Here's the schema and data that i am working with
CREATE TABLE tbl (
name varchar(20) not null,
groups int NOT NULL
);
insert into tbl values('a', 35);
insert into tbl values('a', 36);
insert into tbl values('b', 35);
insert into tbl values('c', 36);
insert into tbl values('d', 37);
| name | groups|
|------|-------|
| a | 35 |
| a | 36 |
| b | 35 |
| c | 36 |
| d | 37 |
now i need names of only those that are having group greater than or equal to 35 but also an additional is that i can only include a row for which group=35 when a corresponding groups=36 is also present
| name | groups|
|------|-------|
| a | 35 |
| a | 36 |
second condition is that it CAN include those names that are having groups greater than or equal to 36 without having a groups=35
| name | groups|
|------|-------|
| c | 36 |
| d | 37 |
the only case it should leave out is where a record has only groups=35 present without a corresponding groups=36
| name | groups|
|------|-------|
| b | 35 |
i have tried the following
select name from tbl
where groups>=35
group by name
having count(distinct(groups))>=2
or groups>=36;
this is the error i am facing Column 'tbl.groups' is invalid in the HAVING clause because it is not contained in either an aggregate function or the GROUP BY clause.
Try this:
DECLARE @tbl table ( [name] varchar(20) not null, groups int NOT NULL );
INSERT INTO @tbl VALUES
('a', 35), ('a', 36), ('b', 35), ('c', 36), ('d', 37);
DECLARE @group int = 35;
; WITH cte AS (
SELECT
[name]
, COUNT ( DISTINCT groups ) AS distinct_group_count
FROM @tbl
WHERE
groups >= @group
GROUP BY
[name]
)
SELECT t.* FROM @tbl AS t
INNER JOIN cte
ON t.[name] = cte.[name]
WHERE
cte.distinct_group_count > 1
OR t.groups > @group;
RETURNS
+------+--------+
| name | groups |
+------+--------+
| a | 35 |
| a | 36 |
| c | 36 |
| d | 37 |
+------+--------+
Basically, this restricts the name results to groups with a value >= 35 with more than one distinct group associated, or any name with a group value greater than 35. Several assumptions were made in regard to your data, but I believe the logic still applies.