I have a interim table without any primary key and identity. I need to check one of the columns (branch_ref) value for duplicate entries and should mark the flag as 'D' if the branch_ref is same for more than one record except the last occurrence in the table. How can we do this?
Actual data as stored in table.
select branch_name,branch_reference,address_1,zip_cd,null as flag_val FROM Branch_Master
As per above table, I need all flag to be updated as ‘D’ except for 6th (brach_reference=9910) and 16th record (branch_reference=99100 and zip_cd=612).
When I use row_number function to identify the duplicates order gets changed.
SELECT branch_name,branch_reference,address_1,zip_cd,flag_val, ROW_NUMBER() OVER(PARTITION BY branch_reference ORDER BY branch_reference) RID
FROM Branch_Master
Am using below query to update flag_val and its updating wrong records.
;WITH CTE AS
(
SELECT branch_name,branch_reference,address_1,zip_cd,flag_val, ROW_NUMBER() OVER(PARTITION BY branch_reference ORDER BY branch_reference) RID
FROM Branch_Master
WHERE flag_val IS NULL
)
UPDATE C1 SET flag_val = 'D'
FROM CTE C1
LEFT OUTER JOIN (SELECT branch_reference, max(RID) MRID FROM CTE GROUP BY branch_reference) C2
ON C1.branch_reference=C2.branch_reference and C1.RID=C2.MRID
WHERE C2.branch_reference IS NULL
Related
I have two tables(Table A and Table B) in a Postgres DB.
Both have "id" column in common. Table A has one column called "id" and Table B has three columns: "id, date, value($)".
For each "id" of Table A there exists multiple rows in Table B in the following format - (id, date, value).
For instance, for Table A with "id" as 1 if there exists following rows in Table B:
(1, 2018-06-21, null)
(1, 2018-06-20, null)
(1, 2018-06-19, 202)
(1, 2018-06-18, 200)
I would like to extract the most recent dated non-null value. For example for id - 1, the result should be 202. Please share your thoughts or let me know in case more info is required.
Here is the solution I went ahead with:
with mapping as ( select distinct table1.id, table2.value, table2.date, row_number() over (partition by table1.id order by table2.date desc nulls last) as row_number
from table1
left join table2 on table2.id=table1.id and table2.value is not null
)
select * from mapping where row_number = 1
Let me know if there is scope for improvement.
You may very well want an inner join, not an outer join. If you have an id in table1 that does not exist in table2 or that has only null values you will get NULL for both date and value. This is due to the how outer join works. What it says is if nothing in the right side table matches the ON condition then return NULL for each column in that table. So
with mapping as
(select distinct table1.id
, table2.value
, table2.date
, row_number() over (partition by table1.id order by table2.date desc nulls last) as row_number
from table1
join table2 on table2.id=table1.id and table2.value is not null
)
select *
from mapping
where row_number = 1;
See example of each here. Your query worked because all your test data satisfied the 1st condition of the ON condition. You really need test data that fails to see what your query does.
Caution: DATE and VALUE are very poor choice for a column names. Both are SQL standard reserved words, although not Postgres specifically. Further DATE is a Postgres data type. Having columns with names the same as datatype leads to confusion.
I have created synthetic data for a typical call center.
Below is the screenshot of the table I have created.
Table 1:
Problem statement: Since this is completely random data, I noticed that there are some customers who are being assigned to the same agents whenever they call again.
So using this query I was able to test such a case and count the number of times agents are being repeated for each customer.
select agentid, customerid, count(customerid) from aa_dev.calls group by agentid, customerid having count(customerid) > 1 ;
Table 2
I have a separate agents table to called aa_dev.agents in which the agent's ids are stored
Now I want to replace the agentid for such cases, such that if agentid is repeated 6 times for a single customer then 5 of the times the agent id should be updated with any other agentid from the table but call time shouldn't be overlapping That means the agent we are replacing with should not be busy on the time the call is going one.
I have assigned row numbers to each repeated ones.
WITH cte AS (
SELECT *, ROW_NUMBER() OVER (PARTITION BY agentid, customerid ORDER BY random()) rn,
COUNT(*) OVER (PARTITION BY agentid, customerid) cnt
FROM aa_dev.calls
)
SELECT agentid, customerid, rn
FROM cte
WHERE cnt > 1;
This way I could visualize the repetition clearly.
So I don't want to update row 1 but the rest.
Is there any way I can acheive this? Can I use the row number and write a query according to the row number to update rownum 2 onwards row one by one with each row having a unique agent?
If you don't want duplicates in your artificial data, it's probably better to not generate them.
But if you already have a table with duplicates and want to work on the duplicates, either updating them or deleting, here is the easy way:
You need a unique ID for each updated row. If you don't have it,
add it temporarily. Then you can use this pattern to update all duplicates
except the first one:
To add artificial id column to preexisting table, use:
ALTER TABLE calls ADD id serial;
In my case I generated a test table with 100 random rows:
CREATE TEMP TABLE calls (id serial, agentid int, customerid int);
INSERT INTO calls (agentid, customerid)
SELECT (random()*10)::int, (random()*10)::int
FROM generate_series(1, 100) n;
Define what constitutes a duplicate and find duplicates in data:
SELECT agentid, customerid, count(*), array_agg(id) id
FROM calls
GROUP BY 1,2 HAVING count(*)>1
ORDER BY 1,2;
Update all the duplicate rows except first one with NULLs:
UPDATE calls SET agentid = whatever_needed
FROM (
SELECT array_agg(id) id, min(id) idmin FROM calls
GROUP BY agentid, customerid HAVING count(*)>1
) AS dup
WHERE calls.id = ANY(dup.id) AND calls.id <> dup.idmin;
Alternatively, remove all duplicates except first one:
DELETE FROM calls
USING (
SELECT array_agg(id) id, min(id) idmin FROM calls
GROUP BY agentid, customerid HAVING count(*)>1
) AS dup
WHERE calls.id = ANY(dup.id) AND calls.id <> dup.idmin;
I'm dealing with a pretty unique record matching problem within postgres right now. Essentially I have a table (A) with a lot of records in it, including a key value that I need to match on and the date of the record. Then I have this other table (B) that I want to match the first table on that key value. However, there can be multiple of the same 'key values' in both tables. To get around this I need to match the earliest key value from table A to the earliest key value to table B, the second earliest to the second earliest, and so on... However, if table B runs out of key value matches in table B then I want to default to the latest key value match in A, even though something else already matched on it.
My initial thought is to use a something like this on both tables:
ROW_NUMBER() OVER ( PARTITION BY key_value ORDER BY date) AS rank
And then join on the rank and key_value field. However, I'm not exactly sure how to get that default scenario to work with this method. And if records are added to one table and not the other and I try the join again, I feel like it might get out of sync.
My other thought was to use a cursor, but I'm really struggling to see how I'd implement that.
Any help would be greatly appreciated!
first you need number all your rows, the find the one with matching ranks.
After that match the one without matching to the latest_date
with cteA as (
SELECT *, ROW_NUMBER() OVER ( PARTITION BY key_value ORDER BY date) AS rank
FROM tableA
), cteB as (
SELECT *, ROW_NUMBER() OVER ( PARTITION BY key_value ORDER BY date) AS rank
FROM tableB
), ranked_match as (
SELECT ctA.*, cteB.*
FROM cteA
LEFT JOIN cteB
ON cteA.key_value = cteB.key_value
AND cteA.rank = cteB.rank
), latest_row as (
SELECT *, ROW_NUMBER() OVER ( PARTITION BY key_value ORDER BY date DESC) AS rank
FROM tableB
)
SELECT *
FROM ranked_match
WHERE cteB.key_value IS NOT NULL
UNION ALL
SELECT *
FROM ranked_match
JOIN latest_row
ON ranked_match.key_value = latest_row .key_value
WHERE cteB.key_value IS NULL
AND latest_row .rank = 1
So far I have come up with the below:
WHERE (extract(month FROM orders)) =
(SELECT min(extract(month from orderdate))
FROM orders)
However, that will consequently return zero to many rows, and in my case, many, because many orders exist within that same earliest (minimum) month, i.e. 4th February, 9th February, 15th Feb, ...
I know that a WHERE clause can contain multiple columns, so why wouldn't the below work?
WHERE (extract(day FROM orderdate)), (extract(month FROM orderdate)) =
(SELECT min(extract(day from orderdate)), min(extract(month FROM orderdate))
FROM orders)
I simply get: SQL Error: ORA-00920: invalid relational operator
Any help would be great, thank you!
Sample data:
02-Feb-2012
14-Feb-2012
22-Dec-2012
09-Feb-2013
18-Jul-2013
01-Jan-2014
Output:
02-Feb-2012
14-Feb-2012
Desired output:
02-Feb-2012
I recreated your table and found out you just messed up the brackets a bit. The following works for me:
where
(extract(day from OrderDate),extract(month from OrderDate))
=
(select
min(extract(day from OrderDate)),
min(extract(month from OrderDate))
from orders
)
Use something like this:
with cte1 as (
select
extract(month from OrderDate) date_month,
extract(day from OrderDate) date_day,
OrderNo
from tablename
), cte2 as (
select min(date_month) min_date_month, min(date_day) min_date_day
from cte1
)
select cte1.*
from cte1
where (date_month, date_day) = (select min_date_month, min_date_day from cte2)
A common table expression enables you to restructure your data and then use this data to do your select. The first cte-block (cte1) selects the month and the day for each of your table rows. Cte2 then selects min(month) and min(date). The last select then combines both ctes to select all rows from cte1 that have the desired month and day.
There is probably a shorter solution to that, however I like common table expressions as they are almost all the time better to understand than the "optimal, shortest" query.
If that is really what you want, as bizarre as it seems, then as a different approach you could forget the extracts and the subquery against the table to get the minimums, and use an analytic approach instead:
select orderdate
from (
select o.*,
row_number() over (order by to_char(orderdate, 'MMDD')) as rn
from orders o
)
where rn = 1;
ORDERDATE
---------
01-JAN-14
The row_number() effectively adds a pseudo-column to every row in your original table, based on the month and day in the order date. The rn values are unique, so there will be one row marked as 1, which will be from the earliest day in the earliest month. If you have multiple orders with the same day/month, say 01-Jan-2013 and 01-Jan-2014, then you'll still only get exactly one with rn = 1, but which is picked is indeterminate. You'd need to add further order by conditions to make it deterministic, but I have no idea what you might want.
That is done in the inner query; the outer query then filters so that only the records marked with rn = 1 is returned; so you get exactly one row back from the overall query.
This also avoids the situation where the earliest day number is not in the earliest month number - say if you only had 01-Jan-2014 and 02-Feb-2014; comparing the day and month separately would look for 01-Feb-2014, which doesn't exist.
SQL Fiddle (with Thomas Tschernich's anwer thrown in too, giving the same result for this data).
To join the result against your invoice table, you don't need to join to the orders table again - especially not with a cross join, which is skewing your results. You can do the join (at least) two ways:
SELECT
o.orderno,
to_char(o.orderdate, 'DD-MM-YYYY'),
i.invno
FROM
(
SELECT o.*,
row_number() over (order by to_char(orderdate, 'MMDD')) as rn
FROM orders o
) o, invoices i
WHERE i.invno = o.invno
AND rn = 1;
Or:
SELECT
o.orderno,
to_char(o.orderdate, 'DD-MM-YYYY'),
i.invno
FROM
(
SELECT orderno, orderdate, invno
FROM
(
SELECT o.*,
row_number() over (order by to_char(orderdate, 'MMDD')) as rn
FROM orders o
)
WHERE rn = 1
) o, invoices i
WHERE i.invno = o.invno;
The first looks like it does more work but the execution plans are the same.
SQL Fiddle with your pastebin-supplied query that gets two rows back, and these two that get one.
I am trying to removing duplicate values which, for some reason, was imported in a specific Table.
There is no Primary Key in this table.
There is 27797 unique records.
Select distinct txdate, plunumber from itemaudit
Give me the correct records, but only displays the txdate, plunumber of course.
If it was possible to select all the fields but only select the distinct of txdate,plunumber I could export the values, delete the duplicated ones and re-import.
Or if its possible to delete the distinct values from the entire table.
If you select the distinct of all fields the value is incorrect.
To get all information on the duplicates, you simply need to query all information for the duplicate rows using a JOIN:
SELECT b.*
FROM (SELECT COUNT(*) as cnt, txdate, plunumber
FROM itemaudit
GROUP BY txdate, plunumber
HAVING COUNT(*) > 1) a
INNER JOIN itemaudit b ON a.txdate = b.txdate AND a.plunumber = b.plunumber
DELETE FROM itemaudit t1
WHERE EXISTS (
SELECT 1 FROM itemaudit t2
WHERE t1.txdate = t2.txdate and t1.plunumber = t2.plunumber
AND t1.RDB$DB_KEY < t2.RDB$DB_KEY
);