I am trying to assign a specific code to a client based on the number of gifts that they have given in the past 6 months using a CASE. I am unable to use WITH (screenshot) due to the limitations of the software that I am creating the query in. It only allows for select functions. I am unsure how to get a distinct count from another table (transaction data) and use that as parameters in the CASE I have currently built (based on my client information table). Does anyone know of any workarounds for this? I am unable to GROUP BY clientID at the end of my query because not all of my columns are aggregate, and I only need to GROUP BY clientID for this particular WHEN statement in the CASE. I have looked into the OVER() clause, but I am needing my date range that I am evaluating to be dynamic (counting transactions over the last six months), and the amount of rows that I would be including is variable, as the transaction count month to month varies. Also, the software that I am building this in does not recognize the PARTITIONED BY parameter of the over clause.
Any help would be great!
EDIT:
it is not letting me attach an image... -____- I have added the two sections of code that I am looking for assistance with!
WITH "6MonthGIftCount" (
"ConstituentID"
,"GiftCount"
)
AS (
SELECT COUNT(DISTINCT "GiftView"."GiftID" FROM "GiftView" WHERE MONTHS_BETWEEN("GiftView"."GiftDate", getdate()) <= 6 GROUP BY "GiftView"."ConstituentID")
SELECT...CASE
WHEN "6MonthGiftCount"."GiftCount" >= 4
THEN 'A010'
)
Perform your grouping/COUNT(1) in a subquery to obtain the total # of donations by ConstituentID, then JOIN this total into your main query that uses this new column to perform its CASE statement.
select
hist.*,
case when timesDonated > 5 then 'gracious donor'
when timesDonated > 3 then 'repeated donor'
when timesDonated >= 1 then 'donor'
else null end as donorCode
from gifthistory hist
left join ( /* your grouping subquery here, pretending to be a new table */
select
personID,
count(1) as timesDonated
from gifthistory i
WHERE abs(months_between(giftDate, sysdate)) <= 6
group by personid ) grp on hist.personid = grp.personID
order by 1;
*Naturally, syntax changes will vary by DB; you didn't specify which it was based on, but you should be able to use this template with whichever you utilize. This works in both Oracle and SQL Server after tweaking the month calculation appropriately.
Related
I have a database called ‘tweets’. The database 'tweets' includes (amongst others) the rows 'tweet_id', 'created at' (dd/mm/yyyy hh/mm/ss), ‘classified’ and 'processed text'. Within the ‘processed text’ row there are certain strings such as {TICKER|IBM}', to which I will refer as ticker-strings.
My target is to get the average value of ‘classified’ per ticker-string per day. The row ‘classified’ includes the numerical values -1, 0 and 1.
At this moment, I have a working SQL query for the average value of ‘classified’ for one ticker-string per day. See the script below.
SELECT Date( `created_at` ) , AVG( `classified` ) AS Classified
FROM `tweets`
WHERE `processed_text` LIKE '%{TICKER|IBM}%'
GROUP BY Date( `created_at` )
There are however two problems with this script:
It does not include days on which there were zero ‘processed_text’s like {TICKER|IBM}. I would however like it to spit out the value zero in this case.
I have 100+ different ticker-strings and would thus like to have a script which can process multiple strings at the same time. I can also do them manually, one by one, but this would cost me a terrible lot of time.
When I had a similar question for counting the ‘tweet_id’s per ticker-string, somebody else suggested using the following:
SELECT d.date, coalesce(IBM, 0) as IBM, coalesce(GOOG, 0) as GOOG,
coalesce(BAC, 0) AS BAC
FROM dates d LEFT JOIN
(SELECT DATE(created_at) AS date,
COUNT(DISTINCT CASE WHEN processed_text LIKE '%{TICKER|IBM}%' then tweet_id
END) as IBM,
COUNT(DISTINCT CASE WHEN processed_text LIKE '%{TICKER|GOOG}%' then tweet_id
END) as GOOG,
COUNT(DISTINCT CASE WHEN processed_text LIKE '%{TICKER|BAC}%' then tweet_id
END) as BAC
FROM tweets
GROUP BY date
) t
ON d.date = t.date;
This script worked perfectly for counting the tweet_ids per ticker-string. As I however stated, I am not looking to find the average classified scores per ticker-string. My question is therefore: Could someone show me how to adjust this script in such a way that I can calculate the average classified scores per ticker-string per day?
SELECT d.date, t.ticker, COALESCE(COUNT(DISTINCT tweet_id), 0) AS tweets
FROM dates d
LEFT JOIN
(SELECT DATE(created_at) AS date,
SUBSTR(processed_text,
LOCATE('{TICKER|', processed_text) + 8,
LOCATE('}', processed_text, LOCATE('{TICKER|', processed_text))
- LOCATE('{TICKER|', processed_text) - 8)) t
ON d.date = t.date
GROUP BY d.date, t.ticker
This will put each ticker on its own row, not a column. If you want them moved to columns, you have to pivot the result. How you do this depends on the DBMS. Some have built-in features for creating pivot tables. Others (e.g. MySQL) do not and you have to write tricky code to do it; if you know all the possible values ahead of time, it's not too hard, but if they can change you have to write dynamic SQL in a stored procedure.
See MySQL pivot table for how to do it in MySQL.
I am having trouble in calculating the maximum of a row_number in my sql case.
I will explain it directly on the SQL Fiddle example, as I think it will be faster to understand: SQL Fiddle
Columns 'OrderNumber', 'HourMinute' and 'Code' are just to represent my table and hence, should not be relevant for coding purposes
Column 'DateOnly' contains the dates
Column 'Phone' contains the phones of my customers
Column 'Purchases' contains the number of times customers have bought in the last 12 months. Note that this value is provided for each date, so the 12 months time period is relative to the date we're evaluating.
Finally, the column I am trying to produce is the 'PREVIOUSPURCHASES' which counts the number of times the figure provided in the column 'Purchases' has appeared in the previous 12 months (for each phone).
You can see on the SQL Fiddle example what I have achieved so far. The column 'PREVIOUSPURCHASES' is producing what I want, however, it is also producing lower values (e.g. only the maximum one is the one I need).
For instance, you can see that rows 4 and 5 are duplicated, one with a 'PREVIOUSPURCHASES' of 1 and the other with 2. I don't want to have the 4th row, in this case.
I have though about replacing the row_number by something like max(row_number) but I haven't been able to produce it (already looked at similar posts at stackoverflow...).
This should be implemented in SQL Server 2012.
Thanks in advance.
I'm not sure what kind of result set you want to see but is there anything wrong with what's returned with this?
SELECT c.OrderNumber, c.DateOnly, c.HourMinute, c.Code, c.Phone, c.Purchases, MAX(o.PreviousPurchases)
FROM cte c CROSS APPLY (
SELECT t2.DateOnly, t2.Phone,t2.ordernumber, t2.Purchases, ROW_NUMBER() OVER(PARTITION BY c.DateOnly ORDER BY t2.DateOnly) AS PreviousPurchases
FROM CurrentCustomers_v2 t2
WHERE c.Phone = t2.Phone AND t2.purchases<=c.purchases AND DATEDIFF(DAY, t2.DateOnly, c.DateOnly) BETWEEN 0 AND 365
) o
WHERE c.OrderNumber = o.OrderNumber
GROUP BY c.OrderNumber, c.DateOnly, c.HourMinute, c.Code, c.Phone, c.Purchases
ORDER BY c.DateOnly
I have 2 similar queries which both work on the same table, and I essentially want to combine their results such that the second query supplies default values for what the first query doesn't return. I've simplified the problem as much as possible here. I'm using Oracle btw.
The table has account information in it for a number of accounts, and there are multiple entries for each account with a commit_date to tell when the account information was inserted. I need get the account info which was current for a certain date.
The queries take a list of account ids and a date.
Here is the query:
-- Select the row which was current for the accounts for the given date. (won't return anything for an account which didn't exist for the given date)
SELECT actr.*
FROM Account_Information actr
WHERE actr.account_id in (30000316, 30000350, 30000351)
AND actr.commit_date <= to_date( '2010-DEC-30','YYYY-MON-DD ')
AND actr.commit_date =
(
SELECT MAX(actrInner.commit_date)
FROM Account_Information actrInner
WHERE actrInner.account_id = actr.account_id
AND actrInner.commit_date <= to_date( '2010-DEC-30','YYYY-MON-DD ')
)
This looks a little ugly, but it returns a single row for each account which was current for the given date. The problem is that it doesn't return anything if the account didn't exist until after the given date.
Selecting the earliest account info for each account is trival - I don't need to supply a date for this one:
-- Select the earliest row for the accounts.
SELECT actr.*
FROM Account_Information actr
WHERE actr.account_id in (30000316, 30000350, 30000351)
AND actr.commit_date =
(
SELECT MAX(actrInner .commit_date)
FROM Account_Information actrInner
WHERE actrInner .account_id = actr.account_id
)
But I want to merge the result sets in such a way that:
For each account, if there is account info for it in the first result set - use that.
Otherwise, use the account info from the second result set.
I've researched all of the joins I can use without success. Unions almost do it but they will only merge for unique rows. I want to merge based on the account id in each row.
Sql Merging two result sets - my case is obviously more complicated than that
SQL to return a merged set of results - I might be able to adapt that technique? I'm a programmer being forced to write SQL and I can't quite follow that example well enough to see how I could modify it for what I need.
The standard way to do this is with a left outer join and coalesce. That is, your overall query will look like this:
SELECT ...
FROM defaultQuery
LEFT OUTER JOIN currentQuery ON ...
If you did a SELECT *, each row would correspond to the current account data plus your defaults. With me so far?
Now, instead of SELECT *, for each column you want to return, you do a COALESCE() on matched pairs of columns:
SELECT COALESCE(currentQuery.columnA, defaultQuery.columnA) ...
This will choose the current account data if present, otherwise it will choose the default data.
You can do this more directly using analytic functions:
select *
from (SELECT actr.*, max(commit_date) over (partition by account_id) as maxCommitDate,
max(case when commit_date <= to_date( '2010-DEC-30','YYYY-MON-DD ') then commit_date end) over
(partition by account_id) as MaxCommitDate2
FROM Account_Information actr
WHERE actr.account_id in (30000316, 30000350, 30000351)
) t
where (MaxCommitDate2 is not null and Commit_date = MaxCommitDate2) or
(MaxCommitDate2 is null and Commit_Date = MaxCommitDate)
The subquery calculates two values, the two possibilities of commit dates. The where clause then chooses the appropriate row, using the logic that you want.
I've combined the other answers. Tried it out at apex.oracle.com. Here's some explanation.
MAX(CASE WHEN commit_date <= to_date('2010-DEC-30', 'YYYY-MON-DD')) will give us the latest date not before Dec 30th, or NULL if there isn't one. Combining that with a COALESCE, we get
COALESCE(MAX(CASE WHEN commit_date <= to_date('2010-DEC-30', 'YYYY-MON-DD') THEN commit_date END), MAX(commit_date)).
Now we take the account id and commit date we have and join them with the original table to get all the other fields. Here's the whole query that I came up with:
SELECT *
FROM Account_Information
JOIN (SELECT account_id,
COALESCE(MAX(CASE WHEN commit_date <=
to_date('2010-DEC-30', 'YYYY-MON-DD')
THEN commit_date END),
MAX(commit_date)) AS commit_date
FROM Account_Information
WHERE account_id in (30000316, 30000350, 30000351)
GROUP BY account_id)
USING (account_id, commit_date);
Note that if you do use USING, you have to use * instead of acrt.*.
We have a ERP that integrates nicely with Crystal Reports.
Now, we can add filters through this application, and it passes these to the report (not as parameters but somehow adds this to the WHERE clause).
The problem is, when filtering dates, we have no way in the report to determine what date range the user selected (as we want to show this date on the report).
Any idea how I can show this through SQL?
I was thinking of using the dual table, and selecting a huge list of dates, then using the MIN and MAX of these dates to determine which was selected. The problem is, I can't join this onto my original query without adding LOTS of rows.
I have this so far:
SELECT
MIN(DTE) MIN_DTE,
MAX(DTE) MAX_DTE
FROM
(
SELECT
TRUNC(SYSDATE)-(5*365) + ROWNUM AS DTE
FROM
DUAL
CONNECT BY
ROWNUM <= (10*365)
)
WHERE
DTE >= '12-NOV-07'
AND DTE <= '12-DEC-07'
But the problem is I can't work out how to join that to my original query without upsetting the row cont.
Any other ideas?
That query returns only one row, so it won't upset the row count at all, unless there is something else going on (like, maybe, the automatic filtering doesn't work in subqueries).
Otherwise, this should work as expected:
SELECT q.*, max_min.*
FROM ( ... put your original query here ...) q,
( ... put the subquery that returns one row with max & min here ...) max_min
That's all to it.
I have 2 tables with no relations, both tables have different number of columns, but there are a few columns that are the same but hold different data. I was able to create a function or view of only the data I wanted, but when I try to count the data by filtering the date, I always get the wrong count in return. Let me explain by showing the 2 functions and what I try to do:
Function 1
ID - number from 1 to 8
data sent - YES or NO
Date - date value
Function 2
ID - number from 1 to 8
data sent - yes or no
date - date value
Upon running both separately, I get all the rows from the tables and everything looks good.
Then I try to add the following to each function:
select
count([data sent]), ID
from function1
Where (date between #date1 and #date2)
group by ID
The above statement works great and gives me the right result for each function.
Now I thought what if I want to add those 2 functions into one and get the count from both functions on 1 page.
So I created the following function:
Function 3
select
count(Function1.[data sent]) as Expr1,
Function1.id,
count(Function2.[data sent]) as Expr2,
Function1.date
from
Function1
LEFT OUTER JOIN
Function2 on Function1.id = Function2.id
Where
(Function1.date between #date1 and #date2)
group by
Function1.id
Upon running the above, I get the following table:
ID Expr1 Expr2
On both Expr1 and Expr2, I get results which I am not sure where they come from. I guess something is being multiplied by 100000 since one table holds almost 15000 rows and the other around 5000 rows.
What I would like to know first is if it possible at all to be able to filter by date and count records from both table at the same time. If anyone need more information please let me know and I will be glad to share and explain more.
Thank you
The LEFT OUTER JOIN is taking each row of the left table, finding ALL of the rows in the right table with the same id field, and creating that many rows in the result table. Since id isn't what we usually think of as an identity field (it looks more like a "deviceId" or something), you'll get lots of matches for each one. Repeat 15000 times and you get your combinatorial explosion.
Tip: To debug things like this, you can create sample tables with a tiny subset of the real data, say 10 rows from each, and run your query on them. You'll see the issue immediately.
It's possible to filter by date. It's hard to recommend an actual solution without better understanding your phrase "I want to add those 2 functions into one and get the count from both functions on 1 page".
Why can't you create a temporary table for each function then join them together?
Maybe subqueries can help you to achieve what you want:
SELECT
ID = COALESCE(f1.ID, f2.ID),
Date = COALESCE(f1.Date, f2.Date),
f1.Expr1,
f2.Expr2
FROM (
SELECT
ID,
Date,
Expr1 = COUNT([data sent])
FROM Function1
WHERE Date BETWEEN #date1 AND #date2
GROUP BY
ID,
Date
) f1
FULL JOIN (
SELECT
ID,
Date,
Expr2 = COUNT([data sent])
FROM Function2
WHERE Date BETWEEN #date1 AND #date2
GROUP BY
ID,
Date
) f2
ON f1.ID = f2.ID AND f1.Date = f2.Date
This query also uses full (outer) join instead of left join, in case the right side of the join contains rows that have no match in the left side (and you want those rows).