Is there a method to get a sorted list of users who might become Trust Level 3?
Maybe using the Data Explorer plugin and a query (?)
8 Me gusta
That’s an interesting question. There will be no specific query since each member ‘earns’ TL3 through interaction and engagement, but you could monitor the TL2 users to see who are visiting most regularly and engaging with more content I suppose.
Is there a reason to find this in advance rather than waiting to see who earns it?
Some third party measurement tools create ‘leaderboards’ that might point to members who have been particularly active. Is that what you need?
In the past I have also created queries in excel based on data exported from the Users table and custom Data Explorer queries. I didn’t look at what you are asking, but did create monitoring tools to look at different types of activity, such as reading and posting, to better segment my members.
Let us know what you are trying to achieve and maybe we could come up with cleverer suggestions.
(also, this should probably be moved to community where we can discuss these topics)
8 Me gusta
I thought about TL3 Requirements
Checking which users have the most number of 
Requirements and sort by that
4 Me gusta
You could do that, write a query to track the key fields and limit it to current TL2 users
There are loads of great query ideas for Data Explorer in another thread, and it seems that you could do a version of the User Directory, with the TL2 limit, to answer your query.
Still interested to know what you are trying to achieve in trying to ‘predict’ TL3 before it happens. Sounds like Minority Report 
8 Me gusta
Though I have no doubt that some form of query could be put together, I have serious doubt that the amount of work needed would justify the questionable value of the results.
It is one thing to do this per user from a members admin user page, a whole different story for many accounts all at once.
At best, there will be many “moving parts” to take into consideration and arbitrary values to be decided on.
Some criteria could be used to reduce the “haystack”. i.e. only TL2 accounts that are not already TL3, accounts that are activated and not suspended. That might help somewhat.
Because many of the requirements may have been tweaked from their default values, those values would be needed to base a members values against.
Even then, most member values are unpredictable and unstable. eg. Likes could be given / received at any time changing a “0 - requirements not met” to “requirements met” in a heartbeat. Similar with flags given / received.
And what constitutes an “almost TL3” state? How many of the 12 requirements are already met? A percentage? eg.
if (value < requirement)
&& ((value / requirement) > arbitrary_percent) {
The “all time” values should in theory stagnate or increase only. But the “100 days” could be a problem. Should an algorithm somehow “drop” values associated with older days when it is trying to predict values for future days?
Anyway, long story short, if you can put together exact detailed specifications for how such a feature could work it would make it easier for someone to come up with the code needed to meet those specs.
1 me gusta
I have the beginnings of this progress towards level 3 report which allows admins to view the progress of users so far, which I want to then use to email out messages of encouragement to users who are close (We like to promote TL3 user who share our tone of voice to moderators)
Someone kindly sent me the the trust level 3 requirements rb file which has helped a lot. however my limited knowledge and understanding how to convert the fields within the document into sql is limited, Maybe someone can help finish it off?
This is what I have so far.
Data Explorer Query
-- [params]
-- int :from_days_ago = 0
-- int :duration_days = 100
with
t as (
select
CURRENT_TIMESTAMP - ((:from_days_ago + :duration_days) * (INTERVAL '1 days')) as start,
CURRENT_TIMESTAMP - (:from_days_ago * (INTERVAL '1 days')) as end
),
-- Users
pr AS (
SELECT user_id,
count(1) as visits
FROM user_visits, t
WHERE visited_at > t.start
and visited_at < t.end
GROUP BY user_id
ORDER BY visits DESC
),
-- Visits (all time)
vi as (
select user_id,
count(1) as visits
from user_visits, t
group by user_id
),
-- Topics replied to
trt as (
select user_id,
count(distinct topic_id) as topic_id
from posts, t
where created_at > t.start
and created_at < t.end
group by user_id
),
-- Topics Viewed All Time
tva as (
select user_id,
count(topic_id) as topic_id
from posts
group by user_id
),
-- Posts Read
pra as (
select user_id,
sum(posts_read) as posts_read
from user_visits, t
where visited_at > t.start
and visited_at < t.end
group by user_id
),
-- Posts Read All Time
prat as (
select user_id,
sum(posts_read) as posts_read
from user_visits, t
group by user_id
)
SELECT pr.user_id,
coalesce(pr.visits,0) as "Visits",
coalesce(trt.topic_id,0) as "Topic replied to",
coalesce(tva.topic_id,0) as "Topic viewed (AT)",
coalesce(pra.posts_read,0) as "Posts Read",
coalesce(prat.posts_read,0) as "Posts Read (AT)"
FROM pr
left join vi using (user_id)
left join trt using (user_id)
left join tva using (user_id)
left join pra using (user_id)
left join prat using (user_id)
ORDER BY
pr.visits DESC
8 Me gusta
Great start here, thanks!
I made a few tweaks / fixes:
- Added ‘posts_read > 0’ condition for more accurate user visits calculation
- Removed ‘visits (all time)’ which didn’t seem to be necessary
- Fixed ‘topics viewed’ calculations which was using the wrong table
- Added current trust level (to only get tl2 users)
- Added where clauses for other relevant conditions, set at 50% of current threshold
Also parameterized a bunch of things so you can set your own values for each of the required metrics (since they may vary forum by forum), and also set a threshold percentage to show only users who meet at least that % of ALL the metrics.
So for example the below by default lists only tl2 users who meet 50% or more of all the requirements for visits, topics replied to, topics viewed, posts read…you could set it to 30% or 85% or whatever if it seems to be returning too many or too few results.
I did not add the requirements for likes given/received, or for flags/silences/suspensions. For us at least, the latter are super rare anyway, and I figure likes is one of the easier barriers to get people over if they know about it (some people just barely ever give likes). So this works pretty well for us. But the rest of the requirements could be added if you wanted.
For reference, on our forum we have ~1,000 TL2 users, ~10 TL3 users, and this query identifies ~30 ‘potential/almost TL3’ users with the 50% threshold.
-- [params]
-- int :from_days_ago = 0
-- int :duration_days = 100
-- int :trust_level = 2
-- int :threshold = 50
-- int :visits = 50
-- int :topics_replied_to = 10
-- int :topics_viewed = 76
-- int :topics_viewed_all_time = 200
-- int :posts_read = 755
-- int :posts_read_all_time = 500
-- NOTES
-- trust_level show current TL2 users only
-- threshold show only at users >= this percentage of all above metrics
-- topics_viewed depends on total # of topics (default 25%)
-- posts_read depends on total # of posts (default 25%)
WITH
t AS (
SELECT
CURRENT_TIMESTAMP - ((:from_days_ago + :duration_days) * (INTERVAL '1 days')) AS start,
CURRENT_TIMESTAMP - (:from_days_ago * (INTERVAL '1 days')) AS end
),
-- User Visits
pr AS (
SELECT user_id,
count(1) as visits
FROM user_visits, t
WHERE visited_at > t.start
AND visited_at < t.end
AND posts_read > 0
GROUP BY user_id
ORDER BY visits DESC
),
-- Topics Replied To
trt AS (
SELECT user_id,
COUNT(distinct topic_id) AS topic_id
FROM posts, t
WHERE created_at > t.start
AND created_at < t.end
GROUP BY user_id
),
-- Topics Viewed
tva AS (
SELECT user_id,
COUNT(distinct topic_id) AS topic_id
FROM topic_views, t
WHERE viewed_at > t.start
AND viewed_at < t.end
GROUP BY user_id
),
-- Topics Viewed (All Time)
tvat AS (
SELECT user_id,
COUNT(distinct topic_id) AS topic_id
FROM topic_views
GROUP BY user_id
),
-- Posts Read
pra AS (
SELECT user_id,
SUM(posts_read) AS posts_read
FROM user_visits, t
WHERE visited_at > t.start
AND visited_at < t.end
GROUP BY user_id
),
-- Posts Read (All Time)
prat AS (
SELECT user_id,
SUM(posts_read) AS posts_read
FROM user_visits, t
GROUP BY user_id
),
-- Current Trust Level
tl AS (
SELECT id,
trust_level
FROM users
)
SELECT pr.user_id,
-- tl.trust_level AS "Trust Level",
coalesce(pr.visits,0) AS "Visits",
coalesce(trt.topic_id,0) AS "Topic Replied To",
coalesce(tva.topic_id,0) AS "Topics Viewed",
coalesce(tvat.topic_id,0) AS "Topics Viewed (AT)",
coalesce(pra.posts_read,0) AS "Posts Read",
coalesce(prat.posts_read,0) AS "Posts Read (AT)"
FROM pr
LEFT JOIN trt USING (user_id)
LEFT JOIN tva USING (user_id)
LEFT JOIN tvat USING (user_id)
LEFT JOIN pra USING (user_id)
LEFT JOIN prat USING (user_id)
LEFT JOIN tl ON (tl.id = pr.user_id)
WHERE
tl.trust_level = :trust_level
AND pr.visits >= :visits * :threshold / 100
AND trt.topic_id >= :topics_replied_to * :threshold / 100
AND tva.topic_id >= :topics_viewed * :threshold / 100
AND tvat.topic_id >= :topics_viewed_all_time * :threshold / 100
AND pra.posts_read >= :posts_read * :threshold / 100
AND prat.posts_read >= :posts_read_all_time * :threshold / 100
ORDER BY
pr.visits DESC
8 Me gusta
This seems to be exactly what I am searching for, however, I get the following error when executing the query:
PG::QueryCanceled: ERROR: canceling statement due to statement timeout
Any ideas how to make this work?
3 Me gusta
Hello,
This report returns
- Total topics
- Total topics in AT
but the requirements for TL3 use
- Total topics excluding private messages.
- Total topics in AT excluding private messages.
Anyone knows how to adapt the query to exclude the private messages?
Thanks in advance
2 Me gusta
Yes, tried that: 60, 80, 95, 99 → no effect at all, always the same error message.
2 Me gusta
Aquí tienes una versión modificada sin parámetros: He codificado de forma perezosa (¿eficiente?) los requisitos predeterminados de TL3 en la consulta. He ampliado ligeramente el conjunto de datos para incluir los “me gusta” dados y recibidos, aunque no los “me gusta” por días únicos o “me gusta” por usuarios únicos. Las banderas, silencios y suspensiones también siguen faltando.
Este es un informe de brechas, por lo que realiza la resta para mostrarte lo que le falta a cada usuario.
En un par de lugares, no coincide exactamente con lo que aparece en la página de administración de usuarios:
- “Me gusta” dados (mi recuento es de alguna manera mayor)
- Publicaciones en los últimos 100 días (mi recuento es menor)
Hay bastante suposición en mi recuento de las publicaciones de los últimos 100 días.
Pero por si acaso es útil:
with
t as (
select
CURRENT_TIMESTAMP - ((0 + 100) * (INTERVAL '1 days')) as start,
CURRENT_TIMESTAMP - (0 * (INTERVAL '1 days')) as end
),
-- Recuento de temas en los últimos 100 días 25%
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
),
-- Recuento de publicaciones en los últimos 100 días 25%
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
pr AS (
SELECT user_id,
count(1) as visits
FROM user_visits, t
WHERE visited_at > t.start
AND visited_at < t.end
GROUP BY user_id
ORDER BY visits DESC
),
-- Temas respondidos
trt as (
select user_id,
count(distinct topic_id) as topic_id
from posts, t
where created_at > t.start
and created_at < t.end
group by user_id
),
-- Temas vistos en todo momento
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
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
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
),
-- Publicaciones leídas
pra as (
select user_id,
sum(posts_read) as posts_read
from user_visits, t
where visited_at > t.start
and visited_at < t.end
group by user_id
),
-- Publicaciones leídas en todo momento
prat as (
select user_id,
sum(posts_read) as posts_read
from user_visits, t
group by user_id
),
-- Nivel de confianza actual
tl AS (
SELECT id,
trust_level
FROM users
),
likes AS (
SELECT user_id,
likes_given, likes_received
from user_stats
)
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 respuesta 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(pra.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 pra using (user_id)
left join prat using (user_id)
LEFT JOIN likes using (user_id)
LEFT JOIN tl ON (tl.id = pr.user_id)
WHERE tl.trust_level = 2
ORDER BY
pr.visits DESC
5 Me gusta
¡Gracias por tu versión!
Sin embargo, sigo recibiendo el mismo error
PG::QueryCanceled: ERROR: canceling statement due to statement timeout
Supongo que entonces tenemos un problema con nuestra instalación.
4 Me gusta
Para mí, esto se ejecuta actualmente en 8.379,4 ms, así que está cerca del límite, supongo. Debes tener una comunidad más grande.
Añadir LIMIT 50 al final me ahorra 1k ms. Quizás podrías jugar con eso hasta que obtengas algo.
5 Me gusta
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
8 Me gusta
Y… aquí está el informe de brecha de TL2:
with
-- Usuarios de Nivel de Confianza 1
tl AS (
SELECT id as user_id, trust_level, last_seen_at
FROM users
WHERE trust_level = 1
),
-- Usuarios vistos en los últimos 3 meses + visitas, publicaciones leídas, tiempo de lectura
pr AS (
SELECT user_id,
count(1) as visits,
sum(posts_read) as posts_read,
SUM(time_read)/60 as minutes_reading_time,
DATE(last_seen_at) AS last_seen
FROM user_visits
INNER JOIN tl using (user_id)
WHERE DATE(last_seen_at) >= CURRENT_DATE - INTERVAL '3 month'
GROUP BY user_id, last_seen
ORDER BY visits, last_seen DESC
),
-- Temas respondidos
trt as (
select posts.user_id,
count(distinct topic_id) as replied_count
from posts
INNER JOIN tl using (user_id)
INNER JOIN topics ON topics.id = posts.topic_id
WHERE topics.user_id <> posts.user_id
AND posts.deleted_at IS NULL AND topics.deleted_at IS NULL
-- AND topics.archetype <> 'private_message'
AND archetype = 'regular'
GROUP BY posts.user_id
ORDER BY replied_count DESC
),
-- Temas vistos en todo momento
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
),
likes AS (
SELECT user_id,
likes_given, likes_received
from user_stats
INNER JOIN tl using (user_id)
)
SELECT pr.user_id,
pr.last_seen as "Última vez visto",
-- días visitados: 15
greatest(15-coalesce(pr.visits,0),0) as "Brecha días visitados",
-- respuestas a temas: 3
greatest(3-coalesce(trt.replied_count,0), 0) as "Brecha respuestas temas",
-- temas ingresados: 20
greatest(20-coalesce(tvat.topic_id,0),0) as "Brecha temas vistos",
-- publicaciones leídas: 100
greatest(100-coalesce(pr.posts_read,0),0) as "Brecha publicaciones leídas",
-- tiempo dedicado a leer publicaciones: 60min
greatest(60-pr.minutes_reading_time,0) as "Brecha tiempo de lectura",
-- me gusta dados: 1
greatest(1-likes.likes_given,0) as "Brecha me gusta dados",
-- me gusta recibidos: 1
greatest(1-likes.likes_received,0) as "Brecha me gusta recibidos"
FROM pr
left join trt using (user_id)
left join tvat using (user_id)
LEFT JOIN likes using (user_id)
ORDER BY
pr.visits DESC
LIMIT 500
3 Me gusta
¡Una vez más!
Me acabo de dar cuenta de que los “me gusta” para TL3 son de los últimos 100 días. 
Corregido para eso:
WITH
t as (
select
CURRENT_TIMESTAMP - ((0 + 100) * (INTERVAL '1 days')) as start,
CURRENT_TIMESTAMP - (0 * (INTERVAL '1 days')) as end
),
-- Conteo de temas 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 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
FROM users
WHERE trust_level = 2
),
-- Usuarios + visitas y publicaciones leídas 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 posts.user_id,
count(distinct topic_id) as replied_count
from t, posts
INNER JOIN tl using (user_id)
INNER JOIN topics ON topics.id = posts.topic_id
WHERE posts.created_at > t.start
AND posts.created_at < t.end
AND topics.user_id <> posts.user_id
AND posts.deleted_at IS NULL AND topics.deleted_at IS NULL
AND archetype = 'regular'
group by posts.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_received_lhd AS (
SELECT ua.user_id
, count(*) as likes_received_lhd
FROM t, user_actions ua
JOIN posts p on p.id=ua.target_post_id
JOIN tl on ua.user_id=tl.user_id
WHERE ua.action_type=1
AND ua.created_at > t.start
AND ua.created_at < t.end
GROUP BY ua.user_id
),
likes_given_lhd AS (
SELECT user_id, count(*) as likes_given_lhd
FROM t, given_daily_likes
INNER JOIN tl using (user_id)
WHERE given_date > t.start
AND given_date < t.end
GROUP BY user_id
)
SELECT pr.user_id,
greatest(50-coalesce(pr.visits,0),0) as "Días de visita faltantes últimos 100 días",
greatest(10-coalesce(trt.replied_count,0), 0) as "Falta de respuestas en temas",
greatest(tclhd.all_topics-coalesce(tva.topic_id,0),0) AS "Falta de temas vistos últimos 100 días de 150",
greatest(200-coalesce(tvat.topic_id,0),0) as "Falta de temas vistos (AT)",
greatest(pclhd.all_posts - coalesce(pr.posts_read,0),0) as "Falta de publicaciones leídas últimos 100 días de 250",
greatest(500-coalesce(prat.posts_read,0),0) as "Falta de publicaciones leídas (AT)",
GREATEST(30-COALESCE(likes_given_lhd,0),0) as "Falta de me gusta dados últimos 100 días",
GREATEST(20-COALESCE(likes_received_lhd,0),0) as "Falta de me gusta recibidos últimos 100 días"
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_received_lhd using (user_id)
LEFT JOIN likes_given_lhd using (user_id)
ORDER BY pr.visits DESC
LIMIT 25
6 Me gusta
@alefattorini es un informe de brechas. Cuando las columnas están vacías, el usuario no tiene brechas para ese requisito. Por lo tanto, tu primer usuario está casi calificado para TL3 y su única brecha es dar 25 me gusta y recibir 15.
¿Tiene sentido?
5 Me gusta
¡Sí! Gracias. Estoy ajustando mis parámetros tl3
2 Me gusta