Encuentra a los usuarios que tienen más probabilidades de convertirse en TL3

Datos e informes
,
17

Esto es ligeramente más eficiente. Si todavía no te funciona, puedes intentar eliminar algunas columnas, con sus uniones y consultas asociadas.

EDITAR Vale, finalmente he aclarado mis tipos de unión (hace tiempo que no lo hacía). Esta consulta actualizada es mucho más eficiente.

with
t as (
  select 
    CURRENT_TIMESTAMP - ((0 + 100) * (INTERVAL '1 days')) as start,
    CURRENT_TIMESTAMP - (0 * (INTERVAL '1 days')) as end
  ),

-- Conteo de temas en los últimos 100 días 25%
-- el menor de 25% de los temas creados en los últimos 100 días 
-- O 500, el requisito máximo predeterminado del sistema para TL3
tclhd AS (
    SELECT LEAST(floor(count(id)*.25)::REAL,500) as all_topics
    FROM topics, t
    WHERE created_at > t.start 
        AND archetype = 'regular'
        AND deleted_at is null
  ),

-- Conteo de publicaciones en los últimos 100 días 25%
-- el menor de 25% de las publicaciones creadas en los últimos 100 días 
-- O 20k, el requisito máximo predeterminado del sistema para TL3
pclhd AS (
SELECT LEAST(FLOOR(count(id)*.25)::REAL,20000) AS all_posts
FROM t, posts
WHERE posts.created_at > start 
    AND posts.deleted_at is null
    AND posts.hidden_at is null
    AND posts.last_editor_id >0  -- Omitir Discobot y Sistema
    AND (action_code is null OR action_code != 'assigned')
  ),

-- Usuarios de Nivel de Confianza 2
tl AS (
SELECT id as user_id, trust_level
FROM users
WHERE trust_level = 2
  ),

-- Usuarios, visitas y publicaciones leídas en los últimos 100 días
pr AS (
    SELECT user_id, 
        count(1) as visits,
        sum(posts_read) as posts_read
    FROM t, user_visits
    INNER JOIN tl using (user_id)
    WHERE visited_at > t.start
      AND visited_at < t.end
    GROUP BY user_id
    ORDER BY visits DESC
  ),

-- Publicaciones Leídas Todo el Tiempo
prat as (
    select user_id, 
        sum(posts_read) as posts_read
    from t, user_visits
    INNER JOIN tl using (user_id)
    group by user_id
  ),

-- Temas respondidos
trt as (
    select user_id,
           count(distinct topic_id) as topic_id
    from t, posts
    INNER JOIN tl using (user_id)
    where posts.created_at > t.start
      and posts.created_at < t.end
    group by user_id
  ),

-- Temas Vistos Todo el Tiempo
tvat as (
    select tv.user_id,
        COUNT(distinct tv.topic_id) AS topic_id
    FROM topic_views tv
    LEFT JOIN topics t on tv.topic_id=t.id
    INNER JOIN tl on tv.user_id=tl.user_id
    WHERE 
        t.archetype = 'regular'
        AND t.deleted_at is null
    group by tv.user_id
  ),

-- Temas Vistos
tva AS (
SELECT tv.user_id,
    COUNT(distinct tv.topic_id) AS topic_id
FROM t, topic_views tv
    LEFT JOIN topics on topic_id=topics.id
    INNER JOIN tl on tv.user_id=tl.user_id
    WHERE 
        topics.archetype = 'regular'
        AND topics.deleted_at is null
        AND viewed_at > t.start
        AND viewed_at < t.end
GROUP BY tv.user_id
  ),

likes AS (
    SELECT user_id,
        likes_given, likes_received
  from user_stats
  INNER JOIN tl using (user_id)
)


SELECT  pr.user_id, 
        greatest(50-coalesce(pr.visits,0),0) as "Brecha de días visitados",
        greatest(10-coalesce(trt.topic_id,0), 0)  as "Brecha de respuestas a temas",
        greatest(tclhd.all_topics-coalesce(tva.topic_id,0),0) AS "Brecha de temas vistos",
        greatest(200-coalesce(tvat.topic_id,0),0) as "Brecha de temas vistos (AT)",
        greatest(pclhd.all_posts - coalesce(pr.posts_read,0),0) as "Brecha de publicaciones leídas",
        greatest(500-coalesce(prat.posts_read,0),0) as "Brecha de publicaciones leídas (AT)",
        greatest(30-likes.likes_given,0) as "Brecha de me gusta dados",
        greatest(20-likes.likes_received,0) as "Brecha de me gusta recibidos"

FROM pclhd, tclhd, pr
left join trt using (user_id)
LEFT JOIN tva USING (user_id)
left join tvat using (user_id)
left join prat using (user_id)
LEFT JOIN likes using (user_id)


ORDER BY
  pr.visits DESC
  
LIMIT 50
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