This code gives me a table of the unique values (without duplicates):
SELECT id, firstname, lastname, startdate, position
FROM (
SELECT id, firstname, lastname, startdate, position,
ROW_NUMBER() OVER (PARTITION BY (firstname, lastname) ORDER BY startdate DESC) rn
FROM people
) tmp
WHERE rn = 1;
What syntax would replace the current table with just the results of this one?
Alternatively, I could use WHERE rn <> 1 to get all the data I want to delete, but again, I am struggling to get the syntax of the DELETE right using this method.
Assuming values in firstname, lastname and startdate are never NULL, this simple query with a NOT EXISTS anti-semi-join does the job:
DELETE FROM people AS p
WHERE EXISTS (
SELECT FROM people AS p1
WHERE p1.firstname = p.firstname
AND p1.lastname = p.lastname
AND p1.startdate > p.startdate
);
It deletes every row where a newer copy exists, effectively keeping the latest row per group of peers. (Of course, (firstname, lastname) is a poor way of establishing identity. There are many distinct people with identical names. The demo may be simplified ...)
Can there be identical values in startdate? Then you need a tiebreaker ...
Typically faster than using a subquery with row_number(). There are a hundred and one ways to make this faster, depending on your precise situation and requirements. See:
How do I (or can I) SELECT DISTINCT on multiple columns?
If compared columns can be NULL, consider:
How to delete duplicate rows without unique identifier
There is a whole dedicated tag for duplicate-removal. Combine it with postgres to narrow down:
https://stackoverflow.com/questions/tagged/duplicates+postgresql
Related
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 need to write a sql code that probably is very simple but I am very new to it.
I need to find all the records from one table that have matching id (but no more than one) from the other table. eg. one table contains records of the employees and the second one with employees' telephone numbers. i need to find all employees with only one telephone no
Sample data would be nice. In absence of:
SELECT
employees.employee_id
FROM
employees
LEFT JOIN
(SELECT distinct on(employee_id) employee_id FROM emp_phone) AS phone
ON
employees.employee_id = phone.employee_id
WHERE
phone.employee_id IS NOT NULL;
You need a join of the 2 tables, group by employee and the condition in the having clause:
SELECT e.employee_id, e.name
FROM employees e INNER JOIN numbers n
ON e.employee_id = n.employee_id
GROUP BY e.employee_id, e.name
HAVING COUNT(*) = 1;
If there can be more than a few numbers per employee in the table with the employees' telephone numbers (calling it tel), then it's cheaper to avoid GROUP BY and HAVING which has to process all rows. Find employees with "unique" numbers using a self-anti-join with NOT EXISTS.
While you don't need more than the employee_id and their unique phone number, you don't even have to involve the employee table at all:
SELECT *
FROM tel t
WHERE NOT EXISTS (
SELECT FROM tel
WHERE employee_id = t.employee_id
AND tel_number <> t.tel_number -- or use PK column
);
If you need additional columns from the employee table:
SELECT * -- or any columns you need
FROM (
SELECT employee_id AS id, tel_number -- or any columns you need
FROM tel t
WHERE NOT EXISTS (
SELECT FROM tel
WHERE employee_id = t.employee_id
AND tel_number <> t.tel_number -- or use PK column
)
) t
JOIN employee e USING (id);
The column alias in the subquery (employee_id AS id) is just for convenience. Then the outer join condition can be USING (id), and the ID column is only included once in the result, even with SELECT * ...
Simpler with a smart naming convention that uses employee_id for the employee ID everywhere. But it's a widespread anti-pattern to use employee.id instead.
Related:
JOIN table if condition is satisfied, else perform no join
My table is somethingg like
CREATE TABLE table1
(
_id text,
name text,
data_type int,
data_value int,
data_date timestamp -- insertion time
);
Now due to a system bug, many duplicate entries are created and I need to remove those duplicated and keep only unique entries excluding data_date because it is a system generated date.
My query to do that is something like:
DELETE FROM table1 A
USING ( SELECT _id, name, data_type, data_value, MIN(data_date) min_date
FROM table1
GROUP BY _id, name, data_type, data_value
HAVING count(data_date) > 1) B
WHERE A._id = B._id
AND A.name = B.name
AND A.data_type = B.data_type
AND A.data_value = B.data_value
AND A.data_date != B.min_date;
However this query works, having millions of records in the table, I want a faster way for it. My idea is to create a new column with value as partition by [_id, name, data_type, data_value] or columns which are in group by. However, I could not find the way to create such column.
I would appretiate if any one may suggest a way to create such column.
Edit 1:
There is another thing to add, I don't want to use CTE or subquery for updating this new column because it will be same as my existing query.
The best way is simply creating a new table without duplicated records:
CREATE...
SELECT _id, name, data_type, data_value, MIN(data_date) min_date
FROM table1
GROUP BY _id, name, data_type, data_value;
Alternatively, you can create a rank and then filter, but a subquery is needed.
RANK() OVER (PARTITION BY your_variables ORDER BY data_date ASC) r
And then filter r=1.
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
Long story short, I took over a project and a table in the database is in serious need of de-duping. The table looks like this:
supply_req_id | int | [primary key]
supply_req_dt | datetime |
request_id | int | [foreign key]
supply_id | int | [foreign key]
is_disabled | bit |
The duplication is exists with records having the same request_id and supply_id. I'd like to find a best practice way to de-dupe this table.
[EDIT]
#Kirk_Broadhurst, thanks for the question. Since supply_req_id is not referenced anywhere else, I would answer by saying keep the first, delete any subsequent occurances.
Happy Holidays
This creates a rank for each row in the (supply_req_dt, request_id) grouping, starting with 1 = lowest supply_req_id. Any dupe has a value > 1
;WITH cDupes AS
(
SELECT
supply_req_id,
ROW_NUMBER() OVER (PARTITION BY supply_req_dt, request_id ORDER BY supply_req_id) AS RowNum
FROM
MyTable
)
DELETE
cDupes
WHERE
RowNum > 1
Then add a unique constraint or INDEX
CREATE UNIQUE INDEX IXU_NoDupes ON MyTable (supply_req_dt, request_id)
Seems like there should be a command for this, but maybe that's because I'm used to a different database server. Here's the relevant support doc:
How to remove duplicate rows from a table in SQL Server
http://support.microsoft.com/kb/139444
You need to clarify your rule for determining which record to keep in the case of a 'match' - the most recent, the earliest, the one that has is_disabled true, or false?
Once you've identified that rule, the rest is fairly simple:
select the records you want to keep - the distinct records
join back to the original table to get the ids for those records.
delete everthing where not in the joined dataset.
So let's say you want to keep the most recent records of any 'duplicate' pair. Your query would look like this:
DELETE FROM [table] WHERE supply_req_id NOT IN
(SELECT supply_req_id from [table] t
INNER JOIN
(SELECT MAX(supply_req_dt) dt, request_id, supply_id
FROM [table]
GROUP BY request_id, supply_id) d
ON t.supply_req_dt = d.dt
AND t.request_id = d.request_id
AND t.supply_id = d.supply_id)
The catch is that if the supply_req_dt is also duplicated, then you'll be keeping both of the duplicates. The fix is to do another group by and select the top id
select MAX(supply_req_id), supply_req_dt, request_id, supply_id
group by supply_req_dt, request_id, supply_id
as an interim step. But if you don't need to do that, don't bother with it.