pivot/cross distinct row data to colums with postgres - sql

I have distinct data that I want to pivot/cross, for instance
Given table A with
name tag
Bob sport
Bob action
Bob comedy
Tom action
Tom drama
Sue sport
I'd like a query that transforms the data to
name sport action comedy drama
Bob 1 1 1 0
Tom 0 1 0 1
Sue 1 0 0 0
For any number n of distinct tags.
How would I create this transformation using sql if I didn't know the distinct tags before I begin.

Some simple solutions adequate for some cases. Using this table (SQL Fiddle is not working right now)
create table a (
name text,
tag text
);
insert into a (name, tag) values
('Bob', 'sport'),
('Bob', 'action'),
('Bob', 'comedy'),
('Tom', 'action'),
('Tom', 'drama'),
('Sue', 'sport');
A simple arrays aggregation if they can be split somewhere else
select
name,
array_agg(tag order by tag) as tags,
array_agg(total order by tag) as totals
from (
select name, tag, count(a.name) as total
from
a
right join (
(select distinct tag from a) t
cross join
(select distinct name from a) n
) c using (name, tag)
group by name, tag
) s
group by name
order by 1
;
name | tags | totals
------+-----------------------------+-----------
Bob | {action,comedy,drama,sport} | {1,1,0,1}
Sue | {action,comedy,drama,sport} | {0,0,0,1}
Tom | {action,comedy,drama,sport} | {1,0,1,0}
For JSON aware clients a set of JSON objects
select format(
'{%s:{%s}}',
to_json(name),
string_agg(o, ',')
)::json as o
from (
select name,
format(
'%s:%s',
to_json(tag),
to_json(count(a.name))
) as o
from
a
right join (
(select distinct tag from a) t
cross join
(select distinct name from a) n
) c using (name, tag)
group by name, tag
) s
group by name
;
o
-----------------------------------------------------
{"Bob":{"action":1,"comedy":1,"drama":0,"sport":1}}
{"Sue":{"action":0,"comedy":0,"drama":0,"sport":1}}
{"Tom":{"action":1,"comedy":0,"drama":1,"sport":0}}
or a single JSON object
select format('{%s}', string_agg(o, ','))::json as o
from (
select format(
'%s:{%s}',
to_json(name),
string_agg(o, ',')
) as o
from (
select name,
format(
'%s:%s',
to_json(tag),
to_json(count(a.name))
) as o
from
a
right join (
(select distinct tag from a) t
cross join
(select distinct name from a) n
) c using (name, tag)
group by name, tag
) s
group by name
) s
;
o
---------------------------------------------------------------------------------------------------------------------------------------------------------
{"Bob":{"action":1,"comedy":1,"drama":0,"sport":1},"Sue":{"action":0,"comedy":0,"drama":0,"sport":1},"Tom":{"action":1,"comedy":0,"drama":1,"sport":0}}

Related

SQL: rows that share several values on a specific column

I have a table Visited with 2 columns:
ID | City
ID is an integer, City is a string.
Note that none of the columns is a key by itself - we can have the same ID visiting several cities, and several different IDs in the same city.
Given a specific ID, I want to return all the IDs in the table that visited at least half of the places that the input ID did (not including themselves)
edit: We only count places that are the same.
so if
ID 1 visited cities a,b,c.
ID 2 visited b,c,d.
ID 3 visited c,d,e.
then for ID=1 we return only [2], because out of the three cities ID1 visited, ID3 visited only one
Inner join the visited table with the list of cities visited by the specific id, then select ids with at least half of the number of rows when grouped by id.
with u as
(select city as visitedBySpecificId from visited where id = *specificId*),
v as
(select * from visited inner join u on city = visitedBySpecificId where id <> *specificId*)
(select id from v group by id having count(*) >= (select count(*) from u)/2.0)
Fiddle
Join them and compare the counts.
create table suspect_tracking (id int, city varchar(30))
insert into suspect_tracking values
(1, 'Brussels'), (1,'London'), (1,'Paris')
, (1,'New York'), (1,'Bangkok'), (1, 'Hong Kong')
, (1,'Dubai'), (1,'Singapoor'), (1,'Rome')
, (1,'Macau'), (1, 'Istanbul'), (1,'Kuala Lumpur')
, (1,'Dehli'), (1,'Tokyo'), (1,'Moscow')
, (2,'New York'), (2,'Bangkok'), (2, 'Hong Kong')
, (2,'Dubai'), (2,'Singapoor'), (2,'Rome')
, (2,'Macau'), (2, 'Istanbul'), (2,'Kuala Lumpur')
, (3,'Macau'), (3, 'Istanbul'), (3,'Kuala Lumpur')
, (3,'Dehli'), (3,'Tokyo'), (3,'Moscow')
with cte_suspects as (
select id, city
from suspect_tracking
group by id, city
)
, cte_prime_suspect as (
select distinct id, city
from suspect_tracking
where id = 1
)
, cte_prime_total as (
select id, count(city) as cities
from cte_prime_suspect
group by id
)
select sus.id
from cte_prime_suspect prime
join cte_prime_total primetot
on primetot.id = prime.id
join cte_suspects sus
on sus.city = prime.city and sus.id <> prime.id
group by prime.id, sus.id, primetot.cities
having count(sus.city) >= primetot.cities/2
| id |
| -: |
| 2 |
db<>fiddle here

LIMIT by distinct values in PostgreSQL

I have a table of contacts with phone numbers similar to this:
Name Phone
Alice 11
Alice 33
Bob 22
Bob 44
Charlie 12
Charlie 55
I can't figure out how to query such a table with LIMITing the rows not just by plain count but by distinct names. For example, if I had a magic LIMIT_BY clause, it would work like this:
SELECT * FROM "Contacts" ORDER BY "Phone" LIMIT_BY("Name") 1
Alice 11
Alice 33
-- ^ only the first contact
SELECT * FROM "Contacts" ORDER BY "Phone" LIMIT_BY("Name") 2
Alice 11
Charlie 12
Alice 33
Charlie 55
-- ^ now with Charlie because his phone 12 goes right after 11. Bob isn't here because he's third, beyond the limit
How could I achieve this result?
In other words, select all rows containing top N distinct Names ordered by Phone
I don't think that PostgreSQL provides any particularly efficient way to do this, but for 6 rows it doesn't need to be very efficient. You could do a subquery to compute which people you want to see, then join that subquery back against the full table.
select * from
"Contacts" join
(select name from "Contacts" group by name order by min(phone) limit 2) as limited
using (name)
You could put the subquery in an IN-list rather than a JOIN, but that often performs worse.
If you want all names that are in the first n rows, you can use in:
select t.*
from t
where t.name in (select t2.name
from t t2
order by t2.phone
limit 2
);
If you want the first n names by phone:
select t.*
from t
where t.name in (select t2.name
from t t2
group by t2.name
order by min(t2.phone)
limit 2
);
try this:
SELECT distinct X.name
,X.phone
FROM (
SELECT *
FROM (
SELECT name
,rn
FROM (
SELECT name
,phone
,row_number() OVER (
ORDER BY phone
) rn
FROM "Contacts"
) AA
) DD
WHERE rn <= 2 --rn is the "limit" variable
) EE
,"Contacts" X
WHERE EE.name = X.name
above seems to be working correctly on following dataset:
create table "Contacts" (name text, phone text);
insert into "Contacts" (name, phone) VALUES
('Alice', '11'),
('Alice', '33'),
('Bob', '22'),
('Bob', '44'),
('Charlie', '13'),
('Charlie', '55'),
('Dennis', '12'),
('Dennis', '66');

Convert Comma separated ids into its assigned values

I am writing a view for the Data export feature ,So basically they need view all the columns with data associated to it.
I have a column in a table Languages Spoken and we are storing values as comma separated list 1,2,3 ....etc.,
where as 1 is english , 2 germany ,3 Spanish etc. this value is stored in different table.
StaffID LanguagesSpoken
---------- -------------
1 1,2,3
2 3,4
3 2,5
So when we want to view the the expected out should be
StaffID LanguagesSpoken
---------- -------------
1 English, Germany, Spanish
2 Spanish,Hindi
3 Germany,Arabic
You can use the following to split the LanguagesSpoken string, do a join with Language table and use string_agg to get what you want. As mentioned by others your schema design needs to be fixed so this will help you get the data into the new schema also:
SELECT StaffID, value
FROM StaffLanguagesSpoken
CROSS APPLY string_split(LanguagesSpoken, ",")
For a table containing the languages like this:
CREATE TABLE languages (
id INTEGER,
name VARCHAR(20)
);
INSERT INTO languages
(id, name)
VALUES
('1', 'English'),
('2', 'Germany'),
('3', 'Spanish'),
('4', 'Hindi'),
('5', 'Arabic');
you can join the tables, group by StaffID and use string_agg():
select
t.StaffID,
string_agg(l.name, ',') within group (order by l.id) LanguagesSpoken
from tablename t inner join languages l
on concat(',', t.languagesspoken, ',') like concat('%,', l.id, ',%')
group by t.StaffID
See the demo.
Results:
> StaffID | LanguagesSpoken
> ------: | :----------------------
> 1 | English,Germany,Spanish
> 2 | Spanish,Hindi
> 3 | Germany,Arabic

SQL for Exclude

I have a table which is a simple lists of ID numbers and NAMES - I am trying to write a SQL which only returns rows where the NAME does not have particular IDs.
This has been stumping me - the query below returns all as they have other IDs from the exclude lists (large range of IDs). How to structure a query where only those who don't have ID 2 or 3 are returned -- i.e. only returns 'bob' for table below.
select * from TABLE where ID not in (2, 3)
ID NAMES
1 bob
1 alice
2 alice
1 dave
2 dave
3 dave
4 dave
Thank you.
One method is group by and having:
select name
from t
group by name
having sum(case when ID in (2, 3) then 1 else 0 end) = 0;
If you want the original ids, you can add listagg(id, ',') within group (order by id) to the select. Or use not exists:
select t.*
from t
where not exists (select 1
from t t2
where t2.name = t.name and
t2.id in (2, 3)
);

How to synthesize attribute for joined tables

I have a view defined like this:
CREATE VIEW [dbo].[PossiblyMatchingContracts] AS
SELECT
C.UniqueID,
CC.UniqueID AS PossiblyMatchingContracts
FROM [dbo].AllContracts AS C
INNER JOIN [dbo].AllContracts AS CC
ON C.SecondaryMatchCodeFB = CC.SecondaryMatchCodeFB
OR C.SecondaryMatchCodeLB = CC.SecondaryMatchCodeLB
OR C.SecondaryMatchCodeBB = CC.SecondaryMatchCodeBB
OR C.SecondaryMatchCodeLB = CC.SecondaryMatchCodeBB
OR C.SecondaryMatchCodeBB = CC.SecondaryMatchCodeLB
WHERE C.UniqueID NOT IN
(
SELECT UniqueID FROM [dbo].DefinitiveMatches
)
AND C.AssociatedUser IS NULL
AND C.UniqueID <> CC.UniqueID
Which is basically finding contracts where f.e. the first name and the birthday are matching. This works great. Now I want to add a synthetic attribute to each row with the value from only one source row.
Let me give you an example to make it clearer. Suppose I have the following table:
UniqueID | FirstName | LastName | Birthday
1 | Peter | Smith | 1980-11-04
2 | Peter | Gray | 1980-11-04
3 | Peter | Gray-Smith| 1980-11-04
4 | Frank | May | 1985-06-09
5 | Frank-Paul| May | 1985-06-09
6 | Gina | Ericson | 1950-11-04
The resulting view should look like this:
UniqueID | PossiblyMatchingContracts | SyntheticID
1 | 2 | PeterSmith1980-11-04
1 | 3 | PeterSmith1980-11-04
2 | 1 | PeterSmith1980-11-04
2 | 3 | PeterSmith1980-11-04
3 | 1 | PeterSmith1980-11-04
3 | 2 | PeterSmith1980-11-04
4 | 5 | FrankMay1985-06-09
5 | 4 | FrankMay1985-06-09
6 | NULL | NULL [or] GinaEricson1950-11-04
Notice that the SyntheticID column uses ONLY values from one of the matching source rows. It doesn't matter which one. I am exporting this view to another application and need to be able to identify each "match group" afterwards.
Is it clear what I mean? Any ideas how this could be done in sql?
Maybe it helps to elaborate a bit on the actual use case:
I am importing contracts from different systems. To account for the possibility of typos or people that have married but the last name was only updated in one system, I need to find so called 'possible matches'. Two or more contracts are considered a possible match if they contain the same birthday plus the same first, last or birth name. That implies, that if contract A matches contract B, contract B also matches contract A.
The target system uses multivalue reference attributes to store these relationships. The ultimate goal is to create user objects for these contracts. The catch first is, that the shall only be one user object for multiple matching contracts. Thus I'm creating these matches in the view. The second catch is, that the creation of user objects happens by workflows, which run parallel for each contract. To avoid creating multiple user objects for matching contracts, each workflow needs to check, if there is already a matching user object or another workflow, which is about to create said user object. Because the workflow engine is extremely slow compared to sql, the workflows should not repeat the whole matching test. So the idea is, to let the workflow check only for the 'syntheticID'.
I have solved it with a multi step approach:
Create the list of possible 1st level matches for each contract
Create the base groups list, assigning a different group for for
each contract (as if they were not related to anybody)
Iterate the matches list updating the group list when more contracts need to
be added to a group
Recursively build up the SyntheticID from final group list
Output results
First of all, let me explain what I have understood, so you can tell if my approach is correct or not.
1) matching propagates in "cascade"
I mean, if "Peter Smith" is grouped up with "Peter Gray", it means that all Smith and all Gray are related (if they have the same birth date) so Luke Smith can be in the same group of John Gray
2) I have not understood what you mean with "Birth Name"
You say contracts matches on "first, last or birth name", sorry, I'm italian, I thought birth name and first were the same, also in your data there is not such column. Maybe it is related to that dash symbol between names?
When FirstName is Frank-Paul it means it should match both Frank and Paul?
When LastName is Gray-Smith it means it should match both Gray and Smith?
In following code I have simply ignored this problem, but it could be handled if needed (I already did a try, breaking names, unpivoting them and treating as double match).
Step Zero: some declaration and prepare base data
declare #cli as table (UniqueID int primary key, FirstName varchar(20), LastName varchar(20), Birthday varchar(20))
declare #comb as table (id1 int, id2 int, done bit)
declare #grp as table (ix int identity primary key, grp int, id int, unique (grp,ix))
declare #str_id as table (grp int primary key, SyntheticID varchar(1000))
declare #id1 as int, #g int
;with
t as (
select *
from (values
(1 , 'Peter' , 'Smith' , '1980-11-04'),
(2 , 'Peter' , 'Gray' , '1980-11-04'),
(3 , 'Peter' , 'Gray-Smith', '1980-11-04'),
(4 , 'Frank' , 'May' , '1985-06-09'),
(5 , 'Frank-Paul', 'May' , '1985-06-09'),
(6 , 'Gina' , 'Ericson' , '1950-11-04')
) x (UniqueID , FirstName , LastName , Birthday)
)
insert into #cli
select * from t
Step One: Create the list of possible 1st level matches for each contract
;with
p as(select UniqueID, Birthday, FirstName, LastName from #cli),
m as (
select p.UniqueID UniqueID1, p.FirstName FirstName1, p.LastName LastName1, p.Birthday Birthday1, pp.UniqueID UniqueID2, pp.FirstName FirstName2, pp.LastName LastName2, pp.Birthday Birthday2
from p
join p pp on (pp.Birthday=p.Birthday) and (pp.FirstName = p.FirstName or pp.LastName = p.LastName)
where p.UniqueID<=pp.UniqueID
)
insert into #comb
select UniqueID1,UniqueID2,0
from m
Step Two: Create the base groups list
insert into #grp
select ROW_NUMBER() over(order by id1), id1 from #comb where id1=id2
Step Three: Iterate the matches list updating the group list
Only loop on contracts that have possible matches and updates only if needed
set #id1 = 0
while not(#id1 is null) begin
set #id1 = (select top 1 id1 from #comb where id1<>id2 and done=0)
if not(#id1 is null) begin
set #g = (select grp from #grp where id=#id1)
update g set grp= #g
from #grp g
inner join #comb c on g.id = c.id2
where c.id2<>#id1 and c.id1=#id1
and grp<>#g
update #comb set done=1 where id1=#id1
end
end
Step Four: Build up the SyntheticID
Recursively add ALL (distinct) first and last names of group to SyntheticID.
I used '_' as separator for birth date, first names and last names, and ',' as separator for the list of names to avoid conflicts.
;with
c as(
select c.*, g.grp
from #cli c
join #grp g on g.id = c.UniqueID
),
d as (
select *, row_number() over (partition by g order by t,s) n1, row_number() over (partition by g order by t desc,s desc) n2
from (
select distinct c.grp g, 1 t, FirstName s from c
union
select distinct c.grp, 2, LastName from c
) l
),
r as (
select d.*, cast(CONVERT(VARCHAR(10), t.Birthday, 112) + '_' + s as varchar(1000)) Names, cast(0 as bigint) i1, cast(0 as bigint) i2
from d
join #cli t on t.UniqueID=d.g
where n1=1
union all
select d.*, cast(r.names + IIF(r.t<>d.t,'_',',') + d.s as varchar(1000)), r.n1, r.n2
from d
join r on r.g = d.g and r.n1=d.n1-1
)
insert into #str_id
select g, Names
from r
where n2=1
Step Five: Output results
select c.UniqueID, case when id2=UniqueID then id1 else id2 end PossibleMatchingContract, s.SyntheticID
from #cli c
left join #comb cb on c.UniqueID in(id1,id2) and id1<>id2
left join #grp g on c.UniqueID = g.id
left join #str_id s on s.grp = g.grp
Here is the results
UniqueID PossibleMatchingContract SyntheticID
1 2 1980-11-04_Peter_Gray,Gray-Smith,Smith
1 3 1980-11-04_Peter_Gray,Gray-Smith,Smith
2 1 1980-11-04_Peter_Gray,Gray-Smith,Smith
2 3 1980-11-04_Peter_Gray,Gray-Smith,Smith
3 1 1980-11-04_Peter_Gray,Gray-Smith,Smith
3 2 1980-11-04_Peter_Gray,Gray-Smith,Smith
4 5 1985-06-09_Frank,Frank-Paul_May
5 4 1985-06-09_Frank,Frank-Paul_May
6 NULL 1950-11-04_Gina_Ericson
I think that in this way the resulting SyntheticID should also be "unique" for each group
This creates a synthetic value and is easy to change to suit your needs.
DECLARE #T TABLE (
UniqueID INT
,FirstName VARCHAR(200)
,LastName VARCHAR(200)
,Birthday DATE
)
INSERT INTO #T(UniqueID,FirstName,LastName,Birthday) SELECT 1,'Peter','Smith','1980-11-04'
INSERT INTO #T(UniqueID,FirstName,LastName,Birthday) SELECT 2,'Peter','Gray','1980-11-04'
INSERT INTO #T(UniqueID,FirstName,LastName,Birthday) SELECT 3,'Peter','Gray-Smith','1980-11-04'
INSERT INTO #T(UniqueID,FirstName,LastName,Birthday) SELECT 4,'Frank','May','1985-06-09'
INSERT INTO #T(UniqueID,FirstName,LastName,Birthday) SELECT 5,'Frank-Paul','May','1985-06-09'
INSERT INTO #T(UniqueID,FirstName,LastName,Birthday) SELECT 6,'Gina','Ericson','1950-11-04'
DECLARE #PossibleMatches TABLE (UniqueID INT,[PossibleMatch] INT,SynKey VARCHAR(2000)
)
INSERT INTO #PossibleMatches
SELECT t1.UniqueID [UniqueID],t2.UniqueID [Possible Matches],'Ln=' + t1.LastName + ' Fn=' + + t1.FirstName + ' DoB=' + CONVERT(VARCHAR,t1.Birthday,102) [SynKey]
FROM #T t1
INNER JOIN #T t2 ON t1.Birthday=t2.Birthday
AND t1.FirstName=t2.FirstName
AND t1.LastName=t2.LastName
AND t1.UniqueID<>t2.UniqueID
INSERT INTO #PossibleMatches
SELECT t1.UniqueID [UniqueID],t2.UniqueID [Possible Matches],'Fn=' + t1.FirstName + ' DoB=' + CONVERT(VARCHAR,t1.Birthday,102) [SynKey]
FROM #T t1
INNER JOIN #T t2 ON t1.Birthday=t2.Birthday
AND t1.FirstName=t2.FirstName
AND t1.UniqueID<>t2.UniqueID
INSERT INTO #PossibleMatches
SELECT t1.UniqueID,t2.UniqueID,'Ln=' + t1.LastName + ' DoB=' + CONVERT(VARCHAR,t1.Birthday,102) [SynKey]
FROM #T t1
INNER JOIN #T t2 ON t1.Birthday=t2.Birthday
AND t1.LastName=t2.LastName
AND t1.UniqueID<>t2.UniqueID
INSERT INTO #PossibleMatches
SELECT t1.UniqueID,pm.UniqueID,'Ln=' + t1.LastName + ' Fn=' + + t1.FirstName + ' DoB=' + CONVERT(VARCHAR,t1.Birthday,102) [SynKey]
FROM #T t1
LEFT JOIN #PossibleMatches pm on pm.UniqueID=t1.UniqueID
WHERE pm.UniqueID IS NULL
SELECT *
FROM #PossibleMatches
ORDER BY UniqueID,[PossibleMatch]
I think this will work for you
SELECT
C.UniqueID,
CC.UniqueID AS PossiblyMatchingContracts,
FIRST_VALUE(CC.FirstName+CC.LastName+CC.Birthday)
OVER (PARTITION BY C.UniqueID ORDER BY CC.UniqueID) as SyntheticID
FROM
[dbo].AllContracts AS C INNER JOIN
[dbo].AllContracts AS CC ON
C.SecondaryMatchCodeFB = CC.SecondaryMatchCodeFB OR
C.SecondaryMatchCodeLB = CC.SecondaryMatchCodeLB OR
C.SecondaryMatchCodeBB = CC.SecondaryMatchCodeBB OR
C.SecondaryMatchCodeLB = CC.SecondaryMatchCodeBB OR
C.SecondaryMatchCodeBB = CC.SecondaryMatchCodeLB
WHERE
C.UniqueID NOT IN(
SELECT UniqueID FROM [dbo].DefinitiveMatches)
AND C.AssociatedUser IS NULL
You can try this:
SELECT
C.UniqueID,
CC.UniqueID AS PossiblyMatchingContracts,
FIRST_VALUE(CC.FirstName+CC.LastName+CC.Birthday)
OVER (PARTITION BY C.UniqueID ORDER BY CC.UniqueID) as SyntheticID
FROM
[dbo].AllContracts AS C
INNER JOIN
[dbo].AllContracts AS CC
ON
C.SecondaryMatchCodeFB = CC.SecondaryMatchCodeFB
OR
C.SecondaryMatchCodeLB = CC.SecondaryMatchCodeLB
OR
C.SecondaryMatchCodeBB = CC.SecondaryMatchCodeBB
OR
C.SecondaryMatchCodeLB = CC.SecondaryMatchCodeBB
OR
C.SecondaryMatchCodeBB = CC.SecondaryMatchCodeLB
WHERE
C.UniqueID NOT IN
(
SELECT UniqueID FROM [dbo].DefinitiveMatches
)
AND
C.AssociatedUser IS NULL
This will generate one extra row (because we left out C.UniqueID <> CC.UniqueID) but will give you the good souluton.
Following an example with some example data extracted from your original post. The idea: Generate all SyntheticID in a CTE, query all records with a "PossibleMatch" and Union it with all records which are not yet included:
DECLARE #t TABLE(
UniqueID int
,FirstName nvarchar(20)
,LastName nvarchar(20)
,Birthday datetime
)
INSERT INTO #t VALUES (1, 'Peter', 'Smith', '1980-11-04');
INSERT INTO #t VALUES (2, 'Peter', 'Gray', '1980-11-04');
INSERT INTO #t VALUES (3, 'Peter', 'Gray-Smith', '1980-11-04');
INSERT INTO #t VALUES (4, 'Frank', 'May', '1985-06-09');
INSERT INTO #t VALUES (5, 'Frank-Paul', 'May', '1985-06-09');
INSERT INTO #t VALUES (6, 'Gina', 'Ericson', '1950-11-04');
WITH ctePrep AS(
SELECT UniqueID, FirstName, LastName, BirthDay,
ROW_NUMBER() OVER (PARTITION BY FirstName, BirthDay ORDER BY FirstName, BirthDay) AS k,
FirstName+LastName+CONVERT(nvarchar(10), Birthday, 126) AS SyntheticID
FROM #t
),
cteKeys AS(
SELECT FirstName, BirthDay, SyntheticID
FROM ctePrep
WHERE k = 1
),
cteFiltered AS(
SELECT
C.UniqueID,
CC.UniqueID AS PossiblyMatchingContracts,
keys.SyntheticID
FROM #t AS C
JOIN #t AS CC ON C.FirstName = CC.FirstName
AND C.Birthday = CC.Birthday
JOIN cteKeys AS keys ON keys.FirstName = c.FirstName
AND keys.Birthday = c.Birthday
WHERE C.UniqueID <> CC.UniqueID
)
SELECT UniqueID, PossiblyMatchingContracts, SyntheticID
FROM cteFiltered
UNION ALL
SELECT UniqueID, NULL, FirstName+LastName+CONVERT(nvarchar(10), Birthday, 126) AS SyntheticID
FROM #t
WHERE UniqueID NOT IN (SELECT UniqueID FROM cteFiltered)
Hope this helps. The result looked OK to me:
UniqueID PossiblyMatchingContracts SyntheticID
---------------------------------------------------------------
2 1 PeterSmith1980-11-04
3 1 PeterSmith1980-11-04
1 2 PeterSmith1980-11-04
3 2 PeterSmith1980-11-04
1 3 PeterSmith1980-11-04
2 3 PeterSmith1980-11-04
4 NULL FrankMay1985-06-09
5 NULL Frank-PaulMay1985-06-09
6 NULL GinaEricson1950-11-04
Tested in SSMS, it works perfect. :)
--create table structure
create table #temp
(
uniqueID int,
firstname varchar(15),
lastname varchar(15),
birthday date
)
--insert data into the table
insert #temp
select 1, 'peter','smith','1980-11-04'
union all
select 2, 'peter','gray','1980-11-04'
union all
select 3, 'peter','gray-smith','1980-11-04'
union all
select 4, 'frank','may','1985-06-09'
union all
select 5, 'frank-paul','may','1985-06-09'
union all
select 6, 'gina','ericson','1950-11-04'
select * from #temp
--solution is as below
select ab.uniqueID
, PossiblyMatchingContracts
, c.firstname+c.lastname+cast(c.birthday as varchar) as synID
from
(
select a.uniqueID
, case
when a.uniqueID < min(b.uniqueID)over(partition by a.uniqueid)
then a.uniqueID
else min(b.uniqueID)over(partition by a.uniqueid)
end as SmallestID
, b.uniqueID as PossiblyMatchingContracts
from #temp a
left join #temp b
on (a.firstname = b.firstname OR a.lastname = b.lastname) AND a.birthday = b.birthday AND a.uniqueid <> b.uniqueID
) as ab
left join #temp c
on ab.SmallestID = c.uniqueID
Result capture is attached below:
Say we have following table (a VIEW in your case):
UniqueID PossiblyMatchingContracts SyntheticID
1 2 G1
1 3 G2
2 1 G3
2 3 G4
3 1 G4
3 4 G6
4 5 G7
5 4 G8
6 NULL G9
In your case you can set initial SyntheticID as a string like PeterSmith1980-11-04 using UniqueID for each line. Here is a recursive CTE query it divides all lines to unconnected groups and select MAX(SyntheticId) in the current group as a new SyntheticID for all lines in this group.
WITH CTE AS
(
SELECT CAST(','+CAST(UniqueID AS Varchar(100)) +','+ CAST(PossiblyMatchingContracts as Varchar(100))+',' as Varchar(MAX)) as GroupCont,
SyntheticID
FROM PossiblyMatchingContracts
UNION ALL
SELECT CAST(GroupCont+CAST(UniqueID AS Varchar(100)) +','+ CAST(PossiblyMatchingContracts as Varchar(100))+',' AS Varchar(MAX)) as GroupCont,
pm.SyntheticID
FROM CTE
JOIN PossiblyMatchingContracts as pm
ON
(
CTE.GroupCont LIKE '%,'+CAST(pm.UniqueID AS Varchar(100))+',%'
OR
CTE.GroupCont LIKE '%,'+CAST(pm.PossiblyMatchingContracts AS Varchar(100))+',%'
)
AND NOT
(
CTE.GroupCont LIKE '%,'+CAST(pm.UniqueID AS Varchar(100))+',%'
AND
CTE.GroupCont LIKE '%,'+CAST(pm.PossiblyMatchingContracts AS Varchar(100))+',%'
)
)
SELECT pm.UniqueID,
pm.PossiblyMatchingContracts,
ISNULL(
(SELECT MAX(SyntheticID) FROM CTE WHERE
(
CTE.GroupCont LIKE '%,'+CAST(pm.UniqueID AS Varchar(100))+',%'
OR
CTE.GroupCont LIKE '%,'+CAST(pm.PossiblyMatchingContracts AS Varchar(100))+',%'
))
,pm.SyntheticID) as SyntheticID
FROM PossiblyMatchingContracts pm