I have the following SQL statement, which I think should update 1 field, using some pretty simple standard deviation logic, and based on ID and Date. I think the ID and Date has to be included to get everything aligned right. So, here is the code that I'm testing.
UPDATE Price_Test2
SET Vol30Days = STDEV(PX_BID) OVER (ORDER BY ID_CUSIP, AsOfDate ROWS BETWEEN 30 PRECEDING AND CURRENT ROW) FROM Price_Test2
WHERE ID_CUSIP in (SELECT DISTINCT ID_CUSIP FROM Price_Test2)
It seems like it should work fine, but something is off because I'm getting an error that says: Cannot use both a From clause and a subquery in the where clause or in the data values list in an Update statement.
I am using SQL Server 2019.
You are using aggregation functions in an update. What you want is an updatable subquery (or CTE):
UPDATE p
SET Vol30Days = new_Vol30Days,
Vol60Days = new_Vol60Days,
Vol90Days = new_Vol90Days
FROM (SELECT p.*,
STDEV(PX_BID) OVER (ORDER BY Date ROWS BETWEEN 30 PRECEDING AND CURRENT ROW) as new_Vol30day,
STDEV(PX_BID) OVER (ORDER BY Date ROWS BETWEEN 60 PRECEDING AND CURRENT ROW) as new_Vol60day,
STDEV(PX_BID) OVER (ORDER BY Date ROWS BETWEEN 90 PRECEDING AND CURRENT ROW) as new_Vol60day
FROM prices p
) p;
Related
I need to use the current row values in a condition used in a window function on a partition with range. See my example query I am looking for.
select
count(case when orderdate >=
(**current_row.orderdate** -30) then 1 end)
over (partition by customerid order by orderdate range between unbounded preceding and current row)
from xyz
Not getting correct syntax.
Please see below example output required. This is just an example, the 30 days and the logic is just a sample.
I have been given a task which I should look on items table and grab first item of 2019 and last item for 2019 and set the active flags on them as active , the query I wrote only I can grab one by one depends on the store, and it takes days to finish if I have no other choice, here is my query in SQL Server:
SELECT *
FROM NODES
WHERE NODE ID = 5562
AND DATE BETWEEN '2019/01/01' AND '2019/12/30'
Basically I need the first and the last item for the year, but the problem is every Node is a specific store which has many record and I have run the query for million of records in many Nodes, is it possible if I for example say OK SQL from the given nodes take first and last item for 2019 and display to me and then update their active flag = 'Y'
Is it possible with a CTE, do I need a CTE at all?
Thank you
If I understood correctly, you could try using a CTE with a windowed function to fetch only the first row from each store after ordering by date in ascending order and the first row from each store after ordering by date in descending order.
For instance :
CREATE TABLE NODES (NodeId int,NodeDate DATETIME2,status NVARCHAR(128))
INSERT INTO NODES(NodeId,NodeDate,Status) VALUES
(1,'2019/01/01','inactive'),
(1,'2019/03/01','inactive'),
(1,'2019/06/01','inactive'),
(1,'2019/09/01','inactive'),
(1,'2019/12/01','inactive'),
(2,'2019/01/01','inactive'),
(2,'2019/03/01','inactive'),
(2,'2019/06/01','inactive'),
(2,'2019/09/01','inactive'),
(2,'2019/12/01','inactive'),
(3,'2019/01/01','inactive'),
(3,'2019/03/01','inactive'),
(3,'2019/06/01','inactive'),
(3,'2019/09/01','inactive'),
(3,'2019/12/01','inactive')
;WITH cte AS
(
SELECT status,
ROW_NUMBER() OVER (PARTITION BY NodeId ORDER BY NodeDate ASC) AS FirstDate,
ROW_NUMBER() OVER (PARTITION BY NodeId ORDER BY NodeDate DESC) AS LastDate
FROM NODES
WHERE NodeDate >= '2019/01/01' AND NodeDate < '2020/01/01'
)
UPDATE CTE SET status = 'active'
WHERE FirstDate = 1 OR LastDate = 1
SELECT * FROM NODES
Try it online
Please do note however that this operation can be non deterministic if multiple rows have the same date.
See also :
Get top 1 row of each group
I am trying to create following logic in Alteryx and data is coming from Exasol database.
Column “Sum_Qty_28_days“ should sum up the values of “Qty ” column for same article which falls under last 28 days.
My sample data looks like:
and I want following output:
E.g. “Sum_Qty_28_days” value for “article” = ‘A’ and date = ‘’2019-10-8” is 8 because it is summing up the “Qty” values associated with dates (coming within previous 28 days) Which are:
2019-09-15
2019-10-05
2019-10-08
for “article” = ‘A’.
Is this possible using SQL window function?
I tried myself with following code:
SUM("Qty") OVER (PARTITION BY "article", date_trunc('month',"Date")
ORDER BY "Date")
But, it is far from what I need. It is summing up the Qty for dates falling in same month. However, I need to sum of Qty for last 28 days.
Thanks in advance.
Yes, this is possible using standard SQL and in many databases. However, this will not work in all databases:
select t.*,
sum(qty) over (partition by article
order by date
range between interval '27 day' preceding and current row
) as sum_qty_28_days
from t;
If your RDBMS does not support the range frame, an alternative solution is to use an inline subquery:
select
t.*,
(
select sum(t1.qty)
from mytable t1
where
t1.article = t.article
and t1.date between t.date - interval 28 days and t.date
) sum_qty_28_days
from mytable t
Hi I am a newbie when it comes to SQL and was hoping someone can help me in this matter. I've been using the lag function here and there but was wondering if there is a way to rewrite it to make it into a sum range. So instead of prior one month, i want to take the prior 12 months and sum them together for each period. I don't want to write 12 lines of lag but was wondering if there is a way to get it with less lines of code. Note there will be nulls and if one of the 12 records is null then it should be null.
I know you can write write subquery to do this, but was wondering if this is possible. Any help would be much appreciated.
You want the "window frame" part of the window function. A moving 12-month average would look like:
select t.*,
sum(balance) over (order by period rows between 11 preceding and current row) as moving_sum_12
from t;
You can review window frames in the documentation.
If you want a cumulative sum, you can leave out the window frame entirely.
I should note that you can also do this using lag(), but it is much more complicated:
select t.*,
(balance +
lag(balance, 1, 0) over (order by period) +
lag(balance, 2, 0) over (order by period) +
. . .
lag(balance, 11, 0) over (order by period) +
) as sum_1112
from t;
This uses the little known third argument to lag(), which is the default value to use if the record is not available. It replaces a coalesce().
EDIT:
If you want NULL if 12 values are not available, then use case and count() as well:
select t.*,
(case when count(*) over (order by period rows between 11 preceding and current row) = 12
then sum(balance) over (order by period rows between 11 preceding and current row)
end) as moving_sum_12
from t;
I want to see if the price of a stock has changed by 5% this week. I have data that captures the price everyday. I can get the rows from the last 7 days by doing the following:
select price from data where date(capture_timestamp)>date(current_timestamp)-7;
But then how do I analyze that and see if the price has increased or decreased 5%? Is it possible to do all this with one sql statement? I would like to be able to then insert any results of it into a new table but I just want to focus on it printing out in the shell first.
Thanks.
It seems odd to have only one stock in a table called data. What you need to do is bring the two rows together for last week's and today's values, as in the following query:
select d.price
from data d cross join
data dprev
where cast(d.capture_timestamp as date = date(current_timestamp) and
cast(dprev.capture_timestamp as date) )= cast(current_timestamp as date)-7 and
d.price > dprev.price * 1.05
If the data table contains the stock ticker, the cross join would be an equijoin.
You may be able to use query from the following subquery for whatever calculations you want to do. This is assuming one record per day. The 7 preceding rows is literal.
SELECT ticker, price, capture_ts
,MIN(price) OVER (PARTITION BY ticker ORDER BY capture_ts ROWS BETWEEN 7 PRECEDING AND CURRENT ROW) AS min_prev_7_records
,MAX(price) OVER (PARTITION BY ticker ORDER BY capture_ts ROWS BETWEEN 7 PRECEDING AND CURRENT ROW) AS max_prev_7_records
FROM data