GROUP BY one column, while sorting by another in PostgreSQL

How can I GROUP BY one column, while sorting only by another.

I'm trying to do the following:

SELECT dbId,retreivalTime 
    FROM FileItems 
    WHERE sourceSite='something' 
    GROUP BY seriesName 
    ORDER BY retreivalTime DESC 
    LIMIT 100 
    OFFSET 0;

I want to select the last /n/ items from FileItems, in descending order, with the rows filtered by DISTINCT values of seriesName. The above query errors out ERROR: column "fileitems.dbid" must appear in the GROUP BY clause or be used in an aggregate function. I need the dbid value in order to then take the output of this query, and JOIN it on the source table to get the rest of the columns I wasn.

Note this is basically the gestalt of the below question, with a lot of the extraneous details removed for clarity.

Original question

I have a system I'm migrating from sqlite3 to PostgreSQL, because I've largely outgrown sqlite:

SELECT
            d.dbId,
            d.dlState,
            d.sourceSite,
        [snip a bunch of rows]
            d.note

    FROM FileItems AS d
        JOIN
            ( SELECT dbId
                FROM FileItems
                WHERE sourceSite='{something}'
                GROUP BY seriesName
                ORDER BY MAX(retreivalTime) DESC
                LIMIT 100
                OFFSET 0
            ) AS di
            ON  di.dbId = d.dbId
    ORDER BY d.retreivalTime DESC;

Basically, I want to select the last n DISTINCT items in the database, where the distinct constraint is on one column, and the sorting order is on a different column.

Unfortunately, the above query, while it works fine in sqlite, errors out in PostgreSQL with the error psycopg2.ProgrammingError: column "fileitems.dbid" must appear in the GROUP BY clause or be used in an aggregate function.

Unfortunately, while adding dbId to the GROUP BY clause fixes the issue (e.g. GROUP BY seriesName,dbId), it means the distinct filtering on the query results no longer work,

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 come from the same row)?

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.

See:

• SELECT DISTINCT is slower than expected on my table in PostgreSQL

• Optimize GROUP BY query to retrieve latest record per user

Your case is more complex, though. 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)  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.
Explanation

-
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)

-
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.

StackExchange Database Administrators Q#74773, answer score: 12