the goal is to retrieve the number of users in one table which have:
field EXPIREDATE > CURRENT_TIMESTAMP as nUsersActive
field EXPIREDATE < CURRENT_TIMESTAMP as nUsersExpired
field EXPIREDATE IS NULL as nUsersPreregistered
all with one query, and the result should for example be
nUsersActive nUsersExpired nUsersPreregistered
10 2 15
this will later be json_encoded and passed to an ExtJS script for displaying.
Any hint? I tried several times without succeding. I tried with the UNION statement, I get the right numbers, but of course in column, while I need them in row.
Thanks for your support.
Something like the following should work, you may need to adjust for the specific database that you are using.
To get them in columns:
select
count(case when EXPIREDATE > CURRENT_TIMESTAMP then 1 end) AS nUsersActive,
count(case when EXPIREDATE < CURRENT_TIMESTAMP then 1 end) AS nUsersExpired,
count(case when EXPIREDATE IS NULL then 1 end) AS nUserPreregistered
from users_table
And in rows (this is not as efficient!):
select
'nUsersActive' AS Param
count(case when EXPIREDATE > CURRENT_TIMESTAMP then 1 end) AS Value
from users_table
UNION ALL
select 'nUsersExpired',
count(case when EXPIREDATE < CURRENT_TIMESTAMP then 1 end)
from users_table
UNION ALL
select 'nUserPreregistered',
count(case when EXPIREDATE IS NULL then 1 end)
from users_table
I'm assuming you are using SQL Server. You should be able to get what you're looking for by using a CASE statement. Make sure you return something (anything) if the condition is true and NULL if the condition is false. Here is the msdn documentation: http://msdn.microsoft.com/en-us/library/ms181765.aspx
Your query would look something like this:
select COUNT(CASE WHEN #ThingToCheck = 'Value' THEN 1 ELSE NULL END) as Count1, COUNT(CASE WHEN #ThingToCheck = 'Value' THEN 1 ELSE NULL END) FROM ....
SELECT COUNT(CASE WHEN EXPIREDATE > CURRENT_TIMESTAMP THEN 1 END) AS nUsersActive,
COUNT(CASE WHEN EXPIREDATE < CURRENT_TIMESTAMP THEN 1 END) AS nUsersExpired,
COUNT(CASE WHEN EXPIREDATE IS NULL THEN 1 END) AS nUsersPreregistered
FROM Users
Related
I have a bit of sql code that look similar to this:
select sum(case when latitude = '0' then 1 else 0 end) as count_zero,
sum(case when latitude is NULL then 1 else 0 end) as count_null,
sum((case when latitude = '0' then 1 else 0 end) +
(case when latitude is NULL then 1 else 0 end)
) as total_zero,
count(latitude) as count_not_nulls,
count(*) as total
from sites_database
Is there a "cleaner" way to write this same query. I have tried using the "sum" expression using the column alias, something like:
Sum(count_zero + count_null) as total_null
But this doesn't seem to work for some reason
You could use COUNT instead of SUM:
SELECT
COUNT(CASE WHEN latitude = '0' THEN 1 END) As count_zero,
COUNT(CASE WHEN latitude IS NULL THEN 1 END) AS count_null,
COUNT(CASE WHEN COALESCE(latitude, '0') = '0' THEN 1 END) AS total_zero,
COUNT(latitude) As count_not_nulls,
COUNT(*) as total
FROM sites_database;
Using COUNT here saves a bit of coding, because we don't have to provide an explicit ELSE condition (the default ELSE is NULL, which just isn't counted at all). Also note that for the total_zero conditional sum, I used COALESCE to merge the two counts into just one.
Hello guys i need to use mutiple where clause in one sql query as follows but it can't work please help me.
select (select count(total) as 'studentMarks1' from School where total <60 ),
(select count(total) as 'studentMarks2' from School where total >80 )
from School
where Id = '8'
You rather need to use CASE statement like
select SUM(case when total < 60 then 1 else 0 end) as 'studentMarks1',
sum(case when total > 80 then 1 else 0 end) as 'studentMarks2'
from School
where Id = '8'
You cau usually do this with an appropriate CASE statement:
SELECT COUNT(CASE WHEN total < 60 then 1 else NULL END)
, COUNT(CASE WHEN total > 80 then 1 else NULL END)
FROM School
WHERE ID = '8'
I use this SQL query to make status report by day:
CREATE TABLE TICKET(
ID INTEGER NOT NULL,
TITLE TEXT,
STATUS INTEGER,
LAST_UPDATED DATE,
CREATED DATE
)
;
Query:
SELECT t.created,
COUNT(CASE WHEN t.status = '1' THEN 1 END) as cnt_status1,
COUNT(CASE WHEN t.status = '2' THEN 1 END) as cnt_status2,
COUNT(CASE WHEN t.status = '3' THEN 1 END) as cnt_status3,
COUNT(CASE WHEN t.status = '4' THEN 1 END) as cnt_status4
FROM ticket t
GROUP BY t.created
How I can limit this query to last 7 days?
Also I would like to get the results split by day. Fow example I would like to group the first dates for 24 hours, second for next 24 hours and etc.
Expected result:
This might help:
SELECT TO_CHAR(t.created, 'YYYY-MM-DD') AS created_date,
COUNT(CASE WHEN t.status = '1' THEN 1 END) as cnt_status1,
COUNT(CASE WHEN t.status = '2' THEN 1 END) as cnt_status2,
COUNT(CASE WHEN t.status = '3' THEN 1 END) as cnt_status3,
COUNT(CASE WHEN t.status = '4' THEN 1 END) as cnt_status4
FROM ticket t
WHERE t.created >= SYSDATE-7
GROUP BY TO_CHAR(t.created, 'YYYY-MM-DD')
ORDER BY created_date;
I used the oracle function for date conversion. I'm sure you'll find the corresponding one for postgresql.
I've two query from same table but by two condition but how can I make two column for this two conditional count.
SELECT Count(*) FROM TBL_FT WHERE STATUS = 'X';
SELECT Count(*) FROM TBL_FT WHERE STATUS = 'Y' and
LOGDATE>trunc(sysdate);
You can use conditional aggregation:
SELECT
COUNT(CASE WHEN STATUS = 'X' THEN 1 END),
COUNT(CASE WHEN STATUS = 'Y' AND LOGDATE > trunc(sysdate) THEN 1 END)
FROM TBL_FT
You can also add a WHERE clause:
WHERE STATUS IN ('X', 'Y');
you can use something like this -
SELECT SUM(CASE
WHEN STATUS = 'X' THEN
1
ELSE
0
END) FIRST_VAL,
SUM(CASE
WHEN STATUS = 'Y'
AND LOGDATE > TRUNC(SYSDATE) THEN
1
ELSE
0
END) second_val
FROM TBL_FT;
I'm trying to analyze a funnel using event data in Redshift and have difficulties finding an efficient query to extract that data.
For example, in Redshift I have:
timestamp action user id
--------- ------ -------
2015-05-05 12:00 homepage 1
2015-05-05 12:01 product page 1
2015-05-05 12:02 homepage 2
2015-05-05 12:03 checkout 1
I would like to extract the funnel statistics. For example:
homepage_count product_page_count checkout_count
-------------- ------------------ --------------
100 50 25
Where homepage_count represent the distinct number of users who visited the homepage, product_page_count represents the distinct numbers of users who visited the homepage after visiting the homepage, and checkout_count represents the number of users who checked out after visiting the homepage and the product page.
What would be the best query to achieve that with Amazon Redshift? Is it possible to do with a single query?
I think the best method might be to add flags to the data for the first visit of each type for each user and then use these for aggregation logic:
select sum(case when ts_homepage is not null then 1 else 0 end) as homepage_count,
sum(case when ts_productpage > ts_homepage then 1 else 0 end) as productpage_count,
sum(case when ts_checkout > ts.productpage and ts.productpage > ts.homepage then 1 else 0 end) as checkout_count
from (select userid,
min(case when action = 'homepage' then timestamp end) as ts_homepage,
min(case when action = 'product page' then timestamp end) as ts_productpage,
min(case when action = 'checkout' then timestamp end) as ts_checkout
from table t
group by userid
) t
The above answer is very much correct . I have modified it for people using it for AWS Mobile Analytics and Redshift.
select sum(case when ts_homepage is not null then 1 else 0 end) as homepage_count,
sum(case when ts_productpage > ts_homepage then 1 else 0 end) as productpage_count,
sum(case when ts_checkout > ts_productpage and ts_productpage > ts_homepage then 1 else 0 end) as checkout_count
from (select client_id,
min(case when event_type = 'App Launch' then event_timestamp end) as ts_homepage,
min(case when event_type = 'SignUp Success' then event_timestamp end) as ts_productpage,
min(case when event_type = 'Start Quiz' then event_timestamp end) as ts_checkout
from awsma.v_event
group by client_id
) ts;
Just in case more precise model required: when product page can be opened twice. First time before home page and second one after. This case usually should be considered as conversion as well.
Redshift SQL query:
SELECT
COUNT(
DISTINCT CASE WHEN cur_homepage_time IS NOT NULL
THEN user_id END
) Step1,
COUNT(
DISTINCT CASE WHEN cur_homepage_time IS NOT NULL AND cur_productpage_time IS NOT NULL
THEN user_id END
) Step2,
COUNT(
DISTINCT CASE WHEN
cur_homepage_time IS NOT NULL AND cur_productpage_time IS NOT NULL AND cur_checkout_time IS NOT NULL
THEN user_id END
) Step3
FROM (
SELECT
user_id,
timestamp,
COALESCE(homepage_time,
LAG(homepage_time) IGNORE NULLS OVER(PARTITION BY user_id
ORDER BY time)
) cur_homepage_time,
COALESCE(productpage_time,
LAG(productpage_time) IGNORE NULLS OVER(PARTITION BY distinct_id
ORDER BY time)
) cur_productpage_time,
COALESCE(checkout_time,
LAG(checkout_time) IGNORE NULLS OVER(PARTITION BY distinct_id
ORDER BY time)
) cur_checkout_time
FROM
(
SELECT
timestamp,
user_id,
(CASE WHEN event = 'homepage'
THEN timestamp END) homepage_time,
(CASE WHEN event = 'product page'
THEN timestamp END) productpage_time,
(CASE WHEN event = 'checkout'
THEN timestamp END) checkout_time
FROM events
WHERE timestamp > '2016-05-01' AND timestamp < '2017-01-01'
ORDER BY user_id, timestamp
) event_times
ORDER BY user_id, timestamp
) event_windows
This query fills each row's cur_homepage_time, cur_productpage_time and cur_checkout_time with recent timestamp of event occurrences. So in case for some specific time (read row) event occured then particular column is not NULL.
More info here.