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Last updated on 4/19/21

Understand window functions using OVER and PARTITION BY

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Window functions are often used to (among other things):

  • calculate cumulative sums

  • order rows within a partition.

As you will see, there are many similarities between aggregations and window functions.

Let’s wave our little magic want over this... :magicien:

SELECT incorporation_date, min(id) OVER() FROM entity ;

Tada! No more error! When we insert  OVER()  , the aggregate function  min()  returns as many rows as there are in entity. This is not normal behavior for an aggregate function!

Window Functions

Yes, it’s true... there are many similarities between aggregations and window functions. Both are executed in two phases, and they differ only in respect to phase two:

 

Agrégation

Window Function

Phase 1

Partitioning by partitioning attributes

Partitioning by partitioning attributes

Phase 2

Application of an aggregate function

Application...

  •  of an aggregate function with modified behavior

  • OR a ranking function.

Result

As many rows as aggregates

As many rows as the original table

Window functions are defined using an OVER clause. The OVER clause has two capabilities, each with its own behavior! Here are the corresponding syntaxes:

  • OVER (PARTITION BY ...)

  • OVER (PARTITION BY ... ORDER BY ...)

OVER (PARTITION BY...)

Let’s analyze these two queries, which use the nb_entities table from the previous chapter:

-- REQUETE n°1SELECT sum(cnt_entities) FROM nb_entities GROUP BY id_intermediary ;-- REQUETE n°2SELECT sum(cnt_entities) OVER (PARTITION BY id_intermediary) FROM nb_entities ;

Query no. 2 functions almost like the aggregation in query 1; the only thing that’s different is what  sum  returns.

In query no. 2, if  sum  receives as input the list of values  [10, 1, 5]  , it won’t return  16  ; it will return  [16, 16, 16].

In both cases, we are calculating the total number of companies created by each intermediary. But here is how the result is presented using a window function:

SELECT id_intermediary, jurisdiction, cnt_entities, sum(cnt_entities) OVER (PARTITION BY id_intermediary) AS entities_by_intermediary FROM nb_entities ;

id_intermediary

jurisdiction

cnt_entities

entities_by_intermediary 

4000

SAM

10

16

4000

PMA

1

16

4000

CYP

5

16

4001

SAM

3

5

4001

NEV

2

5

[...]

[...]

[...]

[...]

OVER (PARTITION BY... ORDER BY...)

With an aggregate function

When we add  ORDER BY  to the  OVER  clause, the aggregate function behaves in still another way!

Indeed, it considers these values to be ranked. As before, the aggregate function is going to return as many rows as it received as input. But it’s going to do this:

  1. Perform a calculation on the 1st value, and return the result;

  2. Perform a calculation on the 1st and 2nd values, and return the result;

  3. Perform a calculation on the 1st, 2nd, and 3rd values, and return the result;

  4. And so on.

Thus, if the  sum  function receives [10, 5, 1], it will return [10, 15, 16], because

  • 10 = 10

  • 10 + 5 = 15

  • 10 + 5 + 1 = 16

Here,  sum  behaves like a cumulative sum!

With a ranking function

If we use a ranking function (for example,  rank  ), it will simply return the order of the rows. These rows have been previously sorted, thanks to  ORDER BY .

A little example: we are in a race, and have recorded the time it took each runner to finish the course. To find out who will be on the podium, we need to rank the athletes according to their time:

SELECT firstname, time, rank() OVER (ORDER BY temps) FROM course ;

firstname

time

rank()

Naomi

3 min 15 s

1

Sarah

3 min 19 s

3

Sonia

3 min 16 s

2

Luke

10 min 39 s

4

Cumulative Sums and Ranking Numbers

So let’s assign a rank to each jurisdiction for each intermediary. Let’s call our ranking  rank  . To assign a  rank  to a jurisdiction, I sort  cnt_entities  in descending order. Since I want to obtain a ranking for each intermediary, I write  PARTITION BY id_intermediary  .

We can also calculate a cumulative sum! Let’s calculate the cumulative sum of   cnt_entities  for each intermediary, sorting the rows in descending order of   cnt_entities  . Let’s call our cumulative sum  cum_sum  .

SELECT id_intermediary, jurisdiction, cnt_entities, rank() OVER(PARTITION BY id_intermediary ORDER BY cnt_entities DESC) AS rank, sum(cnt_entities) OVER(PARTITION BY id_intermediary ORDER BY cnt_entities DESC) AS cum_sumFROM nb_entities ;

Here's the result:

id_intermediary

jurisdiction

cnt_entitites

rank

cum_sum

4000

SAM

10

1

10

4000

CYP

5

2

15

4000

PMA

1

3

16

4001

SAM

3

1

3

4001

NEV

2

2

5

[...]

[...]

[...]

[...]

[...]

A Little Exercise!

The database is online. Get some practice by rewriting the queries found in this chapter. Don’t hesitate to change them, play with them, and “see what happens.”

Interactive Console

Summary

  • Window functions are very similar to aggregations, except they don’t change the number of rows.

  • The  OVER  keyword can be used to form groups of rows (aggregate functions) or to order rows within a partition (ranking functions).

  • The keyword  OVER  can be used to calculate  cumulative sums  or  determine rankings .

     

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