Question 113870 in PostgreSQL Question posted in
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Postgresql – Basing OFFSET on another query?

My table structure is roughly as described in this post:

name processed processing updated ref_time
abc t f 27794395 27794160
def t f 27794395 27793440
ghi t f 27794395 27793440
jkl f f 27794395 27794160
mno t f 27794395 27793440
pqr f t 27794395 27794160

I created a dbfiddle already based on this table structure (more on this below), so there is no need to create your own.

Based on this answer, I am deriving a list of ref_time values to use as a basis for deleting ‘old’ entries from status_table:

with 
    ref as (
        select ref_time 
        from status_table 
        group by ref_time 
        having bool_and(processed)
        order by ref_time desc
        offset 1
    )
delete from status_table s
using ref r
where s.ref_time = r.ref_time

But now I want to be more sophisticated about what I use as the offset… I would ideally like to keep the most recent ref_time for which all records are processed (as per the above example where offset is 1), but the two most recent ref_time where the second ref_time has more associated records than the first (i.e. offset needs to be 2 to skip over the two most recent ref_time).

I figure that the following query (based on this answer) will help in this task, because it counts the total number of processed records based on ref_time:

select ref_time, 
    count(*) cnt_total,
    count(*) filter(where processed) cnt_processed,
    round(avg(processed::int),2) ratio_processed
from status_table
group by ref_time
order by ratio_processed desc, ref_time desc;

So in this dbfiddle I’d need to preserve ref_time=27794160 (rather than include it in the delete list as is the case in the example) because, although it is second, it also has a higher cnt_total than the first.

In general, the rule is that I want to keep all ref_time up to (but not including) the ref_time having the same cnt_total as the one before (or less).

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2

Answers


  1. 0

    Here’s a simple translation into window functions:

    with 
 count_per_completed_ref_time as
  ( select 
        ref_time, 
        count(*) cnt_total
    from  status_table 
    group by ref_time 
    having bool_and(processed)
    order by ref_time desc )
,windowed_counts as
  ( select 
        ref_time,
        cnt_total,
        row_number() over w1 as ref_time_num,
        lag(cnt_total) over w1 as preceding_cnt_total
    from count_per_completed_ref_time
    window w1 as (order by ref_time desc) )
delete from status_table s
where ref_time in --only delete completed ref_times, found in the first CTE
  ( select ref_time from count_per_completed_ref_time)
and ref_time not in --prevent deleting these
  ( select ref_time
    from windowed_counts
    where ref_time_num = 1 --top, latest completed ref_time
    or (  ref_time_num = 2 --second latest
        and cnt_total>preceding_cnt_total)--has higher total than the latest
   ) 
returning *;
    1. Selects your ref_time rows same as before, keeping only the ones that are fully processed.
    2. Uses a window to show order of these ref_time‘s, plus the cnt_total of the preceding ref_time, one higher in this ranking.
    3. Always picks the top ref_time in this order and if the second one’s cnt_total is higher, takes it too.
    4. Deletes all completed ref_time‘s found in 1., unless they were picked in 3., returning everything it deleted, for you to inspect.

    Demo with additional test cases.

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  2. 0 
    WITH sel AS (
   SELECT ref_time
   FROM  (
      SELECT ref_time
           , count(*) FILTER (WHERE drop) OVER (ORDER BY ref_time DESC) AS drops
      FROM  (
         SELECT ref_time
              , lag(count(*)) OVER (ORDER BY ref_time DESC) >= count(*) IS TRUE AS drop
         FROM   status_table
         GROUP  BY ref_time
         HAVING bool_and(processed)
         ) sub1
      ) sub2
   WHERE drops > 0
   )
DELETE FROM status_table d
USING  sel s
WHERE  d.ref_time = s.ref_time;

    fiddle

    Subquery sub1 is mostly what you already had. Plus some more:

    We only need count(*) since HAVING bool_and(processed) excludes other cases anyway.

    lag(count(*)) OVER (ORDER BY ref_time DESC) >= count(*) checks whether the previous row has been same or greater, in which case, we’ll call that a "drop". And we want to keep all rows before the first "drop".

    So count(*) FILTER (WHERE drop) OVER (ORDER BY ref_time DESC) AS drops in sub2 counts those "drops", and WHERE drops > 0 eliminate the leading rows we want to preserve.

    About this "gaps-and-islands" approach:

    If there can be concurrent writes on status_table, you may need to add the locking clause FOR UPDATE to be sure. But you cannot do that in an aggregate query, so you would add another subquery where you do that … See:

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