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 (?)
「いいね！」 8
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)
「いいね！」 8
I thought about TL3 Requirements
Checking which users have the most number of 
Requirements and sort by that
「いいね！」 4
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 
「いいね！」 8
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.
「いいね！」 1
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
「いいね！」 8
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
「いいね！」 8
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?
「いいね！」 3
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
「いいね！」 2
Yes, tried that: 60, 80, 95, 99 → no effect at all, always the same error message.
「いいね！」 2
パラメータなしの修正版です。TL3の要件をクエリにハードコーディングしました。与えられた、および受け取ったいいねを含めるようにデータセットをわずかに拡張しましたが、いいね/ユニーク日数やいいね/ユニークユーザーは含まれていません。フラグ、サイレンス、サスペンションもまだ欠落しています。
これはギャップレポートなので、各ユーザーが不足しているものを表示するために減算を行います。
いくつかの場所で、ユーザー管理ページに表示されるものと正確に一致しません。
- 与えられたいいね（私のカウントはなぜか高い）
- 過去100日間の投稿（私のカウントは低い）
過去100日間の投稿のカウントにはかなりの推測が含まれています。
しかし、役立つかもしれないので：
with
t as (
select
CURRENT_TIMESTAMP - ((0 + 100) * (INTERVAL '1 days')) as start,
CURRENT_TIMESTAMP - (0 * (INTERVAL '1 days')) as end
),
-- 過去100日間のトピック数 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
),
-- 過去100日間の投稿数 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 -- Discobot & System を除外
AND (action_code is null OR action_code != 'assigned')
),
-- ユーザー
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
),
-- 返信したトピック
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
),
-- 全期間の閲覧トピック
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
),
-- 閲覧トピック
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
),
-- 読んだ投稿
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
),
-- 全期間の読んだ投稿
prat as (
select user_id,
sum(posts_read) as posts_read
from user_visits, t
group by user_id
),
-- 現在の信頼レベル
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 "訪問日数ギャップ",
greatest(10-coalesce(trt.topic_id,0), 0) as "返信トピックギャップ",
greatest(tclhd.all_topics-coalesce(tva.topic_id,0),0) AS "閲覧トピックギャップ",
greatest(200-coalesce(tvat.topic_id,0),0) as "閲覧トピック（全期間）ギャップ",
greatest(pclhd.all_posts - coalesce(pra.posts_read,0),0) as "読んだ投稿ギャップ",
greatest(500-coalesce(prat.posts_read,0),0) as "読んだ投稿（全期間）ギャップ",
greatest(30-likes.likes_given,0) as "与えたいいねギャップ",
greatest(20-likes.likes_received,0) as "受け取ったいいねギャップ"
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
「いいね！」 5
バージョンありがとうございます！
しかし、同じエラーが返ってきます。
PG::QueryCanceled: ERROR: canceling statement due to statement timeout
インストールに問題があるようですね。
「いいね！」 4
私の場合、これは現在 8,379.4 ミリ秒で実行されており、制限に近い値だと思います。コミュニティが大きいのでしょう。
最後に LIMIT 50 を追加すると、私の場合は 1k ミリ秒短縮されます。何か結果が得られるまで、それで調整してみてはいかがでしょうか。
「いいね！」 5
これで わずかに 効率が向上しました。それでも実行できない場合は、一部の列を削除し、関連する結合とクエリを削除してみてください。
編集
JOIN の種類をようやく理解しました（しばらくぶりです）。この更新されたクエリは はるかに 効率的です。
with
t as (
select
CURRENT_TIMESTAMP - ((0 + 100) * (INTERVAL '1 days')) as start,
CURRENT_TIMESTAMP - (0 * (INTERVAL '1 days')) as end
),
-- 過去100日間のトピック数 25%
-- 過去100日間に作成されたトピックの25%の小さい方
-- または 500 (TL3 のシステムデフォルト最大要件)
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
),
-- 過去100日間の投稿数 25%
-- 過去100日間に作成された投稿の25%の小さい方
-- または 20k (TL3 のシステムデフォルト最大要件)
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 -- Discobot & System を除く
AND (action_code is null OR action_code != 'assigned')
),
-- レベル2ユーザー
tl AS (
SELECT id as user_id, trust_level
FROM users
WHERE trust_level = 2
),
-- ユーザー、訪問、投稿閲覧数 過去100日
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
),
-- 投稿閲覧数 全期間
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
),
-- 返信したトピック
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
),
-- 閲覧したトピック 全期間
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
),
-- 閲覧したトピック
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 "訪問日数ギャップ",
greatest(10-coalesce(trt.topic_id,0), 0) as "返信トピックギャップ",
greatest(tclhd.all_topics-coalesce(tva.topic_id,0),0) AS "閲覧トピックギャップ",
greatest(200-coalesce(tvat.topic_id,0),0) as "閲覧トピック(AT)ギャップ",
greatest(pclhd.all_posts - coalesce(pr.posts_read,0),0) as "投稿閲覧ギャップ",
greatest(500-coalesce(prat.posts_read,0),0) as "投稿閲覧(AT)ギャップ",
greatest(30-likes.likes_given,0) as "いいね送信ギャップ",
greatest(20-likes.likes_received,0) as "いいね受信ギャップ"
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
「いいね！」 8
そして… TL2ギャップレポートです。
with
-- Trust Level 1 users
tl AS (
SELECT id as user_id, trust_level, last_seen_at
FROM users
WHERE trust_level = 1
),
-- Users seen in last 3mo + visits, posts read, reading time
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
),
-- Topics replied to
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
),
-- Topics Viewed All Time
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 "最終ログイン",
-- days visited: 15
greatest(15-coalesce(pr.visits,0),0) as "訪問日数ギャップ",
-- topic replies: 3
greatest(3-coalesce(trt.replied_count,0), 0) as "トピック返信ギャップ",
-- topics entered: 20
greatest(20-coalesce(tvat.topic_id,0),0) as "トピック閲覧ギャップ",
-- posts read: 100
greatest(100-coalesce(pr.posts_read,0),0) as "投稿閲覧ギャップ",
-- time spent reading posts: 60min
greatest(60-pr.minutes_reading_time,0) as "読書時間ギャップ",
-- likes given: 1
greatest(1-likes.likes_given,0) as "いいね送信ギャップ",
-- likes received: 1
greatest(1-likes.likes_received,0) as "いいね受信ギャップ"
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
「いいね！」 3
もう一度！
TL3のいいねは過去100日間のものだと気づいたばかりです！
それを修正しました：
WITH
t as (
select
CURRENT_TIMESTAMP - ((0 + 100) * (INTERVAL '1 days')) as start,
CURRENT_TIMESTAMP - (0 * (INTERVAL '1 days')) as end
),
-- 過去100日間のトピック数 25%
-- 過去100日間に作成されたトピックの25%の少ない方
-- または、TL3のシステムデフォルト最大要件である500
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
),
-- 過去100日間の投稿数 25%
-- 過去100日間に作成された投稿の25%の少ない方
-- または、TL3のシステムデフォルト最大要件である20k
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 -- Discobotとシステムを除く
AND (action_code is null OR action_code != 'assigned')
),
-- レベル2のユーザー
tl AS (
SELECT id as user_id
FROM users
WHERE trust_level = 2
),
-- ユーザー + 訪問数と投稿閲覧数 過去100日間
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
),
-- 全期間の投稿閲覧数
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
),
-- 返信したトピック
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
),
-- 全期間のトピック閲覧数
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
),
-- トピック閲覧数
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 "過去100日間の訪問日数ギャップ",
greatest(10-coalesce(trt.replied_count,0), 0) as "トピック返信ギャップ",
greatest(tclhd.all_topics-coalesce(tva.topic_id,0),0) AS "過去100日間のトピック閲覧ギャップ（150）",
greatest(200-coalesce(tvat.topic_id,0),0) as "トピック閲覧ギャップ（全期間）",
greatest(pclhd.all_posts - coalesce(pr.posts_read,0),0) as "過去100日間の投稿閲覧ギャップ（250）",
greatest(500-coalesce(prat.posts_read,0),0) as "投稿閲覧ギャップ（全期間）",
GREATEST(30-COALESCE(likes_given_lhd,0),0) as "過去100日間のいいね送信ギャップ",
GREATEST(20-COALESCE(likes_received_lhd,0),0) as "過去100日間のいいね受信ギャップ"
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
「いいね！」 6
@alefattorini これはギャップレポートです。列が空の場合、ユーザーはその要件にギャップがありません。したがって、最初のユーザーはTL3の資格がほぼあり、ギャップは25件の「いいね！」を付け、15件を受け取ることだけです。
意味が通じますか？
「いいね！」 5
はい、ありがとうございます。tl3パラメータを調整しています。
「いいね！」 2