Hi Given that I have a table with 2 columns.
Table Booking
Column Amount-TransactionDate
Get me total Amount between Last 2 transactionDate.
How do you do that ?How do you get the last transaction but 01
Any suggestions?
You can use a common table expression (CTE) to assign a sequence number to each row based on descending order of the transaction date. And then select the rows with a filter to get the last 2 rows.
This query displays the last two transactions in the table
WITH BookingCTE AS (
SELECT ROW_NUMBER() OVER (ORDER BY TransactionDate DESC) as Sequence,
Amount, TransactionDate
FROM Booking
)
SELECT Sequence, Amount, TransactionDate
FROM BookingCTE
WHERE Sequence <= 2
;
This query give you the total amount for the last two transactions.
WITH BookingCTE AS (
SELECT ROW_NUMBER() OVER (ORDER BY TransactionDate DESC) as Sequence, Amount, TransactionDate
FROM Booking
)
SELECT SUM(Amount) AS TotalAmount
FROM BookingCTE
WHERE Sequence <= 2
;
Related
I am attempting to pull 10 random records from each month of this year using this query here but I get an error "ERROR: relation "c1" does not exist
"
Not sure where I'm going wrong - I think it may be I'm using Mysql syntax instead, but how do I resolve this?
My desired output is like this
Month
Another header
2021-01
random email 1
2021-01
random email 2
total of ten random emails from January, then ten more for each month this year (til November of course as Dec yet to happen)..
With CTE AS
(
Select month,
email,
Row_Number() Over (Partition By month Order By FLOOR(RANDOM()*(1-1000000+1))) AS RN
From (
SELECT
DISTINCT(TO_CHAR(DATE_TRUNC('month', timestamp ), 'YYYY-MM')) AS month
,CASE
WHEN
JSON_EXTRACT_PATH_TEXT(json_extract_array_element_text (form_data,0),'name') = 'email'
THEN
JSON_EXTRACT_PATH_TEXT(json_extract_array_element_text (form_data,0),'value')
END AS email
FROM form_submits_y2 fs
WHERE fs.website_id IN (791)
AND month LIKE '2021%'
GROUP BY 1,2
ORDER BY 1 ASC
)
)
SELECT *
FROM CTE C1
LEFT JOIN
(SELECT RN
,month
,email
FROM CTE C2
WHERE C2.month = C1.month
ORDER BY RANDOM() LIMIT 10) C3
ON C1.RN = C3.RN
ORDER By month ASC```
You can't reference an outer table inside a derived table with a regular join. You need to use left join lateral to make that work
I did end up finding a more elegant solution to my query here via this source from github :
SELECT
month
,email
FROM
(
Select month,
email,
Row_Number() Over (Partition By month Order By FLOOR(RANDOM()*(1-1000000+1))) AS RN
From (
SELECT
TO_CHAR(DATE_TRUNC('month', timestamp ), 'YYYY-MM') AS month
,CASE
WHEN JSON_EXTRACT_PATH_TEXT(json_extract_array_element_text (form_data,0),'name') = 'email'
THEN JSON_EXTRACT_PATH_TEXT(json_extract_array_element_text (form_data,0),'value')
END AS email
FROM form_submits_y2 fs
WHERE fs.website_id IN (791)
AND month LIKE '2021%'
GROUP BY 1,2
ORDER BY 1 ASC
)
) q
WHERE
RN <=10
ORDER BY month ASC
I am writing a simple SQL query to get the latest record from every customer and to get the max of device_count if there are multiple records for a customer with same timestamp. However, the max function doesn't seem to take the max value though. Any help would be appreciated.
My SQL query -
select sub.customerid, max(sub.device_count) from(
SELECT customerid, device_count,
RANK() OVER
(
PARTITION by customerid
ORDER BY date_time desc
) AS rownum
FROM tableA) sub
WHERE rownum = 1
group by 1
Sample data:
customerid
device_count
date_time
A
3573
2021-07-26 02:15:09-05:00
A
4
2021-07-26 02:15:13-05:00
A
16988
2021-07-26 02:15:13-05:00
A
20696
2021-07-26 02:15:13-05:00
A
24655
2021-07-26 02:15:13-05:00
Desired Output should be to get the row with max device_count which is 24655 but I get 16988 as the output.
try to :
sort your table using ORDER BY customerid,device_count
Then apply the LAST_VALUE(device_count) window function aver the customerid partition.
Apply LAST_VALUE() to find the latest device_count (since it's sorted ascending, the last device_count value is the max).
You need to put device_count into the window function's order by and take out the aggregation:
select sub.customerid, device_count from(
SELECT customerid, device_count,
RANK() OVER
(
PARTITION by customerid
ORDER BY date_time desc, device_count desc
) AS rownum
FROM tableA) sub where rownum=1;
But if the top row for a customerid has ties (in both date_time and device_count fields) it will return all such ties. So better to replace RANK() with ROW_NUMBER().
Let's say I have an orders table with customer_id, order_total, and order_date columns. I'd like to build a report that shows all customers who haven't placed an order in the last 30 days, with a column for the total amount their last order was.
This gets all of the customers who should be on the report:
select customer, max(order_date), (select order_total from orders o2 where o2.customer = orders.customer order by order_date desc limit 1)
from orders
group by 1
having max(order_date) < NOW() - '30 days'::interval
Is there a better way to do this that doesn't require a subquery but instead uses a window function or other more efficient method in order to access the total amount from the most recent order? The techniques from How to select id with max date group by category in PostgreSQL? are related, but the extra having restriction seems to stop me from using something like DISTINCT ON.
demo:db<>fiddle
Solution with row_number window function (https://www.postgresql.org/docs/current/static/tutorial-window.html)
SELECT
customer, order_date, order_total
FROM (
SELECT
*,
first_value(order_date) OVER w as last_order,
first_value(order_total) OVER w as last_total,
row_number() OVER w as row_count
FROM orders
WINDOW w AS (PARTITION BY customer ORDER BY order_date DESC)
) s
WHERE row_count = 1 AND order_date < CURRENT_DATE - 30
Solution with DISTINCT ON (https://www.postgresql.org/docs/9.5/static/sql-select.html#SQL-DISTINCT):
SELECT
customer, order_date, order_total
FROM (
SELECT DISTINCT ON (customer)
*,
first_value(order_date) OVER w as last_order,
first_value(order_total) OVER w as last_total
FROM orders
WINDOW w AS (PARTITION BY customer ORDER BY order_date DESC)
ORDER BY customer, order_date DESC
) s
WHERE order_date < CURRENT_DATE - 30
Explanation:
In both solutions I am working with the first_value window function. The window function's frame is defined by customers. The rows within the customers' groups are ordered descending by date which gives the latest row first (last_value is not working as expected every time). So it is possible to get the last order_date and the last order_total of this order.
The difference between both solutions is the filtering. I showed both versions because sometimes one of them is significantly faster
The window function style is creating a row count within the frames. Every first row can be filtered later. This is done by adding a row_number window function. The benefit of this solution comes out when you are trying to filter the first two or three data sets. You simply have to change the filter from WHERE row_count = 1 to WHERE row_count = 2
But if you want only one single row per group you just need to ensure that the expected row per group is ordered to be the first row in the group. Then the DISTINCT ON function can delete all following rows. DISTINCT ON (customer) gives the first (ordered) row per customer group.
Try to join table on itself
select o1.customer, max(order_date),
from orders o1
join orders o2 on o1.id=o2.id
group by o1.customer
having max(o1.order_date) < NOW() - '30 days'::interval
Subqueries in select is a bad idea, because DB will execute a query for each row
If you use postgres you can also try to use CTE
https://www.postgresql.org/docs/9.6/static/queries-with.html
WITH t as (
select id, order_total from orders o2 where o2.customer = orders.customer
order by order_date desc limit 1
) select o1.customer, max(order_date),
from orders o1
join t t.id=o2.id
group by o1.customer
having max(order_date) < NOW() - '30 days'::interval
I have a table with duplicate entries and the objective is to get the distinct entries based on the latest time stamp.
In my case 'serial_no' will have duplicate entries but I select unique entries based on the latest time stamp.
Below query is giving me the unique results with the latest time stamp.
But my concern is I need to get the total of unique entries.
For example assume my table has 40 entries overall. With the below query I am able to get 20 unique rows based on the serial number.
But the 'total' is returned as 40 instead of 20.
Any help on this pls?
SELECT
*
FROM
(
SELECT
DISTINCT ON (serial_no) id,
serial_no,
name,
timestamp,
COUNT(*) OVER() as total
FROM
product_info
INNER JOIN my.account ON id = accountid
WHERE
lower(name) = 'hello'
ORDER BY
serial_no,
timestamp DESC OFFSET 0
LIMIT
10
) AS my_info
ORDER BY
serial_no asc
product_info table intially has this data
serial_no name timestamp
11212 pulp12 2018-06-01 20:00:01
11213 mango 2018-06-01 17:00:01
11214 grapes 2018-06-02 04:00:01
11215 orange 2018-06-02 07:05:30
11212 pulp12 2018-06-03 14:00:01
11213 mango 2018-06-03 13:00:00
After the distict query I got all unique results based on the latest
timestamp:
serial_no name timestamp total
11212 pulp12 2018-06-03 14:00:01 6
11213 mango 2018-06-03 13:00:00 6
11214 grapes 2018-06-02 04:00:01 6
11215 orange 2018-06-02 07:05:30 6
But total is appearing as 6 . I wanted the total to be 4 since it has
only 4 unique entries.
I am not sure how to modify my existing query to get this desired
result.
Postgres supports COUNT(DISTINCT column_name), so if I have understood your request, using that instead of COUNT(*) will work, and you can drop the OVER.
What you could do is move the window function to a higher level select statement. This is because window function is evaluated before distinct on and limit clauses are applied. Also, you can not include DISTINCT keyword within window functions - it has not been implemented yet (as of Postgres 9.6).
SELECT
*,
COUNT(*) OVER() as total -- here
FROM
(
SELECT
DISTINCT ON (serial_no) id,
serial_no,
name,
timestamp
FROM
product_info
INNER JOIN my.account ON id = accountid
WHERE
lower(name) = 'hello'
ORDER BY
serial_no,
timestamp DESC
LIMIT
10
) AS my_info
Additionally, offset is not required there and one more sorting is also superfluous. I've removed these.
Another way would be to include a computed column in the select clause but this would not be as fast as it would require one more scan of the table. This is obviously assuming that your total is strictly connected to your resultset and not what's beyond that being stored in the table, but gets filtered out.
select count(*), serial_no from product_info group by serial_no
will give you the number of duplicates for each serial number
The most mindless way of incorporating that information would be to join in a sub query
SELECT
*
FROM
(
SELECT
DISTINCT ON (serial_no) id,
serial_no,
name,
timestamp,
COUNT(*) OVER() as total
FROM
product_info
INNER JOIN my.account ON id = accountid
WHERE
lower(name) = 'hello'
ORDER BY
serial_no,
timestamp DESC OFFSET 0
LIMIT
10
) AS my_info
join (select count(*) as counts, serial_no from product_info group by serial_no) as X
on X.serial_no = my_info.serial_no
ORDER BY
serial_no asc
Just have a standard orders table:
order_id
order_date
customer_id
order_total
Trying to write a query that generates a column that shows the days since the last purchase, for each customer. If the customer had no prior orders, the value would be zero.
I have tried something like this:
WITH user_data AS (
SELECT customer_id, order_total, order_date::DATE,
ROW_NUMBER() OVER (
PARTITION BY customer_id ORDER BY order_date::DATE DESC
)
AS order_count
FROM transactions
WHERE STATUS = 100 AND order_total > 0
)
SELECT * FROM user_data WHERE order_count < 3;
Which I could feed into tableau, then use some table calculations to wrangle the data, but I really would like to understand the SQL approach. My approach also only analyzes the most recent 2 transactions, which is a drawback.
Thanks
You should use lag() function:
select *,
lag(order_date) over (partition by customer_id order by order_date)
as prior_order_date
from transactions
order by order_id
To have the number of days since last order, just subtract the prior order date from the current order date:
select *,
order_date- lag(order_date) over (partition by customer_id order by order_date)
as days_since_last_order
from transactions
order by order_id
The query selects null if there is no prior order. You can use coalesce() to change it to zero.
You indicated that you need to calculate number of days since the last purchase.
..Trying to write a query that generates a column that shows the days
since the last purchase
So, basically you need get a difference between now and last purchase date for each client. Query can be the following:
-- test DDL
CREATE TABLE orders (
order_id SERIAL PRIMARY KEY,
order_date DATE,
customer_id INTEGER,
order_total INTEGER
);
INSERT INTO orders(order_date, customer_id, order_total) VALUES
('01-01-2015'::DATE,1,2),
('01-02-2015'::DATE,1,3),
('02-01-2015'::DATE,2,4),
('02-02-2015'::DATE,2,5),
('03-01-2015'::DATE,3,6),
('03-02-2015'::DATE,3,7);
WITH orderdata AS (
SELECT customer_id,order_total,order_date,
(now()::DATE - max(order_date) OVER (PARTITION BY customer_id)) as days_since_purchase
FROM orders
WHERE order_total > 0
)
SELECT DISTINCT customer_id ,days_since_purchase FROM orderdata ORDER BY customer_id;