WITH Queries (Common Table Expressions)
Hai semuanya, di materi kali ini kita akan membahas tentang Common Table Expression yaitu menggunakan WITH Queries pada PostgreSQL. Karena pembahasan kali ini akan lumayan panjang jadi kita akan bagi-bagi menjadi beberapa bagian diataranya:
- Select in WITH
- More details using Select in WITH
- Recursive Queries
- Search order
- Cycle Detection
Ok langsung aja kita bahas materi yang pertama
Select in WITH
The WITH query provides a way to write auxiliary statements for use in a larger query. It helps in breaking down complicated and large queries into simpler forms, which are easily readable. These statements often referred to as Common Table Expressions or CTEs, can be thought of as defining temporary tables that exist just for one query.
The WITH query being CTE query, is particularly useful when subquery is executed multiple times. It is equally helpful in place of temporary tables. It computes the aggregation once and allows us to reference it by its name (may be multiple times) in the queries.
The basic syntax of WITH Query is
WITH <named_query> as (
select ...
from ...
[where ...]
)
select ...
from ... | <named_query>
[where ... | <named_query>]Where <named_query> equal to temporary table with given named. The <named_query> can be the same as existing table name and will take precedence. You can use data-modifying statements (INSERT, UPDATE or DELETE) in WITH. This allows you to perform several different operations in the same query.
Berikut adalah contoh implementasi querynya:
Jika dijalankan hasilnya seperti berikut:
hr=# with get_emp_in_dep_hundred as (
hr(# select *
hr(# from employees
hr(# where department_id = 100
hr(# )
hr-# select employee_id, first_name, salary, commission_pct
hr-# from get_emp_in_dep_hundred
hr-# limit 5;
employee_id | first_name | salary | commission_pct
-------------+-------------+----------+----------------
108 | Nancy | 12000.00 |
109 | Daniel | 9000.00 |
110 | John | 8200.00 |
111 | Ismael | 7700.00 |
112 | Jose Manuel | 7800.00 |
(5 rows)
More details using Select in WITH
Sepertinya telah saya jelaskan di section sebelumnya, The WITH Query pada dasarnya digunakan untuk mem-breakdown complicated queries menjadi lebih simple. berikut contohnya:
select employee_id, first_name, salary, department_id
from employees
where department_id in
(
select distinct department_id as dep_id
from departments natural join locations
where country_id in ('UK', 'US')
)
and salary >= 10000
order by salary desc
limit 10;Jika menggunakan WITH Queries maka seperti berikut implementasinya:
which displays top 10 employees salary and filter by department location in US or UK. jika dijalankan hasilnya seperti berikut:
hr=# with top10_salaries as
hr-# (
hr(# select employee_id, first_name, salary, department_id
hr(# from employees
hr(# where salary >= 10000
hr(# order by salary desc
hr(# limit 10),
hr-# department_uk_us as
hr-# (
hr(# select distinct department_id as dep_id
hr(# from departments
hr(# natural join locations
hr(# where country_id in ('UK', 'US')
hr(# )
hr-# select *
hr-# from top10_salaries
hr-# where department_id in (select dep_id from department_uk_us);
employee_id | first_name | salary | department_id
-------------+------------+----------+---------------
100 | Steven | 24000.00 | 90
102 | Lex | 17000.00 | 90
101 | Neena | 17000.00 | 90
145 | John | 14000.00 | 80
146 | Karen | 13500.00 | 80
205 | Shelley | 12000.00 | 110
108 | Nancy | 12000.00 | 100
147 | Alberto | 12000.00 | 80
168 | Lisa | 11500.00 | 80
(9 rows)
Selain itu juga kita bisa membuat two auxiliary statements named employees_in_dep_90 and top3_salaries dimana the output of employees_in_dep_90 digunakan pada top3_salaries. seperti berikut querynya:
Jika dijalankan hasilnya seperti berikut:
hr=# with employees_in_dep_90 as
hr-# (
hr(# select *
hr(# from employees
hr(# where department_id in (90, 100, 110)
hr(# ),
hr-# top3_salaries as
hr-# (
hr(# select employee_id, first_name, salary
hr(# from employees_in_dep_90
hr(# order by salary desc
hr(# limit 3
hr(# )
hr-# select *
hr-# from top3_salaries;
employee_id | first_name | salary
-------------+------------+----------
100 | Steven | 24000.00
102 | Lex | 17000.00
101 | Neena | 17000.00
(3 rows)
Nah bagaimana? lebih mudah untuk di baca khan dibandingkan kita membuat dengan nested SUB-QUERY.
Recursive Queries
The optional RECURSIVE modifier changes WITH from a mere syntactic convenience into a feature that accomplishes things not otherwise possible in standard SQL. Using RECURSIVE, a WITH query can refer to its own output. A very simple example is this query to sum the integers from 1 through 100:
WITH RECURSIVE t(n) AS (
VALUES (1)
UNION ALL
SELECT n+1 FROM t WHERE n < 100
)
SELECT sum(n) FROM t;The general form of a recursive WITH query is always a non-recursive term, then UNION (or UNION ALL), then a recursive term, where only the recursive term can contain a reference to the query’s own output. Such a query is executed as follows:
-
Evaluate the non-recursive term. For UNION (but not UNION ALL), discard duplicate rows. Include all remaining rows in the result of the recursive query, and also place them in a temporary working table.
-
So long as the working table is not empty, repeat these steps:
- Evaluate the recursive term, substituting the current contents of the working table for the recursive self-reference. For UNION (but not UNION ALL), discard duplicate rows and rows that duplicate any previous result row. Include all remaining rows in the result of the recursive query, and also place them in a temporary intermediate table.
- Replace the contents of the working table with the contents of the intermediate table, then empty the intermediate table.
Recursive queries are typically used to deal with hierarchical or tree-structured data. A usefull example is this query to find all the direct and indirect sub-employees of a manager, given only a table that show immediate includes:
Jika dijalankan hasilnya seperti berikut:
hr=# with recursive managed_by(manager_id, employee_id, first_name) as
hr-# (
hr(# select our_manager.manager_id,
hr(# our_manager.employee_id,
hr(# our_manager.first_name
hr(# from employees our_manager
hr(# where employee_id = 101
hr(# UNION ALL
hr(# select emp.manager_id,
hr(# emp.employee_id,
hr(# emp.first_name
hr(# from employees emp
hr(# join managed_by man on (emp.manager_id = man.employee_id)
hr(# )
hr-# select employee_id,
hr-# first_name,
hr-# manager_id
hr-# from managed_by;
employee_id | first_name | manager_id
-------------+-------------+------------
101 | Neena | 100
108 | Nancy | 101
200 | Jennifer | 101
203 | Susan | 101
204 | Hermann | 101
205 | Shelley | 101
109 | Daniel | 108
110 | John | 108
111 | Ismael | 108
112 | Jose Manuel | 108
113 | Luis | 108
206 | William | 205
(12 rows)
Search order
When computing a tree traversal using a recursive query, you might want to order the results in either depth-first or breadth-first order. This can be done by computing an ordering column alongside the other data columns and using that to sort the results at the end. Note that this does not actually control in which order the query evaluation visits the rows; that is as always in SQL implementation-dependent. This approach merely provides a convenient way to order the results afterwards.
To create a depth-first order, we compute for each result row an array of rows that we have visited so far. For example, consider the following query that searches a table tree using a link field:
WITH RECURSIVE search_tree(... , path) AS (
SELECT ... , ARRAY[t.column]
FROM tree t
UNION ALL
SELECT ... , path || t.column
FROM tree t, search_tree st
WHERE t.id = st.link
)
SELECT * FROM search_tree ORDER BY path;Here the code:
Jika dijalankan hasilnya seperti berikut:
hr=# with recursive managed_by(manager_id, employee_id, first_name, path) as
hr-# (
hr(# select our_manager.manager_id,
hr(# our_manager.employee_id,
hr(# our_manager.first_name,
hr(# array [our_manager.first_name]
hr(# from employees our_manager
hr(# where employee_id = 101
hr(# UNION ALL
hr(# select emp.manager_id,
hr(# emp.employee_id,
hr(# emp.first_name,
hr(# array [emp.first_name]
hr(# from employees emp
hr(# join managed_by man on (emp.manager_id = man.employee_id)
hr(# )
hr-# select employee_id, first_name, manager_id
hr-# from managed_by
hr-# order by path desc;
employee_id | first_name | manager_id
-------------+-------------+------------
206 | William | 205
203 | Susan | 101
205 | Shelley | 101
101 | Neena | 100
108 | Nancy | 101
113 | Luis | 108
112 | Jose Manuel | 108
110 | John | 108
200 | Jennifer | 101
111 | Ismael | 108
204 | Hermann | 101
109 | Daniel | 108
(12 rows)
Atau selain itu juga kita bisa multiple column order dengan with query recursive seperti berikut:
Jika dijalankan hasilnya seperti berikut:
hr=# with recursive managed_by(manager_id, employee_id, first_name, salary, department_id, path) as
hr-# (
hr(# select our_manager.manager_id,
hr(# our_manager.employee_id,
hr(# our_manager.first_name,
hr(# our_manager.salary,
hr(# our_manager.department_id,
hr(# array [ROW (our_manager.department_id, our_manager.salary)]
hr(# from employees our_manager
hr(# where employee_id = 101
hr(# UNION ALL
hr(# select emp.manager_id,
hr(# emp.employee_id,
hr(# emp.first_name,
hr(# emp.salary,
hr(# emp.department_id,
hr(# array [ROW (emp.department_id, emp.salary)]
hr(# from employees emp
hr(# join managed_by man on (emp.manager_id = man.employee_id)
hr(# )
hr-# select employee_id, first_name, manager_id, department_id, salary
hr-# from managed_by
hr-# order by path desc;
employee_id | first_name | manager_id | department_id | salary
-------------+-------------+------------+---------------+----------
205 | Shelley | 101 | 110 | 12000.00
206 | William | 205 | 110 | 8300.00
108 | Nancy | 101 | 100 | 12000.00
109 | Daniel | 108 | 100 | 9000.00
110 | John | 108 | 100 | 8200.00
112 | Jose Manuel | 108 | 100 | 7800.00
111 | Ismael | 108 | 100 | 7700.00
113 | Luis | 108 | 100 | 6900.00
101 | Neena | 100 | 90 | 17000.00
204 | Hermann | 101 | 70 | 10000.00
203 | Susan | 101 | 40 | 6500.00
200 | Jennifer | 101 | 10 | 4400.00
(12 rows)
Cycle Detection
When working with recursive queries it is important to be sure that the recursive part of the query will eventually return no tuples, or else the query will loop indefinitely. Sometimes, using UNION instead of UNION ALL can accomplish this by discarding rows that duplicate previous output rows. However, often a cycle does not involve output rows that are completely duplicate: it may be necessary to check just one or a few fields to see if the same point has been reached before. The standard method for handling such situations is to compute an array of the already-visited values. For example, consider again the following query that searches a table graph using a link field:
WITH RECURSIVE search_graph(... , depth) AS (
SELECT ... , 0
FROM ...
UNION ALL
SELECT ... , sg.depth + 1
FROM ... , search_graph sg
)
SELECT * FROM search_graph;The simple query example is:
This query will loop if the link relationships contain cycles. Jika dijalankan hasilnya seperti berikut:
hr=# with recursive managed_by(manager_id, employee_id, first_name, depth) as
hr-# (
hr(# select our_manager.manager_id,
hr(# our_manager.employee_id,
hr(# our_manager.first_name,
hr(# 0
hr(# from employees our_manager
hr(# UNION ALL
hr(# select emp.manager_id,
hr(# emp.employee_id,
hr(# emp.first_name,
hr(# man.depth + 1
hr(# from employees emp
hr(# join managed_by man on (emp.manager_id = man.employee_id)
hr(# )
hr-# select *
hr-# from managed_by;
manager_id | employee_id | first_name | depth
------------+-------------+-------------+-------
| 100 | Steven | 0
100 | 101 | Neena | 0
100 | 102 | Lex | 0
102 | 103 | Alexander | 0
103 | 104 | Bruce | 0
103 | 105 | David | 0
103 | 106 | Valli | 0
100 | 122 | Payam | 0
100 | 123 | Shanta | 0
100 | 124 | Kevin | 0
120 | 125 | Julia | 0
120 | 126 | Irene | 0
120 | 127 | James | 0
100 | 146 | Karen | 1
100 | 145 | John | 1
100 | 124 | Kevin | 1
100 | 123 | Shanta | 1
100 | 122 | Payam | 1
100 | 121 | Adam | 1
100 | 120 | Matthew | 1
100 | 114 | Den | 1
100 | 102 | Lex | 1
100 | 101 | Neena | 1
(315 rows)
Because we require a “depth” output, just changing UNION ALL to UNION would not eliminate the looping. Instead we need to recognize whether we have reached the same row again while following a particular path of links. We add two columns is_cycle and path to the loop-prone query:
Jika dijalankan maka hasilnya seperti berikut:
hr=# with recursive managed_by(manager_id, employee_id, first_name, depth, is_cycle, path) as
hr-# (
hr(# select our_manager.manager_id,
hr(# our_manager.employee_id,
hr(# our_manager.first_name,
hr(# 0,
hr(# false,
hr(# ARRAY [our_manager.employee_id]
hr(# from employees our_manager
hr(# UNION ALL
hr(# select emp.manager_id,
hr(# emp.employee_id,
hr(# emp.first_name,
hr(# man.depth + 1,
hr(# emp.employee_id = ANY (path),
hr(# path || emp.employee_id
hr(# from employees emp
hr(# join managed_by man on (emp.manager_id = man.employee_id)
hr(# where NOT is_cycle
hr(# )
hr-# select *
hr-# from managed_by;
manager_id | employee_id | first_name | depth | is_cycle | path
------------+-------------+-------------+-------+----------+-------------------
| 100 | Steven | 0 | f | {100}
100 | 101 | Neena | 0 | f | {101}
100 | 102 | Lex | 0 | f | {102}
102 | 103 | Alexander | 0 | f | {103}
101 | 205 | Shelley | 0 | f | {205}
205 | 206 | William | 0 | f | {206}
100 | 201 | Michael | 1 | f | {100,201}
100 | 149 | Eleni | 1 | f | {100,149}
100 | 148 | Gerald | 1 | f | {100,148}
100 | 147 | Alberto | 1 | f | {100,147}
100 | 146 | Karen | 1 | f | {100,146}
100 | 145 | John | 1 | f | {100,145}
100 | 124 | Kevin | 1 | f | {100,124}
100 | 123 | Shanta | 1 | f | {100,123}
100 | 122 | Payam | 1 | f | {100,122}
100 | 121 | Adam | 1 | f | {100,121}
100 | 120 | Matthew | 1 | f | {100,120}
100 | 114 | Den | 1 | f | {100,114}
(315 rows)
hr=#