can be
[ROW or RANGE] [<start_expr> PRECEDING or UNBOUNDED PRECEDING ]

[ROW or RANGE] CURRENT ROW is also allowed but this is redundant. In this case the function behaves as a single-row function and acts only on the current row.

ROW Type Windows

For analytic functions with ROW type windows, the general syntax is:

Function( ) OVER (PARTITIN BY <expr1> ORDER BY <expr2,..> ROWS BETWEEN <start_expr> AND <end_expr>)
or
Function( ) OVER (PARTITON BY <expr1> ORDER BY <expr2,..> ROWS [<start_expr> PRECEDING or UNBOUNDED PRECEDING]

For ROW type windows the windowing clause is in terms of record numbers.

The query Query-10 has no apparent real life description (except column FROM_PU_C) but the various windowing clause are illustrated by a COUNT(*) function. The count simply shows the number of rows inside the window definition. Note the build up of the count for each column for the YEAR 1981.

The column FROM_P3_TO_F1 shows an example where start point of the window is before the current row and end point of the window is after current row. This is a 5 row window; it shows values less than 5 during the beginning and end.

-- The query below has no apparent real life description (except 
-- column FROM_PU_C) but is remarkable in illustrating the various windowing
-- clause by a COUNT(*) function.
 
SELECT empno, deptno, TO_CHAR(hiredate, 'YYYY') YEAR,
COUNT(*) OVER (PARTITION BY TO_CHAR(hiredate, 'YYYY')
ORDER BY hiredate ROWS BETWEEN 3 PRECEDING AND 1 FOLLOWING) FROM_P3_TO_F1,
COUNT(*) OVER (PARTITION BY TO_CHAR(hiredate, 'YYYY')
ORDER BY hiredate ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) FROM_PU_TO_C,
COUNT(*) OVER (PARTITION BY TO_CHAR(hiredate, 'YYYY')
ORDER BY hiredate ROWS BETWEEN 3 PRECEDING AND 1 PRECEDING) FROM_P2_TO_P1,
COUNT(*) OVER (PARTITION BY TO_CHAR(hiredate, 'YYYY')
ORDER BY hiredate ROWS BETWEEN 1 FOLLOWING AND 3 FOLLOWING) FROM_F1_TO_F3
FROM emp
ORDEDR BY hiredate

 EMPNO  DEPTNO YEAR FROM_P3_TO_F1 FROM_PU_TO_C FROM_P2_TO_P1 FROM_F1_TO_F3
------ ------- ---- ------------- ------------ ------------- -------------
  7369      20 1980             1            1             0             0
  <font bgcolor=yellow>7499      30 1981             2            1             0             3
  7521      30 1981             3            2             1             3
  7566      20 1981             4            3             2             3
  7698      30 1981             5            4             3             3
  7782      10 1981             5            5             3             3
  7844      30 1981             5            6             3             3
  7654      30 1981             5            7             3             3
  7839      10 1981             5            8             3             2
  7900      30 1981             5            9             3             1
  7902      20 1981             4           10             3             0</font>
  7934      10 1982             2            1             0             1
  7788      20 1982             2            2             1             0
  7876      20 1983             1            1             0             0

14 rows selected.
Query-10 (ROW type windowing example)

The column FROM_PU_TO_CURR shows an example where start point of the window is before the current row and end point of the window is the current row. This column only has some real world significance. It can be thought of as the yearly employee build-up of the organization as each employee is getting hired.

The column FROM_P2_TO_P1 shows an example where start point of the window is before the current row and end point of the window is before the current row. This is a 3 row window and the count remains constant after it has got 3 previous rows.

The column FROM_F1_TO_F3 shows an example where start point of the window is after the current row and end point of the window is after the current row. This is a reverse of the previous column. Note how the count declines during the end.

RANGE Windows

For RANGE windows the general syntax is same as that of ROW:

Function( ) OVER (PARTITION BY <expr1> ORDER BY <expr2> RANGE BETWEEN <start_expr> AND <end_expr>)
or
Function( ) OVER (PARTITION BY <expr1> ORDER BY <expr2> RANGE [<start_expr> PRECEDING or UNBOUNDED PRECEDING]

For <start_expr> or <end_expr> we can use UNBOUNDED PECEDING, CURRENT ROW or <sql_expr> PRECEDING or FOLLOWING. However for RANGE type windows <sql_expr> must evaluate to value compatible with ORDER BY expression <expr1>.

<sql_expr> is a logical offset. It must be a constant or expression that evaluates to a positive numeric value or an interval literal. Only one ORDER BY expression is allowed.

If <sql_expr> evaluates to a numeric value, then the ORDER BY expr must be a NUMBER or DATE datatype. If <sql_expr> evaluates to an interval value, then the ORDER BY expr must be a DATE datatype.

Note the example (Query-11) below which uses RANGE windowing. The important thing here is that the size of the window in terms of the number of records can vary.

-- For each employee give the count of employees getting half more that their 
-- salary and also the count of employees in the departments 20 and 30 getting half 
-- less than their salary.
 
SELECT deptno, empno, sal,
Count(*) OVER (PARTITION BY deptno ORDER BY sal RANGE
BETWEEN UNBOUNDED PRECEDING AND (sal/2) PRECEDING) CNT_LT_HALF,
COUNT(*) OVER (PARTITION BY deptno ORDER BY sal RANGE
BETWEEN (sal/2) FOLLOWING AND UNBOUNDED FOLLOWING) CNT_MT_HALF
FROM emp
WHERE deptno IN (20, 30)
ORDER BY deptno, sal

 DEPTNO  EMPNO   SAL CNT_LT_HALF CNT_MT_HALF
------- ------ ----- ----------- -----------
     20   7369   800           0           3
     20   7876  1100           0           3
     20   7566  2975           2           0
     20   7788  3000           2           0
     20   7902  3000           2           0
     30   7900   950           0           3
     30   7521  1250           0           1
     30   7654  1250           0           1
     30   7844  1500           0           1
     30   7499  1600           0           1
     30   7698  2850           3           0

11 rows selected.
Query-11 (RANGE type windowing example)

Order of computation and performance tips

Defining the PARTITOIN BY and ORDER BY clauses on indexed columns (ordered in accordance with the PARTITION CLAUSE and then the ORDER BY clause in analytic function) will provide optimum performance. For Query-5, for example, a composite index on (deptno, hiredate) columns will prove effective.

It is advisable to always use CBO for queries using analytic functions. The tables and indexes should be analyzed and optimizer mode should be CHOOSE.

Even in absence of indexes analytic functions provide acceptable performance but need to do sorting for computing partition and order by clause. If the query contains multiple analytic functions, sorting and partitioning on two different columns should be avoided if they are both not indexed.

Conclusion

The aim of this article is not to make the reader try analytic functions forcibly in every other complex SQL. It is meant for a SQL coder, who has been avoiding analytic functions till now, even in complex analytic queries and reinventing the same feature much painstakingly by native SQL and join query. Its job is done if such a person finds analytic functions clear, understandable and usable after going through the article, and starts using them.

Most of the examples that I have come across deal with simple dates. What about when you have a data set that contains records with timestamps and you would like to roll them up to the second and then look at a sliding window to find, say the busiest 5 minutes of the day? It is trivial to create the query to aggregate the data into per-second blocks but I cannot figure out the syntax to put a window around it.

Thanks.

useful topic

This is very useful topic,
But I have simple problem I can not solve,
I want the id(or any column) of the row before the current row?

Solution

Hi abuleen, try this :

select empno,ename,deptno,lag(empno,1,999999) over (order by empno nulls last) prev_id
from emp
order by empno

dynamic window range

Hi Stephen,

try this > > >

create table trt (timepoint timestamp,random_str varchar2(7));

insert into trt values(to_timestamp('16.09.2010 07:05:51:781000','DD.MM.YYYY HH24:MI:SS:FF6'),'piNX');
insert into trt values(to_timestamp('16.09.2010 07:09:11:453000','DD.MM.YYYY HH24:MI:SS:FF6'),'EKzU');
insert into trt values(to_timestamp('16.09.2010 07:09:16:515000','DD.MM.YYYY HH24:MI:SS:FF6'),'rnZg');
insert into trt values(to_timestamp('16.09.2010 07:09:18:890000','DD.MM.YYYY HH24:MI:SS:FF6'),'LFEy');
insert into trt values(to_timestamp('16.09.2010 07:09:24:187000','DD.MM.YYYY HH24:MI:SS:FF6'),'BNZf');
insert into trt values(to_timestamp('16.09.2010 07:09:26:937000','DD.MM.YYYY HH24:MI:SS:FF6'),'FXFD');
insert into trt values(to_timestamp('16.09.2010 07:09:29:140000','DD.MM.YYYY HH24:MI:SS:FF6'),'Esgz');
insert into trt values(to_timestamp('16.09.2010 07:09:30:921000','DD.MM.YYYY HH24:MI:SS:FF6'),'wolR');
insert into trt values(to_timestamp('16.09.2010 07:09:32:218000','DD.MM.YYYY HH24:MI:SS:FF6'),'AijN');
insert into trt values(to_timestamp('16.09.2010 07:09:33:500000','DD.MM.YYYY HH24:MI:SS:FF6'),'PUot');
insert into trt values(to_timestamp('16.09.2010 07:09:34:625000','DD.MM.YYYY HH24:MI:SS:FF6'),'nIUX');
insert into trt values(to_timestamp('16.09.2010 07:09:35:796000','DD.MM.YYYY HH24:MI:SS:FF6'),'DGTf');
insert into trt values(to_timestamp('16.09.2010 07:09:36:750000','DD.MM.YYYY HH24:MI:SS:FF6'),'eEYe');
insert into trt values(to_timestamp('16.09.2010 07:09:37:828000','DD.MM.YYYY HH24:MI:SS:FF6'),'mHYt');
insert into trt values(to_timestamp('16.09.2010 07:09:38:859000','DD.MM.YYYY HH24:MI:SS:FF6'),'buWA');
insert into trt values(to_timestamp('16.09.2010 07:09:39:968000','DD.MM.YYYY HH24:MI:SS:FF6'),'yllr');
insert into trt values(to_timestamp('16.09.2010 07:09:45:359000','DD.MM.YYYY HH24:MI:SS:FF6'),'WJua');
insert into trt values(to_timestamp('16.09.2010 07:09:48:328000','DD.MM.YYYY HH24:MI:SS:FF6'),'Zsrp');
insert into trt values(to_timestamp('16.09.2010 07:09:50:656000','DD.MM.YYYY HH24:MI:SS:FF6'),'WtDJ');
commit;

SELECT TO_CHAR(timepoint,'DD.MM.YYYY HH24:MI:SS.FF3') "Start_bussiest_5sec_interval"
FROM
  (SELECT timepoint,
    DENSE_RANK() over (order by forw_dens_per_5sec DESC,end_time_5sec-timepoint,timepoint) rank
  FROM
    (SELECT timepoint,
      COUNT(*) over (order by timepoint range BETWEEN CURRENT row AND interval '5' second following ) forw_dens_per_5sec,
      MAX(timepoint) over (order by timepoint range BETWEEN CURRENT row AND interval '5' second following ) end_time_5sec
    FROM trt
    )
  )
WHERE rank=1;

Regards

Veslar

Correction

The output of your query is: Start_bussiest_5sec_interval=
16.09.2010 07:09:35.796. But I guess this is not the starting of the busiest 5 sec interval. I guess it should be = 16.09.2010 07:09:30.921. If I am correct than your query should be modifed here:

DENSE_RANK() over (order by forw_dens_per_5sec DESC,end_time_5sec-timepoint DESC,timepoint) rank.

Regards.
Pakkia

Explanation

Try this and you'll see why it is so, as I wrote the first time > > >

SELECT *
FROM
(SELECT
DENSE_RANK() over (order by forw_dens_per_5sec DESC,end_time_5sec-timepoint,timepoint) rank,
s.*,
end_time_5sec-timepoint dff
FROM
(SELECT timepoint,
COUNT(*) over (order by timepoint range BETWEEN CURRENT row AND interval '5' second following ) forw_dens_per_5sec,
MAX(timepoint) over (order by timepoint range BETWEEN CURRENT row AND interval '5' second following ) end_time_5sec
FROM trt
) s
)ss
--WHERE rank=1
;

The density is 5 records per interval for both (my and your solution) but mine has minor diff between first member and last one (order by forw_dens_per_5sec DESC,end_time_5sec-timepoint,timepoint).

When I was stuck with the oracle documentation reading about analytic functions, being described highly formally, I got this
excellent article describing complex things in really simple terms with examples.

Hey, why don't u write a book on this.
This article is really cool.

I was stuck with some Oracle Analytical function and was looking for some help. Bumped across this article.

Really neat! Keep up the good work.

Hi Shouvik,

I was dusting off my OLAP stuff (been a while) seeking a solution to a data loading issue. Your article "Analytic functions by Example" helped me zero in on the solution.

Gratitude and a "Thousand At-A-Boys" to you.

Keep up the good work!

BG...

Excellent article. I personally learn best with simple examples to demonstrate potentially complex concepts ... and this article was perfect. Thanks.

Thanx a lot!! This doc really helped me a lot.
One can get a clear idea regarding analytical functions if he/she go thru this page once..
Usha

Excellent!! it is a great privilege to work with you.

-- How many days after the first hire of each department were the next employees hired?
SELECT empno, deptno, hiredate ? FIRST_VALUE(hiredate)
OVER (PARTITION BY deptno ORDER BY hiredate) DAY_GAP
FROM emp
WHERE deptno IN (20, 30)
ORDER BY deptno, DAY_GAP;

I think there is an error in this query. It does not return the same results as shown in the example.
Thanks in advance

correction

Quote:
A great article with everything put together about getting started with analytical functions.

Regarding correction:

Replace the '?' with '-'. I think that will give the difference in dates to calculate the days.

SELECT empno, deptno, hiredate - FIRST_VALUE(hiredate)
OVER (PARTITION BY deptno ORDER BY hiredate) DAY_GAP
FROM emp
WHERE deptno IN (20, 30)
ORDER BY deptno, DAY_GAP;

I was trying to use the dense_rank function to tune a query but really couldn't understand the Oracle doco - your page helped me make the breakthrough and my query runs instantly now whereas it took an hour before.

This is an excellent

This is an excellent treatment of analytic functions. Other analytic function articles just didn't cut it for me. After reading this, was able to quickly solve an SQL problem.

I've added your URL to our Business Unit's Web Site.

Thank you.

Really Enthralling

Hello,

What a presentation you have had in this web page. I appreciate your intuition and noble efforts. Looking forward to seeing your article on how to write well-tuned SQL.
May GOD bless you!!

Regards,
Arindam Mukherjee

Analytic Functions - Awesome article

Shouvik -

Like many other readers I am your real fan.

I have been looking to explore the analytic functions and this article with examples is just a great startup. I won't amaze to Google your name to find something rare gems about Oracle.

Keep up the great work!

Regards,
Prakash

Analytic Functions - Great

Shouvik,

This is one of the best article I have ever found to start up with Analytic Function.

I would say just keep it up and forward the same related articles.

Regards,
Ba

Very Great Effort - Add more here with time

This is a really great effort. It helped me a lot to clear my ambiguities. Please add more in it with the passage of time when you learns/experiences more about these functions.

Best Regards,
Aasif

execllent effort

This is a very good artical for the people who don't know how to use the function for analytical work.

awesome

awesome.
Thanks.

is this a bug?

create table emp (
empno varchar2(10),
deptno varchar2(10),
sal number(10)
)

insert into emp(empno,deptno,sal) values('1','10',101);
insert into emp(empno,deptno,sal) values('2','20',102);
insert into emp(empno,deptno,sal) values('3','20',103);
insert into emp(empno,deptno,sal) values('4','10',104);
insert into emp(empno,deptno,sal) values('5','30',105);
insert into emp(empno,deptno,sal) values('6','30',106);
insert into emp(empno,deptno,sal) values('7','30',107);
insert into emp(empno,deptno,sal) values('8','40',108);
insert into emp(empno,deptno,sal) values('9','30',109);
insert into emp(empno,deptno,sal) values('10','30',110);
insert into emp(empno,deptno,sal) values('11','30',100);

SELECT empno, deptno, sal,
last_value(sal)
OVER (PARTITION BY deptno order by sal desc) col1,
first_value(sal)
OVER (PARTITION BY deptno order by sal asc) col2,
first_value(sal)
OVER (PARTITION BY deptno order by sal desc) col3,
last_value(sal)
OVER (PARTITION BY deptno order by sal asc) col4
FROM emp

col2, col3 return what I expect.

I don't know why col1 and col4 return the these kinds of results.

Caveat with LAST_VALUE function (answering Kang's concern)

If anyone has Metalink Access, read Doc ID 696344.992.

Broadly speaking,
All analytic functions with ORDER BY operate on a default window - a subset of contiguous rows (according to the analytic ORDER BY clause) within the partition. The default windowing clause is "RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW". This affects the LAST_VALUE.

To get the results as you want you need to have.
(PARTITION BY deptno order by sal desc ROWS
BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING).

Hope this helps,
Shouvik Basu

Query -11 column CNT_MT_HALF

I am finding it hard to understand this can someone explain how its counting the last column
Based on what I understand "CNT_LT_HALF" divides the curron row sal and compares with precedding sal row values and that looks fine (not the count does not include the existing row in its count so its less that not less than equal to)
however when I try to apply the same for "CNT_MT_HALF" colum
say take current rows sal/2 eg. 800/2 = 400
now within dept = 20 if you compare this value with all the following sal then for the first row "CNT_LT_HALF" column should have a value of "4" and not "3". I ran the query in Oracle database and the query matches what the article output is ("3"). I know I am understanding it wrong, can someone explain

Way to do a running total by date.

I had a really slow sql query that had columns of effecivedate, amount and running total to date.
by using analytic function I was able to make a 90 second query a < 2 second query with following syntax.

SELECT effectivedate, amount, SUM(amount) OVER (PARTITION BY sysdate ORDER BY effectivedate)
FROM mytable
ORDER BY effectivedate DESC

I think this little snippet will be useful in many applications.
Truly enyoyed your article which gave me the idea to try it this way! Thanks so much!

Analytic Function

Am I doing something wrong?
I have table a and table b, the relation between them is one to many. In table a I have column tax, in table b I have unit price and qty, what I need to get by my query is avg tax, total (sum) tax and sum of price*qty. I have problem with avg_tax_chg and doc_$_tot when join tables. Can somebody help?
select a.doc_num, a.tax_chg,
avg(a.tax_chg) over ( ) avg_tax_chg,
sum(a.tax_chg) over (partition by a.ord_tp_cd,a.final_dt,a.stat_cd) tot_tax_chg,
sum(b.qty*b.unit_prc) over (partition by s.del_doc_num) doc_$_tot
from a, b
where a.doc_num = b.doc_num

Thanks

Recursive Sum

I want to recursevi summary by using analytic functions.
How can I do?
Thanks
For example:

A TABLE B TABLE SQL RESULT MUST BE
CODE CODE VALUES CODE SUM()
----- ------------- ------------------------
1 10000 200 1 600
10 10001 300 10 600
100 10010 100 100 600
1000 2000 200 1000 500
10000 10000 200
10001 10001 300
1001 1001 100
10010 10010 100
2 2 200
20 ....................
200
2000
....

This topic is however quite

This topic is however quite informative and constructive .
But there are some explainations in which still abscruity is there
So in the next topic please try to give the proper and cleare explaination

This Article is a Model Example of Analytical Writing Clarity

RE:"This topic is however quite"

Mr. Swainprafullaranjan, the only obscurity with the text on this page lay within the content of your comment. You provide incomplete sentences with the majority of words mis-spelled and absolutely no reference to what part of the article text that you find unclear or improper .

Had you written your thoughts truly as just a comment I would have refrained from mine. Since you felt obliged to lecture the author on improvement before writing further topics, I feel absolutely obliged to provide the same suggestion to you before critiquing any future article, post, or comment on this site.

Shouvic Basu effectively conveyed in his article, completely, what his topic statement intended- to provide ".. a clear, thorough concept of analytic functions and its various options by a series of simple yet concept building examples".

The flow of his presentation demonstrates a unique ability that I would coin as "precision in detail" of the subject matter. The quantity of detail and selection of organization in my opinion produced an article of many abilities - readability, learnability, capability... and enjoyability - a rare treat in reference material work.

I believe this view is the shared consensus amongst his readers. I can relate exactly to the response by Luke Curran: "Excellent article. I personally learn best with simple examples to demonstrate potentially complex concepts ... and this article was perfect. Thanks. "

Shouvic, I appreciate with great admiration your knowledge sharing and look forward to all future topics that you chose to cover. I have been working extensively with analytic functions on my current work projects and this article filled in a lot of background for me as well as new areas to further this study.

As an author of a chess novel myself, there were periods -painstaking times -in my writing that in retrospect had I posessed the same ability to convey detail as you with such precision, I believe that I would not be dyeing as much grey hair today!

Best Regards,
Harry

Thanks for a Very Useful Article

Hi,

I decided to learn analytical functions conceptually and luckily I got this article. Its very useful. The way of treating the subject is very effective. While reading, I tried them practically and now I am quite confident about their usage.

Thanks a lot for such a useful article!

Regards,
Dipali.

It is very helpful

It gives quick understanding of analytical function.
Great work.

Thanks for your article.

Awesome

Thanks a lot for such a useful article!

Very Good Overview

That was one of the best articles I've read in terms of how to explain an otherwise rather complicated topic.

Great work!!

YTD Calculation using analytical functions

Hi,

I am using Oracle Database 10gR1.
Please help me to write the following query.

I want to calculate ytd ( year to date calculation ), then i have to sum up monthly then sum up for yearly.
Eg : I have to calculate YTD as follows :

GL Curr Day Amount Month YTD
5805 45454 1-Jan 5.23 5.23 5.23
5805 45454 2-Jan -4.52 0.71 5.94
5805 45454 3-Jan 25.3 26.01 31.95
5805 45454 4-Jan 10.53 36.54 68.49
5805 45454 5-Jan -1.88 34.66 103.15

Here in this example, we have column names as gl, curr, day, amount, month, year ; taken from a 1 transaction table.
Now, To calculate ytd (year to-date calculation), i have to calculate month first and then year.

Step 1: Month wise summation :
I have to calculate sum for each day of the month.

From above example for month wise summation:
GL Curr Day Amount Month
5805 45454 1-Jan 5.23 5.23 ( sum of jan1 = 5.23 )
5805 45454 2-Jan -4.52 0.71 ( sum of jan2 = 5.23 + (-4.52) = 0.71 )
5805 45454 3-Jan 25.3 26.01 ( sum of jan3 = 0.71 + 25.3 = 26.01 )
5805 45454 4-Jan 10.53 36.54 ( sum of jan4 = 26.01 + 10.53 = 36.54 )
5805 45454 5-Jan -1.88 34.66 ( sum of jan4 = 36.54 + (-1.88) = 34.66 )

Step 2: Year wise summation : YTD Calculation :
We have done Step1 process to calculate this Step2 process, i.e., YTD Calculation.
So, we have to do Year wise summation with the Step1 month wise data ( with the above output date ).

Again, from above example for year wise summation:
GL Curr Day Amount Month YTD
5805 45454 1-Jan 5.23 5.23 5.23 ( ytd = 5.23 )
5805 45454 2-Jan -4.52 0.71 5.94 ( ytd = 5.23 + 0.71 = 5.94)
5805 45454 3-Jan 25.3 26.01 31.95 ( ytd = 5.94 + 26.01 = 31.95 )
5805 45454 4-Jan 10.53 36.54 68.49 ( ytd = 31.95 + 36.54 = 68.49 )
5805 45454 5-Jan -1.88 34.66 103.15 ( ytd = 68.49 + 34.66 = 103.15 )

So for year to-date calculation, we have to sum all the dates for a month and then sum all the month to get ytd.
How can i do this ytd using any analytical functions (i.e., i have to sum up for every row) ?

Thanks.

answer to tssr_2001

Hi,

select b.*,sum(month) over(partition by GL order by day) YEAR from (select gl,curr,day,amount,sum(amount) over(partition by GL order by day) month from temp1_p ) b.

This article is very nice. HatZ off to ORAFAQ!

Good explanation of Analytical Functions

Thanks for the details on Analytical Functions

Great teacher!

With 16 years of Oracle experience, I would just stay away from "partion by" and "over" clause, because I never really understood what it did. Your article is an eye opener for me. Yeah, promise I will buy your book if you write one!!

THANK YOU!!

Thanks for the Post

It's nice to see a detailed explanation about the Analytical Functions by considering our old "EMP" database as the source.

Good Article on analytical functions

Thank you for giving clear explanation about analytical functions. Very useful.

Very good article for analytical functions

Yesterday, I was dealing with some of the queries asked by my brother which I find very cumbersome with group by and long query.

I searched for analytical functions and believe me the content in your post is so easy to understand that I quickly solved his query and protected my image of knowing a bit more than him. :)

Anyway, I have suggested him to stick to your examples for basic understanding.

Thanks for very good post.

Thanks,
Prashant Gauda

wha are analytic functions different from group or aggregate fun

Fine answer!

Thank you very much...

I came across this article back in 2009 and printed it out (wanted to make sure that if the post was ever removed, I would still this vital information). I have referred back to these examples many times as a reference, they have helped me numerous times in solving a problem. Just wanted to let you know that an article you wrote in 2004 is still being used today. Thank you.

Kindly clear me about the rows and ranges, please?

Hi

Its very easy to follow your article.
But i am not aware about the concept ROWS AND RANGE.
In your example what does the "3 PRECEDING AND 1 FOLLOWING" refers and how it works in the below syntax ? I tried lot to get it, but in vain.
Kindly clear me about it. It will be very helpfull

SELECT empno, deptno, TO_CHAR(hiredate, 'YYYY') YEAR,
COUNT(*) OVER (PARTITION BY TO_CHAR(hiredate, 'YYYY')
ORDER BY hiredate ROWS BETWEEN 3 PRECEDING AND 1 FOLLOWING) FROM_P3_TO_F1 FROM emp
ORDEDR BY hiredate

analytic functions - partition order

Hi,

Thanks for great blog :-) I want to ask, if it is possible to do some kind of partition ordering. I know how to order records in partitions created by partition by and order clause, I can assign row numbering specific for partition. What I want is to order these partitions according to first record in that partition.

Is this possible? :)

Thanks.

Need help for rank based dates

Hi,

I can't find any documentation to create two ranks based on single field, like rank() over (partition by field order by date where date > sysdate) rank_1, rank() over (partition by field order by date where date <= sysdate) rank_2.

Is it possible?

One of my reports have a

One of my reports have a requirement to derive statistics by Last of something where the conditions will defer case to case. The example on partition by has helped me a lot. I thought I would have to do that report entirely in PL/SQL :) This page has definitely saved me a lot of time.

Thanks for helping a newbie SQL user like me to gain some levels :)

clarification required

Hi,

You have said that:

"The main ORDER BY clause of the query operates after the analytic functions. So analytic functions can only appear in the select list and in the main ORDER BY clause of the query."

Can you please give example of analytic function being used in the main order by clause.
That would be a great help from your side.

TIA

clarification given

You can just have a look at the Query-5 example!
The SRLNO field is what you ask for.

SELECT empno, deptno, hiredate, ROW_NUMBER( ) OVER (PARTITION BY deptno ORDER BY hiredate NULLS LAST) >>> SRLNO <<< -- this is the select list
FROM emp
WHERE deptno IN (10, 20)
ORDER BY deptno, >>> SRLNO <<<; -- this is the main order by clause