Guia de referência do relatório do painel de administração

[Discourse]

This is a reference guide for describing how the Admin Dashboard Reports function, the data they’re displaying, the corresponding Data Explorer SQL queries, and where to find the Ruby code for each report.

Required user level: Staff

Discourse contains several built-in admin dashboard Reports that can be useful for exploring stats about a community. To access these reports, you can visit discourse.example.com/admin/dashboard/reports on your site ( or click the Reports link at the top of the dashboard). Note that only staff users will have access to these reports.

Data from all users on a site is included in these reports (including staff activity like visiting admin pages). The only condition that is put on users in the reports is that they are ‘real’ users, which is used to exclude the system user from the reports.

Plugins can also add reports to the dashboard with add_report(name, &block).

Ruby models for most reports are located at: discourse/app/models/concerns/reports/. Some reports also reference: discourse/app/models/report.rb

The dashboard-sql topics contain all of the corresponding SQL queries that can be used to generate reports identical to the Admin Dashboard Reports. These queries can be used within the Data Explorer plugin and for Running Data Explorer queries with the Discourse API

Accepted solutions

Displays daily tally of posts marked as solutions.

Ruby code: discourse-solved/plugin.rb at main · discourse/discourse-solved · GitHub

SQL Query: Dashboard Report - Accepted Solutions

Admin Logins

List of admin login times with locations.

Ruby Code: discourse/app/models/concerns/reports/staff_logins.rb

SQL Query: Dashboard Report - Admin Logins

Anonymous

Number of new pageviews by visitors not logged in to an account.

Ruby Code: discourse/app/models/concerns/reports/consolidated_page_views.rb

SQL Query: Dashboard Report - Anonymous

Bookmarks

Number of new topics and posts bookmarked.

Ruby Code: discourse/app/models/concerns/reports/bookmarks.rb

SQL Query: Dashboard Report - Bookmarks

Consolidated API Requests

API usage statistics by date, tracking both regular API requests and user API requests.

Ruby Code: discourse/app/models/concerns/reports/consolidated_api_requests.rb at main · discourse/discourse · GitHub

SQL Query: Dashboard Report - Consolidated API Requests

Consolidated Pageviews

Pageviews for logged in users, anonymous users and crawlers.

Ruby Code: discourse/app/models/concerns/reports/consolidated_page_views.rb

SQL Query: Dashboard Report - Consolidated Pageviews

Consolidated Pageviews with Browser Detection (Experimental)

Pageviews for logged in users, anonymous users, known crawlers and other. This experimental report ensures logged-in/anon requests are coming from real browsers before counting them.

Ruby Code: discourse/app/models/concerns/reports/consolidated_page_views_browser_detection.rb

SQL Query: Dashboard Report - Consolidated Pageviews with Browser Detection

DAU/MAU

Number of members that logged in in the last day divided by number of members that logged in in the last month – returns a % which indicates community ‘stickiness’. Aim for >20%.

Ruby Code: discourse/app/models/concerns/reports/dau_by_mau.rb

SQL Query: Dashboard Report - DAU/MAU

Daily Engaged Users

Number of users that have liked or posted in the last day.

Ruby Code: discourse/app/models/concerns/reports/daily_engaged_users.rb

SQL Query: Dashboard Report - Daily Engaged Users

Emails Sent

Number of new emails sent.

Ruby Code: discourse/app/models/concerns/reports/emails.rb

SQL Query: Dashboard Report - Emails Sent

Flags

Number of new flags.

Ruby Code: discourse/app/models/concerns/reports/flags.rb

SQL Query: Dashboard Report - Flags

Flags Status

List of flags’ statuses including type of flag, poster, flagger, and time to resolution.

Ruby Code: discourse/app/models/concerns/reports/flags_status.rb

SQL Query: Dashboard Report - Flags Status

Likes

Number of new likes.

Ruby Code: discourse/app/models/concerns/reports/likes.rb

SQL Query: Dashboard Report - Likes

Logged In

Number of new pageviews from logged in users.

Ruby Code: discourse/app/controllers/admin/reports_controller.rb#L5

SQL Query: Dashboard Report - Logged In

Moderator Activity

List of moderator activity including flags reviewed, reading time, topics created, posts created, personal messages created, and revisions.

SQL Query: Dashboard Report - Moderator Activity

Moderator Warning

Number of warnings sent by personal messages from moderators.

Ruby Code: discourse/app/models/concerns/reports/moderator_warning_private_messages.rb

SQL Query: Dashboard Report - Moderator Warnings

New Contributors

Number of users who made their first post during this period.

Ruby Code: discourse/app/models/concerns/reports/new_contributors.rb

SQL Query: Dashboard Report - New Contributors

Notify Moderators

Number of times moderators have been privately notified by a flag.

Ruby Code: discourse/app/models/concerns/reports/notify_moderators_private_messages.rb

SQL Query: Dashboard Report - Notify Moderators

Notify User

Number of times users have been privately notified by a flag.

Ruby Code: discourse/app/models/concerns/reports/notify_user_private_messages.rb

SQL Query: Dashboard Report - Notify User

Overall Sentiment

Number of posts classified either positive or negative with the “Sentiment” AI, over a specified period.

Ruby Code: discourse-ai/lib/sentiment/entry_point.rb at main · discourse/discourse-ai · GitHub

SQL Query: Dashboard Report - Overall Sentiment

Pageviews

Number of new pageviews from all visitors. Same as the total for Consolidated Pageviews.

Discourse uses the follow query to determine total pageviews:

SQL Query: Dashboard Report - Consolidated Pageviews

Post Edits

Number of new post edits.

Ruby Code: discourse/app/models/concerns/reports/post_edits.rb

SQL Query: Dashboard Report - Post Edits

Posts

New posts created during the selected time period

Ruby Code: discourse/app/models/concerns/reports/posts.rb

SQL Query: Dashboard Report - Posts

Post Emotion

Number of posts classified by AI with one of following emotions: Sadness, Surprise, Fear, Anger, Joy, Disgust - group by poster trust level, over a specified period.

Ruby Code: discourse-ai/lib/sentiment/entry_point.rb at main · discourse/discourse-ai · GitHub

SQL Query: Dashboard Report - Post Emotion

Reactions

List most recent reactions.

Ruby code: discourse-reactions/plugin.rb at main · discourse/discourse-reactions · GitHub

SQL Query: Dashboard Report - Reactions

Signups

New account registrations for this period.

Ruby Code: discourse/app/models/concerns/reports/signups.rb

SQL Query: Dashboard Report - Signups

Site Traffic

Ruby Code: discourse/app/models/concerns/reports/site_traffic.rb

SQL Query: Dashboard Report - Site Traffic

Suspicious Logins

Details of new logins that differ suspiciously from previous logins.

Ruby Code: discourse/app/models/concerns/reports/suspicious_logins.rb

SQL Query: Dashboard Report - Suspicious Logins

System

Number of personal messages sent automatically by the System.

Ruby Code: discourse/app/models/concerns/reports/system_private_messages.rb

SQL Query: Dashboard Report - System

Time to first response

Average time (in hours) of the first response to new topics.

Ruby Code: discourse/app/models/concerns/reports/time_to_first_response.rb + discourse/discourse/blob/main/app/models/topic.rb#L1799-L1844

SQL Query: Dashboard Report - Time to First Response

Top Ignored / Muted Users

Users who have been muted and/or ignored by many other users.

Ruby Code: discourse/app/models/concerns/reports/top_ignored_users.rb

SQL Query: Dashboard Report - Top Ignored / Muted Users

Top Referred Topics

Topics that have received the most clicks from external sources.

Ruby Code: discourse/app/models/concerns/reports/top_referred_topics.rb

SQL Query: Dashboard Report - Top Referred Topics

Top Referrers

Users listed by number of clicks on links they have shared.

Ruby Code: discourse/app/models/concerns/reports/top_referrers.rb

SQL Query: Dashboard Report - Top Referrers

Top Traffic Sources

External sources that have linked to this site the most.

Ruby Code: discourse/app/models/concerns/reports/top_traffic_sources.rb

SQL Query: Dashboard Report - Top Traffic Sources

Top Uploads

List all uploads by extension, filesize and author.

Ruby Code: discourse/app/models/concerns/reports/top_uploads.rb

SQL Query: Dashboard Report - Top Uploads

Top Users by likes received

Top 10 users who have received likes.

Ruby Code: discourse/app/models/concerns/reports/top_users_by_likes_received.rb

SQL Query: Dashboard Report - Top Users by Likes Received

Top Users by likes received from a user with a lower trust level

Top 10 users in a higher trust level being liked by people in a lower trust level.

Ruby Code: discourse/app/models/concerns/reports/top_users_by_likes_received_from_inferior_trust_level.rb

SQL Query: Dashboard Report - Top Users by Likes Received from a User with a Lower Trust Level

Top Users by likes received from a variety of people

Top 10 users who have had likes from a wide range of people.

Ruby Code: discourse/app/models/concerns/reports/top_users_by_likes_received_from_a_variety_of_people.rb

SQL Query: Dashboard Report - Top Users by Likes Received From a Variety of People

Topics

New topics created during this period.

Ruby Code: discourse/app/models/concerns/reports/topics.rb

SQL Query: Dashboard Report - Topics

Topics with no response

Number of new topics created that did not receive a response.

Ruby Code: discourse/app/models/concerns/reports/topics_with_no_response.rb

SQL Query: Dashboard Report - Topics with No Response

Topic View Stats

Ruby Code: discourse/app/models/concerns/reports/topic_view_stats.rb

SQL Query: Dashboard Report - Topic View Stats

Trending Search Terms

Most popular search terms with their click-through rates.

Ruby Code: discourse/app/models/concerns/reports/trending_search.rb

SQL Query: Dashboard Report - Trending Search Terms

Trust Level growth

Number of users who increased their Trust Level during this period.

The Trust Level Growth report is pulling data from the user_histories table in the Discourse database. Specifically, this report is counting the number of times a user_histories.action is recorded for an increase in a user trust level.

Ruby Code: discourse/app/models/concerns/reports/trust_level_growth.rb

SQL Query: Dashboard Report - Trust Level Growth

Unaccepted policies

This dashboard report identifies topics with policies that have not been accepted by certain users.

Ruby code: discourse-policy/plugin.rb at main · discourse/discourse-policy · GitHub

SQL Query: Dashboard Report - Unaccepted Policies

User Flagging Ratio

List of users ordered by ratio of staff response to their flags (disagreed to agreed).

Ruby Code: discourse/app/models/concerns/reports/user_flagging_ratio.rb

SQL Query: Dashboard Report - User Flagging Ratio

User notes

List most recent user notes.

Ruby code: discourse-user-notes/plugin.rb at main · discourse/discourse-user-notes · GitHub

SQL Query: Dashboard Report - User Notes

User Profile Views

Total new views of user profiles.

Ruby Code: discourse/app/models/concerns/reports/profile_views.rb

SQL Query: Dashboard Report - User Profile Views

User Visits

The total number of logged-in user visits in the forum for the selected time period (today, yesterday, last 7 days, etc).

A User Visit is counted anytime a unique logged in user visits the site, up to once per day. For example, if a user visited a site every day within a week, Discourse would count that as 7 user visits.

Ruby Code: discourse/app/models/concerns/reports/visits.rb

SQL Query: Dashboard Report - User Visits

User Visits (mobile)

Number of unique logged-in users who visited using a mobile device.

Ruby Code: discourse/app/models/concerns/reports/mobile_visits.rb

SQL Query: Dashboard Report - User Visits

User-to-User (excluding replies)

Number of newly initiated personal messages.

Ruby Code: discourse/app/models/concerns/reports/user_to_user_private_messages.rb

SQL Query: Dashboard Report - User-to-User

User-to-User (with replies)

Number of all new personal messages and responses.

Ruby Code: discourse/app/models/concerns/reports/user_to_user_private_messages_with_replies.rb

SQL Query: Dashboard Report - User-to-User

Users per Trust Level

Number of users grouped by trust level.

Ruby Code: discourse/app/models/concerns/reports/users_by_trust_level.rb

SQL Query: Dashboard Report - Users Per Trust Level

Users per Type

Number of users grouped by admin, moderator, suspended, and silenced.

Ruby Code: discourse/app/models/concerns/reports/users_by_type.rb

SQL Query: Dashboard Report - Users Per Type

Web Crawler Pageviews

Total pageviews from web crawlers over time.

Ruby Code: discourse/app/models/report.rb

SQL Query: Dashboard Report - Web Crawler Pageviews

Web Crawler User Agents

List of web crawler user agents, sorted by pageviews.

Ruby Code: discourse/app/models/concerns/reports/web_crawlers.rb

SQL Query: Dashboard Report - Web Crawler User Agents

Last edited by @SaraDev 2025-10-15T20:49:23Z

Last checked by @SaraDev 2025-01-28T21:42:37Z

Check document

Perform check on document:

[pfaffman (Jay Pfaffman)]

@SaraDev

O Discourse contém vários relatórios integrados no Painel de Administração que podem ser úteis para explorar estatísticas sobre uma comunidade. Para acessar esses relatórios, você pode visitar /admin/dashboard/reports em seu site.

Não vejo um link para isso em /admin. Estou deixando de ler? Pareceria que isso deveria ser mais fácil de descobrir. Acho que eu sabia que esses relatórios estavam aqui, mas procurei e não consegui encontrá-los.

Embora tenha levado apenas alguns minutos para encontrar, pode ser bom adicionar algo como

Plugins podem adicionar relatórios ao painel com add_report(name, &block).

[maiki]

@pfaffman

Não vejo um link para isso em /admin.

@pfaffman

Pareceria que isso deveria ser mais fácil de descobrir. Acho que eu sabia que esses relatórios estavam aqui, mas procurei e não os encontrei.

Sim, seria bom em uma mensagem privada para a equipe mencionar eles quando um site é criado pela primeira vez.

[pfaffman (Jay Pfaffman)]

Desculpe. Eu achava que já tinha visto isso em algum lugar antes.

Você simplesmente não consegue fazer as pessoas lerem as coisas. . . . Exceto que eu poderia ler o código-fonte para descobrir como fazer isso em um plugin?

Mas talvez atualizar o acima para

@SaraDev

. Para acessar esses relatórios, você pode visitar /admin/dashboard/reports em seu site ou clicar no link relatórios no painel.

Acho que foi isso que realmente me confundiu. (Mas não, não tenho desculpa.)

[maiki]

@pfaffman

Mas talvez atualize o acima para

Eu fiz o tópico ser um wiki, vá em frente!

[hello-smile6 (9pfs)]

@SaraDev

Almece \u003e30%.

Isso não corresponde à interface do usuário (a interface do usuário usa 20%), qual deles deve ser?

[JammyDodger]

Boa observação. Foi atualizado recentemente para 20%. Farei a alteração no OP.

Is there a difference in target retention rate between a support-first forum and discussion-first forum?

Here’s a PR with that change: Longer term, I think a more nuanced approach could be powerful. I’d love for communities to be able to set their own goals (with some guidance like what you shared above about why they might choose one vs. the other) and use the dashboard or other related features to help them track their results vs. what they are aiming for.

[Yotam_Hagay]

@SaraDev

Principais Fontes de Tráfego

Fontes externas que mais se vincularam a este site.

Código Ruby: discourse/app/models/concerns/reports/top_traffic_sources.rb

Olá @SaraDev Este resultado do relatório pode ser obtido com uma consulta SQL? Você pode compartilhá-la?
Obrigado

[SaraDev (Sara Devlaeminck)]

@Yotam_Hagay

Olá @SaraDev, este relatório pode ser obtido com uma consulta SQL? Você pode compartilhá-la?
Obrigado

Sim, você pode usar o seguinte relatório SQL para Principais Fontes de Tráfego:

-- [params]
-- date :start_date = 01/05/2023
-- date :end_date = 03/06/2023

WITH count_links AS (

SELECT COUNT(*) AS clicks,
       ind.name AS domain
FROM incoming_links il
  INNER JOIN posts p ON p.deleted_at ISNULL AND p.id = il.post_id
  INNER JOIN topics t ON t.deleted_at ISNULL AND t.id = p.topic_id
  INNER JOIN incoming_referers ir ON ir.id = il.incoming_referer_id
  INNER JOIN incoming_domains ind ON ind.id = ir.incoming_domain_id
WHERE t.archetype = 'regular'
  AND il.created_at::date BETWEEN :start_date AND :end_date
GROUP BY ind.name
ORDER BY clicks DESC
),

count_topics AS (

SELECT COUNT(DISTINCT p.topic_id) AS topics,
       ind.name AS domain
FROM incoming_links il
INNER JOIN posts p ON p.deleted_at ISNULL AND p.id = il.post_id
INNER JOIN topics t ON t.deleted_at ISNULL AND t.id = p.topic_id
INNER JOIN incoming_referers ir ON ir.id = il.incoming_referer_id
INNER JOIN incoming_domains ind ON ind.id = ir.incoming_domain_id
WHERE t.archetype = 'regular'
  AND il.created_at > (CURRENT_TIMESTAMP - INTERVAL '30 DAYS')
GROUP BY ind.name
)

SELECT cl.domain,
       cl.clicks AS "Clicks",
       ct.topics AS "Topics"
FROM count_links cl
JOIN count_topics ct ON cl.domain = ct.domain
LIMIT 10

Com esta consulta, observe que os parâmetros de data aceitam datas no formato dia/mês/ano.

[Yotam_Hagay]

@SaraDev

Sim, você pode usar o seguinte relatório SQL para Principais Fontes de Tráfego:

Olá @SaraDev, obrigado por compartilhar a consulta.
Uma pergunta mais geral sobre este relatório e a tabela incoming_links na verdade - ela representa apenas o tráfego para páginas de posts e não o tráfego para todas as páginas do fórum, certo?

Contexto: Estou procurando analisar as tendências do tráfego geral do fórum e esperava obter o tráfego geral por fontes do relatório Principais Fontes de Tráfego.
Mas enquanto o tráfego geral é de ~ 272 mil no último mês (usuários e anônimos), os cliques totais no relatório de fontes de tráfego para o mesmo período são de apenas 59 mil.
Além disso, vejo que você usa inner join com as tabelas topics e posts, o que significa que se não houver post_id associado ao clique, você não o conta.

Você pode confirmar minha conclusão e talvez explicar um pouco sobre a lógica por trás da tabela incoming_links?

[Yotam_Hagay]

@SaraDev

Posts

Novas postagens criadas durante este período

Olá @SaraDev, executei esta consulta e o resultado não corresponde exatamente ao relatório de Posts na guia geral.
Por exemplo, para 30 de novembro:
Consulta = 112 posts
Relatório = 120 posts
Você pode verificar a diferença?
Obrigado

[JammyDodger]

Apenas um aviso para você, @Yotam_Hagay - mesmo que a Sara seja a OP, o guia é responsabilidade de todos Não há necessidade de uma @menção em cada postagem.

[Yotam_Hagay]

Obrigado @JammyDodger por esclarecer.
Há mais alguém que eu possa marcar ou recorrer para obter uma resposta?

[Yotam_Hagay]

@SaraDev

Tempo de resposta para a primeira resposta em SQL

--[params]
-- date :date_start
-- date :date_end

WITH first_reply AS (
    SELECT 
        p.topic_id, 
        MIN(post_number) post_number, 
        t.created_at
    FROM posts p
    INNER JOIN topics t ON (p.topic_id = t.id)
    WHERE p.deleted_at IS NULL
        AND p.post_number != 1
        AND p.post_type = 1
        AND p.user_id > 0
        AND t.user_id > 0
        AND t.deleted_at IS NULL
        AND t.archetype = 'regular'
        AND t.created_at::date BETWEEN :date_start AND :date_end
    GROUP BY p.topic_id, t.created_at
    ORDER BY 2 DESC
)

SELECT 
    p.topic_id, 
    fr.created_at::date dt_topic_created,
    (p.created_at - fr.created_at) response_time
FROM posts p
INNER JOIN first_reply fr 
    ON fr.topic_id = p.topic_id 
    AND fr.post_number = p.post_number
    AND p.created_at > fr.created_at
ORDER BY response_time

Os resultados desta consulta são ligeiramente diferentes do relatório “Tempo de resposta para a primeira resposta”:
Em 8 de novembro, por exemplo:
Consulta: 93 Horas
Relatório: 116 Horas
Alguém pode me ajudar?

[JammyDodger]

Acho que alguns deles podem levar algum tempo para pesquisar. Estou investigando por conta própria para ver se consigo entender o que está acontecendo (embora a lacuna entre minhas habilidades em SQL e minhas habilidades em Ruby seja bem grande ).

Mas continue enviando as descobertas, pois seria ótimo consolidar todas essas informações.

[JammyDodger]

@Yotam_Hagay

Olá @SaraDev, executei esta consulta e o resultado não corresponde exatamente ao relatório de Posts na aba geral.
Por exemplo, para 30 de novembro:
Consulta = 112 posts
Relatório = 120 posts
Você pode verificar a diferença?
Obrigado

Para o de Posts, acho que o relatório de estoque também está contando posts de tópicos, bem como os de usuários do sistema, mas também visando apenas aqueles com post_type 1 (ou seja, não sussurros, posts de pequenas ações ou ações de moderador).

Acho que o SQL ficaria mais assim:

--[params]
-- date :start_date
-- date :end_date

SELECT 
    p.created_at::date AS "Dia",
    COUNT(p.id) AS "Contagem"
FROM posts p
INNER JOIN topics t ON t.id = p.topic_id AND t.deleted_at ISNULL
WHERE p.created_at::date BETWEEN :start_date AND :end_date
    AND p.deleted_at ISNULL
    AND t.archetype = 'regular'
    AND p.post_type = 1
GROUP BY p.created_at::date
ORDER BY 1

Você poderia executar isso no seu site e ver se corresponde?

[Yotam_Hagay]

Obrigado Jammy, vou verificar!
Estou trabalhando em uma análise de Tempo de Primeira Resposta, então agradeceria se você pudesse dar uma olhada nesta também.

[JammyDodger]

Ao analisar a versão SQL, acho que está faltando o AND p.user_id <> t.user_id para excluir respostas do OP. Se eu adicionar isso, ele me dá o tempo preciso entre o OP e a primeira resposta de outra pessoa:

--[params]
-- date :date_start
-- date :date_end

WITH first_reply AS (
    SELECT 
        p.topic_id, 
        MIN(post_number) post_number, 
        t.created_at
    FROM posts p
    INNER JOIN topics t ON (p.topic_id = t.id)
    WHERE p.deleted_at IS NULL
        AND p.user_id <> t.user_id
        AND p.post_number != 1
        AND p.post_type = 1
        AND p.user_id > 0
        AND t.user_id > 0
        AND t.deleted_at IS NULL
        AND t.archetype = 'regular'
        AND t.created_at::date BETWEEN :date_start AND :date_end
    GROUP BY p.topic_id, t.created_at
    ORDER BY 2 DESC
)

SELECT 
    p.topic_id, 
    fr.created_at::date dt_topic_created,
    (p.created_at - fr.created_at) response_time
FROM posts p
INNER JOIN first_reply fr 
    ON fr.topic_id = p.topic_id 
    AND fr.post_number = p.post_number
    AND p.created_at > fr.created_at
ORDER BY response_time

Também acho que o relatório de estoque está em decimal em vez de horas e minutos como o SQL. Vou tentar novamente para que corresponda.

---

Apenas uma pequena atualização para incluir o AVG para que seja mais semelhante à saída do relatório de estoque:

--[params]
-- date :date_start
-- date :date_end

WITH first_reply AS (
    SELECT 
        p.topic_id, 
        MIN(post_number) post_number, 
        t.created_at
    FROM posts p
    INNER JOIN topics t ON p.topic_id = t.id
    WHERE p.deleted_at IS NULL
        AND p.user_id <> t.user_id
        AND p.post_type = 1
        AND p.user_id > 0
        AND t.user_id > 0
        AND t.deleted_at IS NULL
        AND t.archetype = 'regular'
        AND t.created_at::date BETWEEN :date_start AND :date_end
    GROUP BY p.topic_id, t.created_at
)

SELECT 
    fr.created_at::date dt_topic_created,
    AVG(p.created_at - fr.created_at) response_time
FROM posts p
INNER JOIN first_reply fr 
    ON fr.topic_id = p.topic_id 
    AND fr.post_number = p.post_number
    AND p.created_at > fr.created_at
GROUP BY fr.created_at::date
ORDER BY response_time

Isso parece corresponder ao relatório de estoque, desde que você leve em consideração que um está em decimal e o outro em HH:MM. Tenho certeza de que há uma maneira de converter o response_time do SQL para decimal, mas o HH:MM parece uma maneira mais intuitiva de fazer isso. (Acho que também há alguns critérios extras que podem não ser necessários, mas também podem ser uma proteção contra circunstâncias incomuns, então, em última análise, deixei essas partes como estão até que eu possa dizer com certeza uma coisa ou outra )

Você poderia executar este e ver como ele se compara?

[Yotam_Hagay]

Sim, agora soma os números mostrados no relatório de estoque, obrigado!
Apenas um comentário -
Descobri que a função AVG abaixo retorna resultados ausentes caso o tempo seja > 24h (uma seção de # de dias está faltando, eu acho).

AVG(p.created_at - fr.created_at)::time response_time

[JammyDodger]

Ah sim, converter para time foi uma má escolha. Se você remover o ::time, ele voltará à versão mais precisa (embora mais difícil de ler).

Também editarei a de cima.