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Cómo optimizar una consulta MySQL dolorosamente lenta que encuentra correlaciones

3 cosas:

  • Estás recalculando lo mismo un millón y medio de veces (en realidad, todo solo depende de algunos parámetros que son los mismos para muchas filas)
  • Los agregados son más eficientes en fragmentos grandes (JOIN) que en fragmentos pequeños (subconsultas)
  • MySQL es extremadamente lento con las subconsultas.

Por lo tanto, cuando calcule "recuentos de votos por ID de opción" (que necesita escanear la tabla grande), y luego necesite calcular "recuentos de votos por ID de encuesta", bueno, no vuelva a iniciar la tabla grande, ¡simplemente use los resultados anteriores!

Podrías hacer eso con un ROLLUP.

Aquí hay una consulta que hará lo que necesita, ejecutándose en Postgres.

Para que MySQL haga esto, necesitará reemplazar todas las declaraciones "WITH foo AS (SELECT...)" con tablas temporales. Eso es fácil. Las tablas temporales en memoria de MySQL son rápidas, no tenga miedo de usarlas, ya que le permitirán reutilizar los resultados de los pasos anteriores y ahorrar muchos cálculos.

He generado datos de prueba aleatorios, parece funcionar. Ejecuta en 0.3s...

WITH 
-- users of interest : target group
uids AS (
    SELECT DISTINCT user_id 
        FROM    options 
        JOIN    responses USING (option_id)
        WHERE   poll_id=22
    ),
-- votes of everyone and target group
votes AS (
    SELECT poll_id, option_id, sum(all_votes) AS all_votes, sum(target_votes) AS target_votes
        FROM (
            SELECT option_id, count(*) AS all_votes, count(uids.user_id) AS target_votes
                FROM        responses 
                LEFT JOIN   uids USING (user_id)
                GROUP BY option_id
        ) v
        JOIN    options     USING (option_id)
        GROUP BY poll_id, option_id
    ),
-- totals for all polls (reuse previous result)
totals AS (
    SELECT poll_id, sum(all_votes) AS all_votes, sum(target_votes) AS target_votes
        FROM votes
        GROUP BY poll_id
    ),
poll_options AS (
    SELECT poll_id, count(*) AS poll_option_count
        FROM options 
        GROUP BY poll_id
    )
-- reuse previous tables to get some stats
SELECT  *, ABS(total_percent - subgroup_percent) AS deviation
    FROM (
        SELECT
            poll_id,
            option_id,
            v.target_votes / v.all_votes AS subgroup_percent,
            t.target_votes / t.all_votes AS total_percent,
            poll_option_count
        FROM votes  v
        JOIN totals t           USING (poll_id)
        JOIN poll_options po    USING (poll_id)
    ) AS foo
    ORDER BY deviation DESC, poll_option_count DESC;

                                                                                  QUERY PLAN                                                                                
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------
 Sort  (cost=14910.46..14910.56 rows=40 width=144) (actual time=299.844..299.862 rows=200 loops=1)
   Sort Key: (abs(((t.target_votes / t.all_votes) - (v.target_votes / v.all_votes)))), po.poll_option_count
   Sort Method:  quicksort  Memory: 52kB
   CTE uids
     ->  HashAggregate  (cost=1801.43..1850.52 rows=4909 width=4) (actual time=3.935..4.793 rows=4860 loops=1)
           ->  Nested Loop  (cost=0.00..1789.16 rows=4909 width=4) (actual time=0.029..2.555 rows=4860 loops=1)
                 ->  Seq Scan on options  (cost=0.00..3.50 rows=5 width=4) (actual time=0.008..0.032 rows=5 loops=1)
                       Filter: (poll_id = 22)
                 ->  Index Scan using responses_option_id_key on responses  (cost=0.00..344.86 rows=982 width=8) (actual time=0.012..0.298 rows=972 loops=5)
                       Index Cond: (public.responses.option_id = public.options.option_id)
   CTE votes
     ->  HashAggregate  (cost=13029.43..13032.43 rows=200 width=24) (actual time=298.255..298.317 rows=200 loops=1)
           ->  Hash Join  (cost=13019.68..13027.43 rows=200 width=24) (actual time=297.953..298.103 rows=200 loops=1)
                 Hash Cond: (public.responses.option_id = public.options.option_id)
                 ->  HashAggregate  (cost=13014.18..13017.18 rows=200 width=8) (actual time=297.839..297.879 rows=200 loops=1)
                       ->  Merge Left Join  (cost=399.13..11541.43 rows=196366 width=8) (actual time=9.301..230.467 rows=196366 loops=1)
                             Merge Cond: (public.responses.user_id = uids.user_id)
                             ->  Index Scan using responses_pkey on responses  (cost=0.00..8585.75 rows=196366 width=8) (actual time=0.015..121.971 rows=196366 loops=1)
                             ->  Sort  (cost=399.13..411.40 rows=4909 width=4) (actual time=9.281..22.044 rows=137645 loops=1)
                                   Sort Key: uids.user_id
                                   Sort Method:  quicksort  Memory: 420kB
                                   ->  CTE Scan on uids  (cost=0.00..98.18 rows=4909 width=4) (actual time=3.937..6.549 rows=4860 loops=1)
                 ->  Hash  (cost=3.00..3.00 rows=200 width=8) (actual time=0.095..0.095 rows=200 loops=1)
                       ->  Seq Scan on options  (cost=0.00..3.00 rows=200 width=8) (actual time=0.007..0.043 rows=200 loops=1)
   CTE totals
     ->  HashAggregate  (cost=5.50..8.50 rows=200 width=68) (actual time=298.629..298.640 rows=40 loops=1)
           ->  CTE Scan on votes  (cost=0.00..4.00 rows=200 width=68) (actual time=298.257..298.425 rows=200 loops=1)
   CTE poll_options
     ->  HashAggregate  (cost=4.00..4.50 rows=40 width=4) (actual time=0.091..0.101 rows=40 loops=1)
           ->  Seq Scan on options  (cost=0.00..3.00 rows=200 width=4) (actual time=0.005..0.020 rows=200 loops=1)
   ->  Hash Join  (cost=6.95..13.45 rows=40 width=144) (actual time=298.994..299.554 rows=200 loops=1)
         Hash Cond: (t.poll_id = v.poll_id)
         ->  CTE Scan on totals t  (cost=0.00..4.00 rows=200 width=68) (actual time=298.632..298.669 rows=40 loops=1)
         ->  Hash  (cost=6.45..6.45 rows=40 width=84) (actual time=0.335..0.335 rows=200 loops=1)
               ->  Hash Join  (cost=1.30..6.45 rows=40 width=84) (actual time=0.140..0.263 rows=200 loops=1)
                     Hash Cond: (v.poll_id = po.poll_id)
                     ->  CTE Scan on votes v  (cost=0.00..4.00 rows=200 width=72) (actual time=0.001..0.030 rows=200 loops=1)
                     ->  Hash  (cost=0.80..0.80 rows=40 width=12) (actual time=0.130..0.130 rows=40 loops=1)
                           ->  CTE Scan on poll_options po  (cost=0.00..0.80 rows=40 width=12) (actual time=0.093..0.119 rows=40 loops=1)
 Total runtime: 300.132 ms