如何计算 bigquery 数组字段中元素的频率

How to count frequency of elements in a bigquery array field

我有一个 table 看起来像这样:

我正在寻找 table,它给出字段 l_0, l_1, l_2, l_3.

中元素的频率计数

例如,输出应如下所示:

| author_id  | year | l_o.name         | l_0.count| l1.name    | l1.count | l2.name             | l2.count| l3.name            | l3.count|
| 2164089123 | 1987 | biology          | 3        | botany     | 3        |                     |         |                    |         |
| 2595831531 | 1987 | computer science | 2        | simulation | 2        | computer simulation | 2       | mathematical model | 2       |

编辑:

在某些情况下,数组字段可能有不止一种类型的元素。例如 l_0 可能是 ['biology', 'biology', 'geometry', 'geometry']。在这种情况下,字段 l_0, l_1, l_2, l_3 的输出将是一个嵌套的重复字段,其中包含 l_0.name 中的所有元素以及 l_0.count.

中的所有相应计数

这应该可以工作,假设您想在每个数组的基础上进行计数:

SELECT
  author_id,
  year,
  (SELECT AS STRUCT ANY_VALUE(l_0) AS name, COUNT(*) AS count
   FROM UNNEST(l_0) AS l_0) AS l_0,
  (SELECT AS STRUCT ANY_VALUE(l_1) AS name, COUNT(*) AS count
   FROM UNNEST(l_1) AS l_1) AS l_1,
  (SELECT AS STRUCT ANY_VALUE(l_2) AS name, COUNT(*) AS count
   FROM UNNEST(l_2) AS l_2) AS l_2,
  (SELECT AS STRUCT ANY_VALUE(l_3) AS name, COUNT(*) AS count
   FROM UNNEST(l_3) AS l_3) AS l_3
FROM YourTable;

为了避免太多重复,您可以使用 SQL UDF:

CREATE TEMP FUNCTION GetNameAndCount(elements ARRAY<STRING>) AS (
  (SELECT AS STRUCT ANY_VALUE(elem) AS name, COUNT(*) AS count
   FROM UNNEST(elements) AS elem)
);

SELECT
  author_id,
  year,
  GetNameAndCount(l_0) AS l_0,
  GetNameAndCount(l_1) AS l_1,
  GetNameAndCount(l_2) AS l_2,
  GetNameAndCount(l_3) AS l_3
FROM YourTable;

如果您可能需要考虑一个数组中的多个不同名称,您可以使用 UDF return 一个包含相关计数的名称数组:

CREATE TEMP FUNCTION GetNamesAndCounts(elements ARRAY<STRING>) AS (
  ARRAY(
    SELECT AS STRUCT elem AS name, COUNT(*) AS count
    FROM UNNEST(elements) AS elem
    GROUP BY elem
    ORDER BY count
  )
);

SELECT
  author_id,
  year,
  GetNamesAndCounts(l_0) AS l_0,
  GetNamesAndCounts(l_1) AS l_1,
  GetNamesAndCounts(l_2) AS l_2,
  GetNamesAndCounts(l_3) AS l_3
FROM YourTable;

请注意,如果要跨行计数,则需要取消嵌套数组并在外层执行 GROUP BY,但看起来这不是您的意图基于问题。