带日期和标签参数的已解决和未解决的主题统计

此数据探索器报告提供了在指定日期范围内,对网站上已解决和未解决主题的全面分析,并可选择按特定标签进行筛选。

:discourse: 此报告需要启用 Discourse Solved 插件。

此报告对于希望了解社区响应能力并识别用户支持和参与度改进领域的管理员和版主特别有用。

带日期和标签参数的已解决和未解决主题统计信息

--[params]
-- date :start_date = 2022-01-01
-- date :end_date = 2024-01-01
-- text :tag_name = all

WITH valid_topics AS (
    SELECT
        t.id,
        t.user_id,
        t.title,
        t.views,
        (SELECT COUNT(*) FROM posts WHERE topic_id = t.id AND deleted_at IS NULL AND post_type = 1) - 1 AS "posts_count",
        t.created_at,
        (CURRENT_DATE::date - t.created_at::date) AS "total_days",
        STRING_AGG(tags.name, ', ') AS tag_names, -- Aggregate tags for each topic
        c.name AS category_name
    FROM topics t
    LEFT JOIN topic_tags tt ON tt.topic_id = t.id
    LEFT JOIN tags ON tags.id = tt.tag_id
    LEFT JOIN categories c ON c.id = t.category_id
    WHERE t.deleted_at IS NULL
        AND t.created_at::date BETWEEN :start_date AND :end_date
        AND t.archetype = 'regular'
    GROUP BY t.id, c.name
),

solved_topics AS (
    SELECT
        vt.id,
        dsst.created_at
    FROM discourse_solved_solved_topics dsst
    INNER JOIN valid_topics vt ON vt.id = dsst.topic_id
),

last_reply AS (
    SELECT p.topic_id, p.user_id FROM posts p
    INNER JOIN (SELECT topic_id, MAX(id) AS post FROM posts p
                WHERE deleted_at IS NULL
                AND post_type = 1
                GROUP BY topic_id) x ON x.post = p.id
),

first_reply AS (
    SELECT p.topic_id, p.user_id, p.created_at FROM posts p
    INNER JOIN (SELECT topic_id, MIN(id) AS post FROM posts p
                WHERE deleted_at IS NULL
                AND post_type = 1
                AND post_number > 1
                GROUP BY topic_id) x ON x.post = p.id
)

SELECT
    CASE
        WHEN st.id IS NOT NULL THEN 'solved'
        ELSE 'unsolved'
    END AS status,
    vt.tag_names,
    vt.category_name,
    vt.id AS topic_id,
    vt.user_id AS topic_user_id,
    ue.email,
    vt.title,
    vt.views,
    lr.user_id AS last_reply_user_id,
    ue2.email AS last_reply_user_email,
    vt.created_at::date AS topic_create,
    COALESCE(TO_CHAR(fr.created_at, 'YYYY-MM-DD'), '') AS first_reply_create,
    COALESCE(TO_CHAR(st.created_at, 'YYYY-MM-DD'), '') AS solution_create,
    COALESCE(fr.created_at::date - vt.created_at::date, 0) AS "time_first_reply(days)",
    COALESCE(CEIL(EXTRACT(EPOCH FROM (fr.created_at - vt.created_at)) / 3600.00), 0) AS "time_first_reply(hours)",
    COALESCE(st.created_at::date - vt.created_at::date, 0) AS "time_solution(days)",
    COALESCE(CEIL(EXTRACT(EPOCH FROM (st.created_at - vt.created_at)) / 3600.00), 0) AS "time_solution(hours)",
    vt.created_at::date,
    vt.posts_count AS number_of_replies,
    vt.total_days AS total_days_without_solution
FROM valid_topics vt
LEFT JOIN last_reply lr ON lr.topic_id = vt.id
LEFT JOIN first_reply fr ON fr.topic_id = vt.id
LEFT JOIN solved_topics st ON st.id = vt.id
INNER JOIN user_emails ue ON vt.user_id = ue.user_id AND ue."primary" = true
LEFT JOIN user_emails ue2 ON lr.user_id = ue2.user_id AND ue2."primary" = true
WHERE (:tag_name = 'all' OR vt.tag_names ILIKE '%' || :tag_name || '%')
GROUP BY st.id, vt.tag_names, vt.category_name, vt.id, vt.user_id, ue.email, vt.title, vt.views, lr.user_id, ue2.email, vt.created_at, fr.created_at, st.created_at, vt.posts_count, vt.total_days
ORDER BY topic_create, vt.total_days DESC

SQL 查询说明

报告是通过一个复杂的 SQL 查询生成的,该查询利用公共表表达式 (CTE) 来有效地组织和处理数据。查询结构如下:

  • valid_topics: 此 CTE 按指定的日期范围和类型(“regular”)筛选主题,排除已删除的主题。它还聚合与每个主题关联的标签,以便稍后按标签名称进行筛选(如果指定)。
  • solved_topics: 标识已标记为已解决的主题。
  • last_reply: 通过查找未删除且类型为 1(表示常规帖子)的最大帖子 ID(表示最新帖子)来确定每个主题上最后回复的用户。
  • first_reply: 与 last_reply 类似,但用于识别原始帖子后第一个回复该主题的用户。

主查询然后合并这些 CTE,以编译每个主题的详细报告,包括它是已解决还是未解决、标签名称、类别名称、主题和用户 ID、电子邮件、浏览量、回复计数以及第一次回复和解决方案的时间。

参数

  • start_date: 生成报告的日期范围的开始日期。
  • end_date: 生成报告的日期范围的结束日期。
  • tag_name: 用于筛选主题的特定标签。使用“all”包含具有任何标签的主题。

结果

报告为每个主题提供以下信息(在指定参数范围内):

  • status: 指示主题是已解决还是仍未解决。
  • tag_names: 显示与主题关联的标签。
  • category_name: 显示与主题关联的类别。
  • topic_id: 主题的唯一标识符。
  • topic_user_id: 创建主题的用户的 ID。
  • user_email: 主题创建者的电子邮件地址。
  • title: 主题的标题。
  • views: 主题收到的浏览量。
  • last_reply_user_id: 在主题上进行最后回复的用户的 ID。
  • last_reply_user_email: 进行最后回复的用户的电子邮件地址。
  • topic_create: 创建主题的日期。
  • first_reply_create: 主题第一次回复的日期。
  • solution_create: 为主题标记解决方案的日期(如果适用)。
  • time_first_reply(days/hours): 收到第一次回复所需的时间,以天和小时为单位。
  • time_solution(days/hours): 解决主题所需的时间,以天和小时为单位。
  • created_at: 主题的创建日期。
  • number_of_replies: 主题的总回复数。
  • total_days_without_solution: 主题在没有解决方案的情况下处于活动状态的总天数。

示例结果

status tag_names category_name topic_id topic_user_id user_email title views last_reply_user_id last_reply_user_email topic_create first_reply_create solution_create time_first_reply(days) time_first_reply(hours) time_solution(days) time_solution(hours) created_at number_of_replies total_days_without_solution
solved support, password category1 101 1 user1@example.com How to reset my password? 150 3 user3@example.com 2022-01-05 2022-01-06 2022-01-07 1 24 2 48 2022-01-05 5 2
unsolved support, account category2 102 2 user2@example.com Issue with account activation 75 4 user4@example.com 2022-02-10 2022-02-12 2 48 0 0 2022-02-10 3 412
solved support category3 103 5 user5@example.com Can’t upload profile picture 200 6 user6@example.com 2022-03-15 2022-03-16 2022-03-18 1 24 3 72 2022-03-15 8 3
unsolved NULL category4 104 7 user7@example.com Error when posting 50 8 user8@example.com 2022-04-20 0 0 0 0 2022-04-20 0 373
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又一个很棒的查询,也是我提出的另一个请求。:slight_smile:

你能创建一个选择字段来缩小类别/子类别的范围吗?
我想在仅针对我的工单类别运行此报告。

另外,我发现了一个奇怪的边缘情况。你可能能够也可能无法解释它,但问一下总没坏处。

我有一个主题,我在发布后的第二天回复了它并将其标记为解决方案。然后另一位技术人员在大约 10 天后给出了不同的答案并将其标记为解决方案。

报告显示解决方案时间为 1 天,但无解决方案的总时间为 10 天。

PNG image

您好 @tknospdr

为了回答您在这里提出的两个问题:

您可以使用以下查询来解决此问题:

--[params]
-- date :start_date = 2022-01-01
-- date :end_date = 2024-01-01
-- text :tag_name = all
-- null category_id :category_id

WITH valid_topics AS (
    SELECT
        t.id,
        t.user_id,
        t.title,
        t.views,
        (SELECT COUNT(*) FROM posts WHERE topic_id = t.id AND deleted_at IS NULL AND post_type = 1) - 1 AS "posts_count",
        t.created_at,
        (CURRENT_DATE::date - t.created_at::date) AS "total_days",
        STRING_AGG(tags.name, ', ') AS tag_names,
        c.name AS category_name,
        t.category_id
    FROM topics t
    LEFT JOIN topic_tags tt ON tt.topic_id = t.id
    LEFT JOIN tags ON tags.id = tt.tag_id
    LEFT JOIN categories c ON c.id = t.category_id
    WHERE t.deleted_at IS NULL
        AND t.created_at::date BETWEEN :start_date AND :end_date
        AND t.archetype = 'regular'
    GROUP BY t.id, c.name, t.category_id
),

solved_topics AS (
    SELECT
        dsst.topic_id,
        MIN(dsst.created_at) AS first_solution_at, -- Get earliest solution
        MAX(dsst.created_at) AS latest_solution_at -- Get latest solution
    FROM discourse_solved_solved_topics dsst
    GROUP BY dsst.topic_id
),

last_reply AS (
    SELECT p.topic_id, p.user_id FROM posts p
    INNER JOIN (SELECT topic_id, MAX(id) AS post FROM posts p
                WHERE deleted_at IS NULL
                AND post_type = 1
                GROUP BY topic_id) x ON x.post = p.id
),

first_reply AS (
    SELECT p.topic_id, p.user_id, p.created_at FROM posts p
    INNER JOIN (SELECT topic_id, MIN(id) AS post FROM posts p
                WHERE deleted_at IS NULL
                AND post_type = 1
                AND post_number > 1
                GROUP BY topic_id) x ON x.post = p.id
)

SELECT
    CASE
        WHEN st.topic_id IS NOT NULL THEN 'solved'
        ELSE 'unsolved'
    END AS status,
    vt.tag_names,
    vt.category_name,
    vt.id AS topic_id,
    vt.user_id AS topic_user_id,
    ue.email,
    vt.title,
    vt.views,
    lr.user_id AS last_reply_user_id,
    ue2.email AS last_reply_user_email,
    vt.created_at::date AS topic_create,
    COALESCE(TO_CHAR(fr.created_at, 'YYYY-MM-DD'), '') AS first_reply_create,
    COALESCE(TO_CHAR(st.first_solution_at, 'YYYY-MM-DD'), '') AS first_solution_create,
    COALESCE(TO_CHAR(st.latest_solution_at, 'YYYY-MM-DD'), '') AS latest_solution_create,
    COALESCE(fr.created_at::date - vt.created_at::date, 0) AS "time_first_reply(days)",
    COALESCE(CEIL(EXTRACT(EPOCH FROM (fr.created_at - vt.created_at)) / 3600.00), 0) AS "time_first_reply(hours)",
    COALESCE(st.first_solution_at::date - vt.created_at::date, 0) AS "time_to_first_solution(days)",
    COALESCE(CEIL(EXTRACT(EPOCH FROM (st.first_solution_at - vt.created_at)) / 3600.00), 0) AS "time_to_first_solution(hours)",
    COALESCE(st.latest_solution_at::date - vt.created_at::date, 0) AS "time_to_latest_solution(days)",
    COALESCE(CEIL(EXTRACT(EPOCH FROM (st.latest_solution_at - vt.created_at)) / 3600.00), 0) AS "time_to_latest_solution(hours)",
    vt.created_at::date,
    vt.posts_count AS number_of_replies,
    CASE
        WHEN st.topic_id IS NULL THEN vt.total_days
        ELSE COALESCE(st.latest_solution_at::date - vt.created_at::date, 0)
    END AS total_days_without_solution
FROM valid_topics vt
LEFT JOIN last_reply lr ON lr.topic_id = vt.id
LEFT JOIN first_reply fr ON fr.topic_id = vt.id
LEFT JOIN solved_topics st ON st.topic_id = vt.id
INNER JOIN user_emails ue ON vt.user_id = ue.user_id AND ue."primary" = true
LEFT JOIN user_emails ue2 ON lr.user_id = ue2.user_id AND ue2."primary" = true
WHERE (:tag_name = 'all' OR vt.tag_names ILIKE '%' || :tag_name || '%')
  AND (:category_id ISNULL OR vt.category_id = :category_id)
GROUP BY st.topic_id, st.first_solution_at, st.latest_solution_at, vt.tag_names, vt.category_name, vt.id, vt.user_id, ue.email, vt.title, vt.views, lr.user_id, ue2.email, vt.created_at, fr.created_at, vt.posts_count, vt.total_days
ORDER BY topic_create, vt.total_days DESC

其中 -- null category_id :category_id 参数可用于(可选地)选择一个类别来运行报告,并且结果将跟踪第一个和最后一个解决方案。

此外,total_days_without_solution 结果现在将使用最后一个解决方案日期而不是第一个解决方案日期。

1 个赞

太棒了,谢谢!看起来很棒。

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