Postgresql – How to “group” based on consecutive occurrences of an element in a column in postgres

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I have a table that, when ordered, describes a path by point descriptions in each row.
A column tells whether a row is a special (stop) point within that path and is empty otherwise. The path starts and ends with such a row and has many in between. What I want to do is create line segments from the point rows that start at such a row and also end at such a row.

point  stop
  1     yes
  2      
  3     yes
  4
  5
  6     yes

I want to call ST_Makeline from PostGIS to turn the ordered points into these line segments. How can I enforce that ST_Makeline, being a "summary" function is only called for the inclusive point groups 1 to 3 and 3 to 6?

Best Answer

I personally think this is not a good design because all intermediate stop points must be included into two segments.

IMHO, you should be able to transform it into something similar to:

id | start | end | stop
---|-------|-----|-----
 1 |   1   |  2  |
 2 |   2   |  3  | yes
 3 |   3   |  4  | 
 4 |   4   |  5  | 
 5 |   5   |  6  | yes

But using your current schema you could try by using:

WITH x AS
(
  SELECT
      point,
      stop,
      LEAD(point) OVER (ORDER BY point) nxt,
      SUM(CASE WHEN stop = true THEN 1 ELSE 0 END) OVER (ORDER BY point) grp
  FROM
      tbl
  ORDER BY
      point
)
SELECT
    grp, ST_MakeLine(array_agg(ST_MakePoint(point, nxt::int))) lines
FROM
    x
WHERE
    nxt IS NOT NULL
GROUP BY
    grp
ORDER BY
    grp;

That basically returns an array of points like this:

grp | points                   
--: | :------------------------
  1 | {"(1,2)","(2,3)"}        
  2 | {"(3,4)","(4,5)","(5,6)"}

Then using ST_MakePoint and ST_MakeLine you can get:

grp | lines                                                                                                             
--: | :-----------------------------------------------------------------------------------------------------------------
  1 | 010200000002000000000000000000F03F000000000000004000000000000000400000000000000840                                
  2 | 010200000003000000000000000000084000000000000010400000000000001040000000000000144000000000000014400000000000001840

db<>fiddle here

Consistent rows

The important question which does not seem to be on your radar yet:
From each set of rows for the same seriesName, do you want the columns of one row, or just any values from multiple rows (which may or may not go together)?

Your answer does the latter, you combine the maximum dbid with the maximum retreivaltime, which may come from a different row.

To get consistent rows, use DISTINCT ON and wrap it in a subquery to order the result differently:

SELECT * FROM (
   SELECT DISTINCT ON (seriesName)
          dbid, seriesName, retreivaltime
   FROM   FileItems
   WHERE  sourceSite = 'mk' 
   ORDER  BY seriesName, retreivaltime DESC NULLS LAST  -- latest retreivaltime
   ) sub
ORDER BY retreivaltime DESC NULLS LAST
LIMIT  100;

Details for DISTINCT ON:

Select first row in each GROUP BY group?

Aside: should probably be retrievalTime, or better yet: retrieval_time. Unquoted mixed case identifiers are a common source of confusion in Postgres.

Better Performance with rCTE

Since we are dealing with a big table here, we'd need a query that can use an index, which is not the case for the above query (except for WHERE sourceSite = 'mk')

On closer inspection, your problem seems to be a special case of a loose index scan. Postgres does not support loose index scans natively, but it can be emulated with a recursive CTE. There is a code example for the simple case in the Postgres Wiki.

Related answer on SO with more advanced solutions, explanation, fiddle:

Optimize GROUP BY query to retrieve latest record per user

Your case is more complex, though. But I think I found a variant to make it work for you. Building on this index (without WHERE sourceSite = 'mk')

CREATE INDEX mi_special_full_idx ON MangaItems
(retreivaltime DESC NULLS LAST, seriesName DESC NULLS LAST, dbid)

Or (with WHERE sourceSite = 'mk')

CREATE INDEX mi_special_granulated_idx ON MangaItems
(sourceSite, retreivaltime DESC NULLS LAST, seriesName DESC NULLS LAST, dbid)

The first index can be used for both queries, but is not fully efficient with the additional WHERE condition. The second index is of very limited use for the first query. Since you have both variants of the query consider creating both indexes.

I added dbid at the end to allow Index Only scans.

This query with a recursive CTE makes use of the index. I tested with Postgres 9.3 and it works for me: no sequential scan, all index-only scans:

WITH RECURSIVE cte AS (
   (
   SELECT dbid, seriesName, retreivaltime, 1 AS rn, ARRAY[seriesName] AS arr
   FROM   MangaItems
   WHERE  sourceSite = 'mk'
   ORDER  BY retreivaltime DESC NULLS LAST, seriesName DESC NULLS LAST
   LIMIT  1
   )
   UNION ALL
   SELECT i.dbid, i.seriesName, i.retreivaltime, c.rn + 1, c.arr || i.seriesName
   FROM   cte c
   ,      LATERAL (
      SELECT dbid, seriesName, retreivaltime
      FROM   MangaItems
      WHERE (retreivaltime, seriesName) < (c.retreivaltime, c.seriesName)
      AND    sourceSite = 'mk'  -- repeat condition!
      AND    seriesName <> ALL(c.arr)
      ORDER  BY retreivaltime DESC NULLS LAST, seriesName DESC NULLS LAST
      LIMIT  1
      ) i
   WHERE  c.rn < 101
   )
SELECT dbid
FROM   cte
ORDER  BY rn;

You need to include seriesName in ORDER BY, since retreivaltime is not unique. "Almost" unique is still not unique.

Explain

The non-recursive query starts with the latest row.
The recursive query adds the next-latest row with a seriesName that's not in the list, yet etc., until we have 100 rows.
Essential parts are the JOIN condition (b.retreivaltime, b.seriesName) < (c.retreivaltime, c.seriesName) and the ORDER BY clause ORDER BY retreivaltime DESC NULLS LAST, seriesName DESC NULLS LAST. Both match the sort order of the index, which allows for the magic to happen.
Collecting seriesName in an array to rule out duplicates. The cost for b.seriesName <> ALL(c.foo_arr) grows progressively with the number of rows, but for just 100 rows it is still cheap.
Just returning dbid as clarified in the comments.

Alternative with partial indexes:

We have been dealing with similar problems before. Here is a highly optimized complete solution based on partial indexes and a looping function:

Can spatial index help a "range - order by - limit" query

Probably the fastest way (except for a materialized view) if done right. But more complex.

Materialized View

Since you do not have a lot of write operations and they are not performance-critical as stated in the comments (should be in the question), save the top n pre-computed rows in a materialized view and refresh it after relevant changes to the underlying table. Base your performance-critical queries on the materialized view instead.

Could just be a "thin" mv of the latest 1000 dbid or so. In the query, join to the original table. For instance, if content is sometimes updated, but the top n rows can remain unchanged.
Or a "fat" mv with whole rows to return. Faster, yet. Needs to be refreshed more often, obviously.

Details in the manual here and here.

Best Answer

Related Solutions

Postgresql – Problem with shortest distance calculation in PostGIS

Postgresql – GROUP BY one column, while sorting by another in PostgreSQL

Consistent rows

Better Performance with rCTE

Explain

Alternative with partial indexes:

Materialized View

Related Question