Question

在Clickhouse中，我有一个表，列出了具有用户ID和标记的事件。我的目的是从这些数据中提取会话。

会话是一组时间彼此接近的事件。举个例子，如果一个事件比前一个事件晚了半小时以上，那么它在另一个会话中。但是，如果每1500万发生一次事件，则会话可能长达12个小时。

我查看了时间段函数的文档，该文档描述了与我的相似的用例，但我不知道如何编写查询。（https://clickhouse.yandex/docs/en/query_language/functions/date_time_functions/#timeslot）

例如：

事件：

date                | user  | tag
2018-12-21 00:00:00 │ user1 │ tag1
2018-12-21 00:00:00 │ user2 │ tag1
2018-12-21 00:15:00 │ user1 │ tag1
2018-12-21 00:15:00 │ user2 │ tag2
2018-12-21 00:30:00 │ user1 │ tag1
2018-12-21 00:45:00 │ user1 │ tag1
2018-12-21 01:45:00 │ user1 │ tag1

结果会话：

date                | date_end            | user  | tag  | count
2018-12-21 00:00:00 | 2018-12-21 00:45:00 | user1 | tag1 | 4
2018-12-21 00:00:00 | 2018-12-21 00:00:00 | user2 | tag1 | 1
2018-12-21 00:15:00 | 2018-12-21 00:15:00 | user2 | tag2 | 1
2018-12-21 01:45:00 | 2018-12-21 01:45:00 | user1 | tag1 | 1

Answer 1

此查询依赖于默认的 timeSlot 功能，该功能将日期舍入为半小时：

SELECT user, tag, eventCount, length(sessionStartDateArray) sessionCount, sessionStartDateArray
FROM
(
    SELECT
        user,
        tag,
        -- a count of events with rounded date (remove DISTINCT-clause from nested query to get a real count of events).
        count() as eventCount,
        -- an array of rounded dates
        groupArray(roundedDate) AS roundedDateArray,
        -- an array of rounded dates shifted to 30 minutes (where 30 min taken from timeSlot-function)
        arrayMap(i -> (i + 1800), roundedDateArray) AS shiftedRoundedDateArray,
        -- to intersect two arrays to find the dates when sessions start
        arrayFilter(x -> (has(shiftedRoundedDateArray, x) = 0), roundedDateArray) AS sessionStartDateArray
    FROM
    (
        SELECT DISTINCT
            user,
            tag,
            -- rounds down the time to the half hour.
            timeSlot(date) AS roundedDate
        FROM test01
    )
    GROUP BY user, tag
)
ORDER BY user, tag;

Answer 2

create table C (D DateTime',' user String',' tag String) Engine = Memory;

insert into C values
('2018-12-21 00:00:00','user1','tag1'),
('2018-12-21 00:00:00','user2','tag1'),
('2018-12-21 00:15:00','user1','tag1'),
('2018-12-21 00:15:00','user2','tag2'),
('2018-12-21 00:30:00','user1','tag1'),
('2018-12-21 00:45:00','user1','tag1'),
('2018-12-21 01:45:00','user1','tag1'),



SELECT user, tag,
       toDateTime(((arrayJoin(arraySplit((k, j) -> j, Arr, 
              arrayMap(i -> i > 1800, 
              arrayDifference(arraySort(groupArray(toUnixTimestamp(D))) as Arr))))) 
              as R)[1]) b, 
       toDateTime(R[-1]) e,
       length(R) c
from C    
group by user, tag

┌─user──┬─tag──┬───────────────────b─┬───────────────────e─┬─c─┐
│ user2 │ tag2 │ 2018-12-21 00:15:00 │ 2018-12-21 00:15:00 │ 1 │
│ user1 │ tag1 │ 2018-12-21 00:00:00 │ 2018-12-21 00:45:00 │ 4 │
│ user1 │ tag1 │ 2018-12-21 01:45:00 │ 2018-12-21 01:45:00 │ 1 │
│ user2 │ tag1 │ 2018-12-21 00:00:00 │ 2018-12-21 00:00:00 │ 1 │
└───────┴──────┴─────────────────────┴─────────────────────┴───┘

从事件中提取会话

2 个答案: