I'm trying to combine a few tables into a row.
Team Table:
+----+-------+
| id | team |
+----+-------+
| 10 | Team1 |
| 11 | Team2 |
| 12 | Team3 |
+----+-------+
Location Table:
+----+-----------+
| id | location |
+----+-----------+
| 1 | location1 |
| 2 | location2 |
| 3 | location3 |
+----+-----------+
Stops Table:
+----+---------+-------------+---------------------+
| id | team_id | location_id | timestamp |
+----+---------+-------------+---------------------+
| 1 | 10 | 2 | 2019-11-07 15:27:42 |
| 2 | 10 | 3 | 2019-11-07 16:37:52 |
| 3 | 10 | 4 | 2019-11-07 17:47:62 |
+----+---------+-------------+---------------------+
Looking to create the desired table:
+----+---------+---------------------+---------------------+---------------------+
| id | team_id | (loc id=2) | (loc id=3) | (loc id=4) |
+----+---------+---------------------+---------------------+---------------------+
| 1 | 10 | 2019-11-07 15:27:42 | 2019-11-07 16:37:52 | 2019-11-07 17:47:62 |
| 2 | 11 | | | |
| 3 | 12 | | | |
+----+---------+---------------------+---------------------+---------------------+
There will always be a finite number of locations.
Any guidance would be greatly appreciated! I've tried a handful of LEFT JOINS, but am not getting far.
You can do conditional aggregation:
select
t.id team_id
max(case when s.location_id = 2 then timestamp end) loc_id_2,
max(case when s.location_id = 3 then timestamp end) loc_id_3,
max(case when s.location_id = 4 then timestamp end) loc_id_4
from
team t
left join stops s on s.team_id = t.id
group by t.id
If you want to generate an id column on the fly for the generated results (which makes little sense since you get one record per team_id already), then you can use row_number() (availble in MySQL 8.0 onwards):
select
row_number() over(order by t.id) id,
t.*
from (
select
t.id team_id,
max(case when s.location_id = 2 then timestamp end) loc_id_2,
max(case when s.location_id = 3 then timestamp end) loc_id_3,
max(case when s.location_id = 4 then timestamp end) loc_id_4
from
team t
left join stops s on s.team_id = t.id
group by t.id
) t
Related
I am trying to join two tables with respect to the max values for the values column. I would like to produce the expected results as shown below based on the max value while joining
select * from order
-------------------------
| ID | value | Name |
-------------------------
| 1 | 23 | REM |
| 2 | 0 | SER |
| 3 | 13 | MH |
| 4 | 3 | MH |
| 5 | 1 | MP |
-------------------------
select * from product
-------------------------
| ID | value | Name |
-------------------------
| 1 | 2 | ABC |
| 2 | 2 | DEG |
| 3 | 17 | XYZ |
-------------------------
Desired result:
-------------------------
| ID | Value | Name |
-------------------------
| 1 | 23 | REM |
| 2 | 2 | DEG |
| 3 | 17 | XYZ |
| 4 | 3 | MH |
| 5 | 1 | MP |
-------------------------
I have tried something like below but it's not fetching the value (NAME) from other table
SELECT
MAX(IF(a.value >b.value , a.value ,b.value )) AS Value
from order a left join product b on a.ID= b.ID
Please suggest how to get the expected result from these two tables.
Below is for BigQuery Standard SQL
#standardsql
select as value array_agg(struct(id, value, name) order by value desc limit 1)[offset(0)]
from
(
select * from `project.dataset.order`
union all
select * from `project.dataset.product`
)
group by id
with output
You can do this using a full join:
select id,
(case when p.val is null or p.val < o.val then o.val else p.val end),
(case when p.val is null or p.val < o.val then o.name else p.name end)
from product p full join
order o
using (id);
I just find this the simplest way to think about the problem.
I have table it store hierarchy data in MySQL this table store stable relation but if each user less than 1000 buy removed and user User a lower level replace this is my code and work fine, after GROUP BY it contain all ancestor of descendant with compare then COUNT(*) AS level count level each user. This I have SQL code to compress data According to minimum buy for each user
+-------------+---------------+-------------+
| ancestor_id | descendant_id | path_length |
+-------------+---------------+-------------+
| 1 | 1 | 0 |
| 1 | 2 | 1 |
| 1 | 3 | 1 |
| 1 | 4 | 2 |
| 1 | 5 | 3 |
| 1 | 6 | 4 |
| 2 | 2 | 0 |
| 2 | 4 | 1 |
| 2 | 5 | 2 |
| 2 | 6 | 3 |
| 3 | 3 | 0 |
| 4 | 4 | 0 |
| 4 | 5 | 1 |
| 4 | 6 | 2 |
| 5 | 5 | 0 |
| 5 | 6 | 1 |
| 6 | 6 | 0 |
+-------------+---------------+-------------+
This is table buy
+--------+--------+
| userid | amount |
+--------+--------+
| 2 | 2000 |
| 4 | 6000 |
| 6 | 7000 |
| 1 | 7000 |
SQL code
SELECT a.*
FROM
( SELECT userid
FROM webineh_user_buys
GROUP BY userid
HAVING SUM(amount) >= 1000
) AS buys_d
JOIN
webineh_prefix_nodes_paths AS a
ON a.descendant_id = buys_d.userid
JOIN
(
SELECT userid
FROM webineh_user_buys
GROUP BY userid
HAVING SUM(amount) >= 1000
) AS buys_a on (a.ancestor_id = buys_a.userid )
JOIN
( SELECT descendant_id
, MAX(path_length) path_length
FROM webineh_prefix_nodes_paths
where a.ancestor_id = ancestor_id
GROUP
BY descendant_id
) b
ON b.descendant_id = a.descendant_id
AND b.path_length = a.path_length
GROUP BY a.descendant_id, a.ancestor_id
I need get max path_length where ancestor_id have At least 1000 amount buy but have error in where in subquery where a.ancestor_id = ancestor_id error code
1054 - Unknown column 'a.ancestor_id' in 'where clause'
I add SQLFidle demo.
You could use this query:
select m.userid as descendant,
p.ancestor_id,
p.path_length
from (
select b1.userid,
min(case when b2.amount >= 1000
then p.path_length
end) as path_length
from (select userid, sum(amount) amount
from webineh_user_buys
group by userid
having sum(amount) >= 1000
) as b1
left join webineh_prefix_nodes_paths p
on p.descendant_id = b1.userid
and p.path_length > 0
left join (select userid, sum(amount) amount
from webineh_user_buys
group by userid) as b2
on p.ancestor_id = b2.userid
group by b1.userid
) as m
left join webineh_prefix_nodes_paths p
on p.descendant_id = m.userid
and p.path_length = m.path_length
order by m.userid
Output for sample data in the question:
| userid | ancestor_id | path_length |
|--------|-------------|-------------|
| 1 | (null) | (null) |
| 2 | 1 | 1 |
| 4 | 2 | 1 |
| 6 | 4 | 2 |
SQL fiddle
I have a number of tables in my database.
Table: ObjectToPerson
For example if I had a number of entries below in the database:
+----+------------+------------+----------+----------+--------------+
| Id | WeekNumber | Date | PersonId | ObjectId | ObjectTypeId |
+----+------------+------------+----------+----------+--------------+
| 1 | 1 | 2015-11-04 | 1 | 1 | 1 |
| 2 | 1 | 2015-11-04 | 1 | 3 | 2 |
| 3 | 1 | 2015-11-04 | 2 | 2 | 1 |
| 4 | 1 | 2015-11-04 | 2 | 4 | 2 |
+----+------------+------------+----------+----------+--------------+
I am wanting to return the results back as two lines as follows:
+------+------------+----------+----------------------------+----------------------------+
| Week | Date | PersonId | ObjectId(ObjectTypeId = 1) | ObjectId(ObjectTypeId = 2) |
+------+------------+----------+----------------------------+----------------------------+
| 1 | 2015-11-04 | 1 | 1 | 3 |
| 1 | 2015-11-04 | 2 | 2 | 4 |
+------+------------+----------+----------------------------+----------------------------+
I am thinking of some sort of Group By query but I just can't seem to get it right.
Select * From ObjectToPerson
Left Join Objects O On O.Id = ObjectToPerson.ObjectId And ObjectToPerson.ObjectTypeId = 1
Left Join Objects O On O.Id = ObjectToPerson.ObjectId And ObjectToPerson.ObjectTypeId = 2
Can someone explain how I would get to this please?
You could use CASE to only select the ObjectId if the type is correct for the column, then use MAX/GROUP BY to group the result into a single row per person/week/date.
SELECT WeekNumber week, date, personid,
MAX(CASE WHEN ObjectTypeId=1 THEN ObjectId END) Type1,
MAX(CASE WHEN ObjectTypeId=2 THEN ObjectId END) Type2
FROM ObjectToPerson
GROUP BY week, date, personid
An SQLfiddle to test with.
You don't want two joins, you want a WHERE clause;
SELECT * FROM ObjectToPerson
LEFT JOIN Objects O ON O.Id = ObjectToPerson.ObjectId
WHERE ObjectToPerson.ObjectTypeId IN(1,2)
I have two tables, one for sales and another for stock.
I want to select location id, item id, size id and sales qty from sales table, while I want just to select stock qty from stock table for the same location id and size id from sales table, like this:
Sales table:
------------------------------------
| loc_id | item_id | size_id | qty |
------------------------------------
| 5 | 11321 | 1 | 5 |
| 5 | 11321 | 2 | 8 |
| 5 | 11321 | 3 | 4 |
| 5 | 11321 | 2 | 1 |
Stock table:
------------------------------------
| loc_id | item_id | size_id | qty |
------------------------------------
| 5 | 11321 | 1 | 3 |
| 5 | 11321 | 2 | 7 |
| 5 | 11321 | 3 | 9 |
So the result after select should be like this:
------------------------------------------------------
| loc_id | item_id | size_id | sales_qty | stock_qty |
------------------------------------------------------
| 5 | 11321 | 1 | 5 | 3 |
| 5 | 11321 | 2 | 9 | 7 |
| 5 | 11321 | 3 | 4 | 9 |
Here's what I tried to do:
SELECT SUM(T1.qty) AS `salesQty`, SUM(T2.qty) AS `stockQty`, T1.size_id,
T1.loc_id
FROM sales T1
INNER JOIN stock T2 ON T2.item_id = T1.item_id AND T2.size_id = T1.size_id
WHERE T1.item_id = '11321'
AND T1.size_id IN (1,2,3)
AND T1.loc_id IN (5)
GROUP BY T1.size_id, T1.loc_id
But stock qty always wrong!
select
q1.loc_id
,q1.item_id
,q1.size_id
,sum(case when q1.Type='Sales' then q1.Qty else 0 end) as sales_qty
,sum(case when q1.Type='Stock' then q1.Qty else 0 end) as stock_qty
from (
select
T1.loc_id
,T1.item_id
,T1.size_id
,'Sales' as Type
,SUM(T1.qty) AS Qty
from sales T1
group by
T1.loc_id
,T1.item_id
,T1.size_id
union all
select
T2.loc_id
,T2.item_id
,T2.size_id
,'Stock' as Type
,SUM(T2.qty) AS Qty
from stock T2
group by
T2.loc_id
,T2.item_id
,T2.size_id) q1
group by
q1.loc_id
,q1.item_id
,q1.size_id
I've got four MySQL tables:
users (id, name)
polls (id, text)
options (id, poll_id, text)
responses (id, poll_id, option_id, user_id)
Given a particular poll and a particular option, I'd like to generate a table that shows which options from other polls are most strongly correlated.
Suppose this is our data set:
TABLE users:
+------+-------+
| id | name |
+------+-------+
| 1 | Abe |
| 2 | Bob |
| 3 | Che |
| 4 | Den |
+------+-------+
TABLE polls:
+------+-----------------------+
| id | text |
+------+-----------------------+
| 1 | Do you like apples? |
| 2 | What is your gender? |
| 3 | What is your height? |
| 4 | Do you like polls? |
+------+-----------------------+
TABLE options:
+------+----------+---------+
| id | poll_id | text |
+------+----------+---------+
| 1 | 1 | Yes |
| 2 | 1 | No |
| 3 | 2 | Male |
| 4 | 2 | Female |
| 5 | 3 | Short |
| 6 | 3 | Tall |
| 7 | 4 | Yes |
| 8 | 4 | No |
+------+----------+---------+
TABLE responses:
+------+----------+------------+----------+
| id | poll_id | option_id | user_id |
+------+----------+------------+----------+
| 1 | 1 | 1 | 1 |
| 2 | 1 | 2 | 2 |
| 3 | 1 | 2 | 3 |
| 4 | 1 | 2 | 4 |
| 5 | 2 | 3 | 1 |
| 6 | 2 | 3 | 2 |
| 7 | 2 | 3 | 3 |
| 8 | 2 | 4 | 4 |
| 9 | 3 | 5 | 1 |
| 10 | 3 | 6 | 2 |
| 10 | 3 | 5 | 3 |
| 10 | 3 | 6 | 4 |
| 10 | 4 | 7 | 1 |
| 10 | 4 | 7 | 2 |
| 10 | 4 | 7 | 3 |
| 10 | 4 | 7 | 4 |
+------+----------+------------+----------+
Given the poll ID 1 and the option ID 2, the generated table should be something like this:
+----------+------------+-----------------------+
| poll_id | option_id | percent_correlated |
+----------+------------+-----------------------+
| 4 | 7 | 100 |
| 2 | 3 | 66.66 |
| 3 | 6 | 66.66 |
| 2 | 4 | 33.33 |
| 3 | 5 | 33.33 |
| 4 | 8 | 0 |
+----------+------------+-----------------------+
So basically, we're identifying all of the users who responded to poll ID 1 and selected option ID 2, and we're looking through all the other polls to see what percentage of them also selected each other option.
Don't have an instance handy to test, can you see if this gets proper results:
select
poll_id,
option_id,
((psum - (sum1 * sum2 / n)) / sqrt((sum1sq - pow(sum1, 2.0) / n) * (sum2sq - pow(sum2, 2.0) / n))) AS r,
n
from
(
select
poll_id,
option_id,
SUM(score) AS sum1,
SUM(score_rev) AS sum2,
SUM(score * score) AS sum1sq,
SUM(score_rev * score_rev) AS sum2sq,
SUM(score * score_rev) AS psum,
COUNT(*) AS n
from
(
select
responses.poll_id,
responses.option_id,
CASE
WHEN user_resp.user_id IS NULL THEN SELECT 0
ELSE SELECT 1
END CASE as score,
CASE
WHEN user_resp.user_id IS NULL THEN SELECT 1
ELSE SELECT 0
END CASE as score_rev,
from responses left outer join
(
select
user_id
from
responses
where
poll_id = 1 and
option_id = 2
)user_resp
ON (user_resp.user_id = responses.user_id)
) temp1
group by
poll_id,
option_id
)components
After a few hours of trial and error, I managed to put together a query that works correctly:
SELECT poll_id AS p_id,
option_id AS o_id,
COUNT(*) AS optCount,
(SELECT COUNT(*) FROM response WHERE option_id = o_id AND user_id IN
(SELECT user_id FROM response WHERE poll_id = '1' AND option_id = '2')) /
(SELECT COUNT(*) FROM response WHERE poll_id = p_id AND user_id IN
(SELECT user_id FROM response WHERE poll_id = '1' AND option_id = '2'))
AS percentage
FROM response
INNER JOIN
(SELECT user_id FROM response WHERE poll_id = '1' AND option_id = '2') AS user_ids
ON response.user_id = user_ids.user_id
WHERE poll_id != '1'
GROUP BY option_id DESC
ORDER BY percentage DESC, optCount DESC
Based on a tests with a small data set, this query looks to be reasonably fast, but I'd like to modify it so the "IN" subquery is not repeated three times. Any suggestions?
This seems to give the right results for me:
select poll_stats.poll_id,
option_stats.option_id,
(100 * option_responses / poll_responses) as percent_correlated
from (select response.poll_id,
count(*) as poll_responses
from response selecting_response
join response on response.user_id = selecting_response.user_id
where selecting_response.poll_id = 1 and selecting_response.option_id = 2
group by response.poll_id) poll_stats
join (select options.poll_id,
options.id as option_id,
count(response.id) as option_responses
from options
left join response on response.poll_id = options.poll_id
and response.option_id = options.id
and exists (
select 1 from response selecting_response
where selecting_response.user_id = response.user_id
and selecting_response.poll_id = 1
and selecting_response.option_id = 2)
group by options.poll_id, options.id
) as option_stats
on option_stats.poll_id = poll_stats.poll_id
where poll_stats.poll_id <> 1
order by 3 desc, option_responses desc