I have a table that looks like this:
ID | FIELD_NAME | VALUE
23 | sign_up | yes
23 | first_name | Fred
23 | street | Barber Lane
24 | sign_up | no
24 | first_name | Steve
24 | street | Camaro St.
25 | sign_up | yes
25 | first_name | Larry
25 | street | Huckleberry Ave
I want to run a query that will select unique ID's and the values as named columns so it would appear like so:
ID | SIGN_UP | FIRST_NAME | STREET |
23 | yes | Fred | Barber Lane |
24 | no | Steve | Camaro St. |
25 | yes | Larry | Huckleberry Ave. |
Any help would be much appreciated!!
The DISTINCT clause is used in the SELECT statement to filter out duplicate rows in the result set. You can use DISTINCT when you select a single column, or when you select multiple columns as we did in our example.
As a general rule, SELECT DISTINCT incurs a fair amount of overhead for the query. Hence, you should avoid it or use it sparingly. The idea of generating duplicate rows using JOIN just to remove them with SELECT DISTINCT is rather reminiscent of Sisyphus pushing a rock up a hill, only to have it roll back down again.
Yes, you can use COUNT() and DISTINCT together to display the count of only distinct rows. SELECT COUNT(DISTINCT yourColumnName) AS anyVariableName FROM yourTableName; To understand the above syntax, let us create a table.
The UNIQUE keyword in SQL plays the role of a database constraint; it ensures there are no duplicate values stored in a particular column or a set of columns. On the other hand, the DISTINCT keyword is used in the SELECT statement to fetch distinct rows from a table.
You can use this simple solution:
SELECT DISTINCT
a.id,
b.value AS SIGN_UP,
c.value AS FIRST_NAME,
d.value AS STREET
FROM tbl a
LEFT JOIN tbl b ON a.id = b.id AND b.field_name = 'sign_up'
LEFT JOIN tbl c ON a.id = c.id AND c.field_name = 'first_name'
LEFT JOIN tbl d ON a.id = d.id AND d.field_name = 'street'
Just to be safe, I made the joins LEFT JOIN
's because I do not know if an id can have missing fields, in which case they will show up as NULL
in our derived columns.
SQL-Fiddle Demo
You could also try pivoting with the help of grouping and conditional aggregating:
SELECT
ID,
MAX(CASE FIELD_NAME WHEN 'sign_up' THEN VALUE END) AS SIGN_UP,
MAX(CASE FIELD_NAME WHEN 'first_name' THEN VALUE END) AS FIRST_NAME,
MAX(CASE FIELD_NAME WHEN 'street' THEN VALUE END) AS STREET
FROM atable
GROUP BY
ID
;
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