我正在对Google BigQuery中的publicdata:samples.github_timeline数据集进行漏斗分析。我想按时间顺序提取所有做过一系列三个事件的独特用户。
事件及其顺序:
这是查询:
select user from (
SELECT user1 as user,
ts1 as eventDate1,
ts2 as eventDate2,
IF(ts2 < ts3, ts3, NULL) as eventDate3
FROM
(SELECT user1,
ts1,
ts2,
ts3
FROM (SELECT user1,
ts1,
IF(ts1 < ts2, ts2, NULL) as ts2
FROM
(SELECT user1,
ts1,
ts2
FROM (SELECT repository_owner as user1,
created_at as ts1
FROM [publicdata:samples.github_timeline]
WHERE type = "WatchEvent") as step1
LEFT JOIN EACH (SELECT repository_owner as user2,
created_at as ts2
FROM [publicdata:samples.github_timeline]
WHERE type = "PushEvent") as step2
ON user1 = user2 where ts1 is not NULL)
) as steps1_2
LEFT JOIN (SELECT repository_owner as user3,
created_at as ts3
FROM [publicdata:samples.github_timeline]
WHERE type = "CreateEvent") as step3
ON user1 = user3
where ts2 is not NULL
)
)
where eventDate3 is not null
group by user
limit 100
最后没有GROUP BY用户,它很快(10秒)。但是当我添加它时,需要花费很多时间(超过20分钟)。
查询有什么问题? 您可以在此处测试查询:https://bigquery.cloud.google.com/
答案 0 :(得分:3)
你有一个加入爆炸;也就是说,如果用户A有20个WatchEvents,20个PushEvents和20个CreateEvents,那么您的查询可以从这60个中生成8000行。这是因为当JOIN两侧有多个匹配键时,它会生成笛卡儿积分双方。您可以通过仅采用最小匹配时间来解决此问题,因此您只需查看最短的WatchEvent时间,以便用户查找后续的PushEvent时间,然后查看比WatchEvent时间晚的最小pushEvent时间来查找匹配CreateEvent时间。
这是一个大约20秒内运行的查询:
SELECT user
FROM (
SELECT step2_2.user1 as user,
MIN(step2_2.ts1) as eventDate1,
MIN(step2_2.ts2) as eventDate2,
MIN(step3.ts3) as eventDate3
FROM (
SELECT user1, MIN(ts1) as ts1, MIN(ts2) as ts2
FROM (
SELECT repository_owner as user1,
MIN(created_at) as ts1
FROM [publicdata:samples.github_timeline]
WHERE type = "WatchEvent"
GROUP EACH BY user1) as step1
JOIN EACH (
SELECT repository_owner as user2,
created_at as ts2
FROM [publicdata:samples.github_timeline]
WHERE type = "PushEvent") as step2
ON user1 = user2
WHERE ts1 < ts2
GROUP EACH BY user1
) as step2_2
JOIN EACH (
SELECT repository_owner as user3,
created_at as ts3
FROM [publicdata:samples.github_timeline]
WHERE type = "CreateEvent") as step3
ON user1 = user3
WHERE step2_2.ts2 < step3.ts3
GROUP EACH BY user
)
GROUP BY user
LIMIT 100
答案 1 :(得分:2)
如果您的数据集不是太大,您可以使用lead()窗口函数来查找序列并完全避免连接。
Select repository_owner
FROM
(
Select repository_owner,type as Event0,
LEAD(x,1) OVER(Partition by repository_owner order by ts) as Event1,
LEAD(x,2) OVER(Partition by repository_owner order by ts) as Event2,
FROM
(
SELECT repository_owner as user,created_at as ts,type as x
from [publicdata:samples.github_timeline]
where type in ("WatchEvent","PushEvent","CreateEvent")
))
where Event0="WatchEvent"
and Event1="PushEvent"
and Event2="CreateEvent"
Group by repository_owner
7秒......
如果事件不在&#34;背靠背和#34; (参考约旦的评论),需要让它更复杂一些:
Select repository_owner from
(
Select repository_owner,Event0,Event1,
Lead(Event0,1) OVER (Partition by repository_owner order by ts) as Event2,
Lead(Event1,1) OVER (Partition by repository_owner order by ts) as Event3,
FROM
(Select * from
(Select repository_owner,type as Event0,ts,
LEAD(x,1) OVER(Partition by repository_owner order by ts) as Event1,
FROM
(
SELECT repository_owner as user,created_at as ts,type as x
from [publicdata:samples.github_timeline]
where type in ("WatchEvent","PushEvent","CreateEvent")
))
where (Event0="WatchEvent" and
Event1 in("PushEvent" ,"CreateEvent"))
OR ( Event1="CreateEvent" and
Event0 in("PushEvent" ,"WatchEvent")))
)
Where Event0="WatchEvent" and
(Event1="PushEvent" Or Event2="PushEvent") and
Event3="CreateEvent"
Group by repository_owner
如果您的数据集太大,则会遇到此问题:Parallelizable OVER EACH BY
希望有所帮助
答案 2 :(得分:1)
如果在非分组查询中使用“limit 100”,orchestrator将在获取前100个数据行后中断执行。
“按用户限制分组100”要求在分组之前必须计算所有数据行。然后执行分组。最后,“限制100”终于生效了。