I have a query against a large number of big tables (rows and columns) with a number of joins, however one of tables has some duplicate rows of data causing issues for my query. Since this is a read only realtime feed from another department I can't fix that data, however I am trying to prevent issues in my query from it.

Given that, I need to add this crap data as a left join to my good query. The data set looks like:

IDNo    FirstName   LastName    ...
-------------------------------------------
uqx     bob     smith
abc     john        willis
ABC     john        willis
aBc     john        willis
WTF     jeff        bridges
sss     bill        doe
ere     sally       abby
wtf     jeff        bridges
...

(about 2 dozen columns, and 100K rows)

My first instinct was to perform a distinct gave me about 80K rows:

SELECT DISTINCT P.IDNo
FROM people P

But when I try the following, I get all the rows back:

SELECT DISTINCT P.*
FROM people P

OR

SELECT 
    DISTINCT(P.IDNo) AS IDNoUnq 
    ,P.FirstName
    ,P.LastName
    ...etc.    
FROM people P

I then thought I would do a FIRST() aggregate function on all the columns, however that feels wrong too. Syntactically am I doing something wrong here?

Update: Just wanted to note: These records are duplicates based on a non-key / non-indexed field of ID listed above. The ID is a text field which although has the same value, it is a different case than the other data causing the issue.


distinct is not a function. It always operates on all columns of the select list.

Your problem is a typical "greatest N per group" problem which can easily be solved using a window function:

select ...
from (
  select IDNo,
         FirstName,
         LastName,
         ....,
         row_number() over (partition by lower(idno) order by firstname) as rn 
  from people 
) t
where rn = 1;

Using the order by clause you can select which of the duplicates you want to pick.

The above can be used in a left join, see below:

select ...
from x
  left join (
    select IDNo,
           FirstName,
           LastName,
           ....,
           row_number() over (partition by lower(idno) order by firstname) as rn 
    from people 
  ) p on p.idno = x.idno and p.rn = 1
where ...

Add an identity column (PeopleID) and then use a correlated subquery to return the first value for each value.

SELECT *
FROM People p
WHERE PeopleID = (
    SELECT MIN(PeopleID) 
    FROM People 
    WHERE IDNo = p.IDNo
)