Postgres：用左连接计算行数

Question

我正在尝试使用 Postgres 进行一些分析，我确实有 2 个表，分别称为：predictionstate 和 pageviews。

predictionstate 表：

此表包含具有我们算法结果的列，使用以下结构：

• id ({company_identifier}:{user_identifier})
• 型号（参考字符串值）
• 预测（0.0 到 1.0 之间的浮点数）

pageviews 表：

此表包含用户信息，使用以下结构：

• company_identifier
• user_identifier
• pageview_current_url_type

问题

我正在尝试根据我们的最佳模型获取数据，以分析它的准确性，基本上我需要知道在哪里创建细分并计算我有多少成员。下面的代码就是这样做的：

WITH ranges AS (
  SELECT
    myrange::text || '-' || (myrange + 0.1)::text AS segment,
    myrange as r_min, myrange + 0.1 as r_max
  FROM generate_series(0.0, 0.9, 0.1) AS myrange
)
SELECT
  SPLIT_PART(p.id, ':', 1) as company_identifier,
  p.model,
  r.segment,
  COUNT(DISTINCT(SPLIT_PART(p.id, ':', 2))) as "segment_users"
FROM
  ranges r
INNER JOIN predictionstate p ON p.prediction BETWEEN r.r_min AND r.r_max
GROUP BY company_identifier, p.model, r.segment
ORDER BY company_identifier, p.model, r.segment;

但是我遇到的问题，因为我不知道具体怎么做，所以对于每个（公司、型号、细分市场），需要获取准确度的数据，查询@987654330 @表并识别pageview_current_url_type == 'BUYSUCCESS'。

我试过了，但没用：

WITH ranges AS (
  SELECT
    myrange::text || '-' || (myrange + 0.1)::text AS segment,
    myrange as r_min, myrange + 0.1 as r_max
  FROM generate_series(0.0, 0.9, 0.1) AS myrange
)
SELECT
  SPLIT_PART(p.id, ':', 1) as company_identifier,
  p.model,
  r.segment,
  COUNT(DISTINCT(SPLIT_PART(p.id, ':', 2))) as "segment_users",
  b.n as "converted_users"
FROM
  ranges r,
  (
    SELECT COUNT(DISTINCT(pvs.user_identifier)) as n
    FROM pageviews pvs
    INNER JOIN (
        SELECT
            SPLIT_PART(id, ':', 1) as company_identifier,
            SPLIT_PART(id, ':', 2) as user_identifier
        FROM predictionstate ps
        WHERE prediction BETWEEN r.r_min AND r.r_max ) users
        ON (
            pvs.user_identifier = users.user_identifier AND
            pvs.company_identifier= users.company_identifier) 
        WHERE pageview_current_url_type = 'BUYSUCCESS'

  ) b
INNER JOIN predictionstate p ON p.prediction BETWEEN r.r_min AND r.r_max
GROUP BY company_identifier, p.model, r.segment
ORDER BY company_identifier, p.model, r.segment;

TL;DR：我需要根据主要查询用户来计算 JOIN。

编辑：

我添加了一个 SQL Fiddle https://www.db-fiddle.com/f/5sQiZD6mHwdnwvVfvL9MAh/0 。

我想知道，对于那些segment_users，有多少人有pageview_current_url_type = 'BUYSUCCESS'，在结果中再添加一列：segmented_really_bought。

编辑 2：再一次尝试不起作用（错误：列“p.id”必须出现在 GROUP BY 子句中或用于聚合函数中）

WITH ranges AS (
  SELECT
    myrange::text || '-' || (myrange + 0.1)::text AS segment,
    myrange as r_min, myrange + 0.1 as r_max
  FROM generate_series(0.0, 0.9, 0.1) AS myrange
)
SELECT
  SPLIT_PART(p.id, ':', 1) as company_identifier,
  p.model,
  r.segment,
  COUNT(DISTINCT(SPLIT_PART(p.id, ':', 2))) as "segment_users",
  COUNT(b.*) as "converted_users"
FROM
  ranges r
INNER JOIN predictionstate p ON p.prediction BETWEEN r.r_min AND r.r_max
INNER JOIN (
  SELECT users.company_identifier, COUNT(users.user_identifier) AS n
  FROM pageviews
  INNER JOIN (
    SELECT SPLIT_PART(ps.id, ':', 2) AS user_identifier,
           SPLIT_PART(ps.id, ':', 1) AS company_identifier
    FROM predictionstate ps
    WHERE provider_id=47 AND
          prediction > 0.7
   ) users ON (
      pageviews.user_identifier=users.user_identifier AND
      pageviews.company_identifier=users.company_identifier
    )
  WHERE pageview_current_url_type='BUYSUCCESS'
  GROUP BY users.company_identifier
) AS b
ON (
  b.company_identifier = company_identifier
)
GROUP BY company_identifier, p.model, r.segment
ORDER BY company_identifier, p.model, r.segment;

编辑 3：添加了所需的输出

使用此代码生成：https://gist.github.com/brunoalano/479265b934a67dc02092fb54a846fe1e

company, model, segment, segment_users, really_bought
company_a, model_a, 0.3-0.4, 1, 3
company_a, model_a, 0.5-0.6, 1, 1
company_a, model_b, 0.2-0.3, 1, 3
company_a, model_c, 0.2-0.3, 1, 1
company_a, model_c, 0.7-0.8, 1, 3
company_b, model_a, 0.3-0.4, 3, 2
company_b, model_b, 0.5-0.6, 2, 1
company_b, model_b, 0.6-0.7, 1, 1
company_b, model_c, 0.5-0.6, 1, 0
company_b, model_c, 0.8-0.9, 1, 1

Answer 1

如果没有示例输出，很难判断您需要什么，但我认为您正在寻找的是：

WITH ranges AS (
  SELECT
    myrange::text || '-' || (myrange + 0.1)::text AS segment,
    myrange as r_min, myrange + 0.1 as r_max
  FROM generate_series(0.0, 0.9, 0.1) AS myrange
)
SELECT
  p.company_identifier,
  p.model,
  r.segment,
  COUNT(DISTINCT(p.user_identifier)) as "segment_users",
  COUNT(CASE WHEN pv.pageview_current_url_type = 'BUYSUCCESS' THEN 1 END) AS segmented_really_bought
FROM
  ranges r
INNER JOIN (
  SELECT
    SPLIT_PART(id, ':', 1) as company_identifier,
    SPLIT_PART(id, ':', 2) as user_identifier,
    model,
    prediction
  FROM
    predictionstate
  ) p ON p.prediction BETWEEN r.r_min AND r.r_max
LEFT JOIN pageviews pv ON 
  p.company_identifier = pv.company_identifier
  AND p.user_identifier = pv.user_identifier
GROUP BY p.company_identifier, p.model, r.segment
ORDER BY p.company_identifier, p.model, r.segment;

对小提琴查询的更改：

• 将 predictionstate 替换为我们加入的子查询，我们在其中执行 split_part 逻辑以将公司和用户标识符作为单独的列获取
• 将这些标识符用于LEFT JOIN 到pageviews
• 添加了 segmented_really_bought 列，并带有一个 CASEd COUNT

Answer 2

demo: db<>fiddle

WITH ranges AS (
  SELECT
    myrange::text || '-' || (myrange + 0.1)::text AS segment,
    myrange as r_min, myrange + 0.1 as r_max
  FROM generate_series(0.0, 0.9, 0.1) AS myrange
), pstate AS (                                         -- A
  SELECT 
    SPLIT_PART(ps.id, ':', 1) AS company_identifier,
    SPLIT_PART(ps.id, ':', 2) AS user_identifier,
    model,
    prediction
  FROM predictionstate ps
)
SELECT 
  company_identifier, model, segment,
  COUNT(DISTINCT user_identifier) as segment_users,    -- B
  -- C: 
  COUNT(user_identifier) FILTER (WHERE pageview_current_url_type = 'BUYSUCCESS') as really_bought
FROM pstate ps
LEFT JOIN ranges r 
ON prediction BETWEEN r_min AND r_max
LEFT JOIN pageviews pv 
USING (company_identifier, user_identifier)
GROUP BY company_identifier, model, segment
ORDER BY company_identifier, model, segment

答：我真的建议您将 id 列分成两列以便更好地处理。这将为您节省大量拆分字符串的时间（编写查询并执行它们）并且更具可读性。这就是我添加第二个 CTE 的原因。

B：COUNT(DISTINCT) 统计组中不同的用户

C：统计所有用户（不区分），但在统计前过滤掉预期的状态。

---

我想知道：如果预测恰好在阈值上怎么办，例如0.3。使用BETWEEN 子句，此范围将在0.2-0.3 和0.3-0.4 范围内连接（因为BETWEEN 等于r_min >= x >= r_max）。最好将范围定义为r_min >= x > r_max 或r_min > x >= r_max。我按照您在示例中提到的方式进行了连接，但我更愿意更改它。还是不知道是哪个方向