## All we need is an easy explanation of the problem, so here it is.

Given a table in Postgres like

```
CREATE TABLE t1 (
type text NOT NULL,
value int NOT NULL
)
```

where `type`

could be `A`

, `B`

or `C`

and given an arbitrary, *repeating* pattern like

```
A B B C B B
```

how can I query the table so that the results are sorted first according to the pattern and then according to the value? In other words, the first row is the `A`

with the lowest `value`

, the second row is the `B`

with the lowest `value`

, the third row is the `B`

with the second lowest `value`

and so on. If we run out of particular type, we just move on to the next letter in the pattern (i.e. if we don’t have any more `C`

s to return, the pattern becomes `ABBBB`

).

type | value |
---|---|

A | 1 |

B | 1 |

B | 2 |

C | 1 |

B | 3 |

B | 4 |

A | 2 |

B | 5 |

B | 6 |

B | 7 |

B | 8 |

A | 3 |

B | 9 |

The actual pattern is dynamic and has an arbitrary length, thought it will always be constrained to only the possible values for `type`

.

Here is a fiddle with sample data.

## How to solve :

I know you bored from this bug, So we are here to help you! Take a deep breath and look at the explanation of your problem. We have many solutions to this problem, But we recommend you to use the first method because it is tested & true method that will 100% work for you.

### Method 1

Not easy with plain SQL, but still possible:

```
WITH pattern AS (
SELECT *, row_number() OVER (PARTITION BY type ORDER BY ord) AS pos
FROM unnest('{A,B,B,C,B,B}'::text[]) WITH ORDINALITY t(type, ord)
-- provide pattern here
)
, type_frequency AS (
SELECT type, count(*) AS freq
FROM pattern
GROUP BY 1
)
SELECT type, t.value -- , t.epoch, p.ord, pos
FROM (
SELECT type, value
, ceil(rn / freq::float) AS epoch
, (rn - 1) % freq + 1 AS pos
FROM (
SELECT *, row_number() OVER (PARTITION BY type ORDER BY value) AS rn
FROM t1 -- base table here
JOIN type_frequency tf USING (type)
) sub
) t
JOIN pattern p USING (type, pos)
ORDER BY t.epoch, p.ord;
```

*db<>fiddle here*

Produces exactly your desired result.

Would seem simpler with a procedural solution looping through the pattern and getting the next greater value per type from the table. But this query should still perform decently.

#### User instructions

Provide * any* pattern once in the first CTE

`pattern`

. Assuming base type `text`

, but any type supporting equality works. Unnest using `WITH ORDINALITY`

to preserve the original order of elements in the pattern (`ord`

). Distill the position per type (`pos`

) to match the same for table rows later. About `WITH ORDINALITY`

:The second CTE `type_frequency`

computes distinct values and their respective frequency in the pattern.

In the outer query, in the subquery `sub`

, join to `type_frequency`

to filter only involved types while adding the frequency, and add a row number (`rn`

) per type.

Dividing that `rn`

by the value frequency `freq`

produces an `epoch`

, the principal order of rows. (Can’t use integer division here, that would truncate, so cast to `float`

!)

`rn`

modulo (`%`

) `freq`

produces the position `pos`

per type. Shift back (`- 1`

) and forth (`+ 1`

) to fix an off-by-1 issue. We need an integer type for the modulo operation.

Finally, join to the pattern on `(type, pos)`

to attach the original order (`ord`

) in the pattern per `epoch`

.

**Note: Use and implement method 1 because this method fully tested our system.Thank you 🙂**

All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0