I have a table with field1, field2, field3, … and I need to count the number of items in field1 such that I return all records(field1,filed2,field3,…) that occur 6 times or less in the table.
My SQL code is:
SELECT field1, field2, field3, count(field1) CNT
FROM myTable
WHERE trunc(date) = tp_date(‘03/22/2011’,’mm/dd/yyyy’)
GROUP BY field1
HAVING COUNT(field1) < 7;
The output that I am getting from the above code is all records are returned from the table not what I expected? Any help would be appreciated!!
I think you need to use a subquery:
SELECT field1, field2, field3,
FROM myTable
WHERE trunc(date) = tp_date(‘03/22/2011’,’mm/dd/yyyy’)
AND field1 in
(SELECT field1
FROM mytable
GROUP BY field1
HAVING COUNT(field1) < 7);
WITH tmp AS
(
SELECT field1, COUNT(1) as CountOfField1
FROM myTable
WHERE trunc(date) = tp_date(‘03/22/2011’,’mm/dd/yyyy’)
GROUP BY field1
HAVING COUNT(field1) < 7
)
SELECT mytable.field1, mytable.field2, mytable.field3, tmp.CountOfField1
FROM myTable
INNER JOIN tmp
ON myTable.Field1 = tmp.Field1
Yet another way to do it:
SELECT t.field1, t.field2, t.field3,
FROM myTable t
WHERE trunc(t.date) = tp_date(‘03/22/2011’,’mm/dd/yyyy’)
AND EXISTS
( SELECT *
FROM mytable t2
WHERE t2.field1 = t.field1
AND trunc(t2.date) = tp_date(‘03/22/2011’,’mm/dd/yyyy’)
GROUP BY t2.field1
HAVING COUNT(t2.field1) < 7
)
;
Related
I want to select a column that is not in the GROUP BY.
My code:
SELECT
dbo.func(field1, field2), field3
FROM
table
WHERE
field4 = 1224
GROUP BY
dbo.func(field1, field2), field3
HAVING
COUNT(id) > 1
And I want to select also the column id like this:
SELECT
id, dbo.func(field1, field2), field3
FROM
table
WHERE
field4 = 1224
GROUP BY
dbo.func(field1, field2), field3
HAVING
COUNT(id) > 1
I suspect that you want to apply a count restriction and then return all matching records from the original table, along with the output of the scalar function. One approach is to use COUNT as analytic function with a partition which corresponds to the columns which appeared in your original GROUP BY clause. The difference here is that we don't actually aggregate the original table.
WITH cte AS (
SELECT id, dbo.func(field1, field2) AS out, field3,
COUNT(id) OVER (PARTITION BY dbo.func(field1, field2), field3) cnt
FROM yourTable
WHERE field4 = 1224
)
SELECT id, out, field3
FROM cte
WHERE cnt > 1;
You could join back to the original table to retrieve the matching row(s) with id:
SELECT t.id
, filter.funresult
, t.field3
FROM table t
JOIN (
SELECT dbo.func(field1,field2) as funresult
, field3
FROM table
WHERE field4 = 1224
GROUP BY
dbo.func(field1,field2)
, field3
HAVING COUNT(id) > 1
) filter
ON filter.funresult = dbo.func(t.field1, t.field2)
AND filter.field3 = t.field3
My query return the volume of each field where data is not null.
SELECT COUNT(field1) AS field1, COUNT(field2) AS field2, COUNT(field3) AS field3
FROM (
SELECT field1, field2, field3
FROM table1, table2
WHERE table1.id=table2.idt1
ORDER BY table1.id ASC
LIMIT 10000
) AS rq
table1.id is The primary key of table1 and table2.idt1 is the secondary key of table2.
This query is working perfectly well, but if I need to return the DISTINCT volume of each field, like this
SELECT COUNT(DISTINCT(field1)) AS field1, COUNT(DISTINCT(field2)) AS field2, COUNT(DISTINCT(field3)) AS field3
FROM (
SELECT field1, field2, field3
FROM table1, table2
WHERE table1.id=table2.idt1
ORDER BY table1.id ASC
LIMIT 10000
) AS rq
Problems begins... The query is working on and do the job, but the performances are of course very much slower than without the DISTINCT clause.
Each field of table1 and table2 are indexes with btree
CREATE INDEX field1_index ON table1 USING btree (field1)
CREATE INDEX field2_index ON table1 USING btree (field2)
CREATE INDEX field3_index ON table2 USING btree (field3)
How can I speed up this DISTINCT count ? Maybe with better indexes ?
Thanks for help
I've tried something similar in a big table. (12 Millions rows)
Without the DISTINCT it takes 10 seconds.
With the DISTINCT like your code it take 19 seconds.
Puting the DISTINCT inside the subquery takes 11 seconds
SELECT COUNT(field1) AS field1, COUNT(field2) AS field2, COUNT(field3) AS field3
FROM (
SELECT DISTINCT(field1) AS field1, DISTINCT(field2) AS field2, DISTINCT(field3) AS field3
FROM table1, table2
WHERE table1.id=table2.idt1
ORDER BY table1.id ASC
LIMIT 10000
) AS rq
Other thing, if you only want to filter NULL data, you can make that in the where clause instead of using distinct.
Postgres does not optimize COUNT(DISTINCT) very well. You have multiple such expressions, which makes it a bit harder. I am going to suggest using window functions and conditional aggregation:
SELECT SUM(CASE WHEN seqnum_1 = 1 THEN 1 ELSE 0 END) as field1,
SUM(CASE WHEN seqnum_2 = 1 THEN 1 ELSE 0 END) as field2,
SUM(CASE WHEN seqnum_3 = 1 THEN 1 ELSE 0 END) as field3
FROM (SELECT field1, field2, field3,
ROW_NUMBER() OVER (PARTITION BY field1 ORDER BY field1) as seqnum_1,
ROW_NUMBER() OVER (PARTITION BY field2 ORDER BY field2) as seqnum_2,
ROW_NUMBER() OVER (PARTITION BY field3 ORDER BY field3) as seqnum_3
FROM table1 JOIN
table2
ON table1.id=table2.idt1
ORDER BY table1.id ASC
LIMIT 10000
) rq
EDIT:
It occurs to me that the row_number() might be processed before the limit. Try this version:
SELECT SUM(CASE WHEN seqnum_1 = 1 THEN 1 ELSE 0 END) as field1,
SUM(CASE WHEN seqnum_2 = 1 THEN 1 ELSE 0 END) as field2,
SUM(CASE WHEN seqnum_3 = 1 THEN 1 ELSE 0 END) as field3
FROM (SELECT field1, field2, field3,
ROW_NUMBER() OVER (PARTITION BY field1 ORDER BY field1) as seqnum_1,
ROW_NUMBER() OVER (PARTITION BY field2 ORDER BY field2) as seqnum_2,
ROW_NUMBER() OVER (PARTITION BY field3 ORDER BY field3) as seqnum_3
FROM (SELECT field1, field2, field3
FROM table1 JOIN
table2
ON table1.id = table2.idt1
ORDER BY table1.id ASC
LIMIT 10000
) t
) rq
I have a PostgreSQL database, with only SELECT permissions. In this DB there are two tables with the same structure (the same columns).
I need to write several query in each table and join the results.
There is a way for writing a query like this one?
SELECT
field1,
field2,
field3
FROM
table1
AND
table2
WHERE
condition;
Select from 2 tables. Query = table1 OR table1 + table2 have no answer and it is not my question.
UNION ALL
SELECT field1, field2, field3
FROM table1
WHERE condition
UNION ALL
SELECT field1, field2, field3
FROM table2
WHERE condition;
Or to simplify your WHERE condition
SELECT * FROM
( SELECT field1, field2, field3
FROM table1
UNION ALL
SELECT field1, field2, field3
FROM table2
)
WHERE condition;
You can use Union:
SELECT
field1,
field2,
field3
FROM
table1
UNION
SELECT
field1,
field2,
field3
FROM
table2
SELECT * FROM
( SELECT field1, field2, field3
FROM table1
UNION ALL
SELECT field1, field2, field3
FROM table2
)
WHERE condition;
I have a SQL Server table with the following fields
Field1(REAL), Field2(REAL), ...Fieldn(REAL), DateNTime(TimeStamp)
in a table table1.
How can I get following resultset? i.e. max and min values of each field with corresponding timestamps
Max(Field1), Corresponding TimeStamp, Min(Field1), Corresponding TimeStamp, .....
similarily for other fields.
Thanks All,
By using windowed functions:
with cte as
(select t.*
max(Field1) over () MaxField1,
min(Field1) over () MinField1, ...
from Table1 t)
select max(MaxField1) MaxField1,
max(case Field1 when MaxField1 then DateNTime end) MxF1DateTime,
min(MinField1) MinField1,
min(case Field1 when MinField1 then DateNTime end) MnF1DateTime,
...
from cte
The simplest solution would be something like this:
select
Field1_min, (select max(TimeStamp) from table1 where Field1 = Field1_min) as ts1min,
Field1_max, (select max(TimeStamp) from table1 where Field1 = Field1_max) as ts1max,
Field2_min, (select max(TimeStamp) from table1 where Field2 = Field2_min) as ts2min,
Field2_max, (select max(TimeStamp) from table1 where Field2 = Field2_max) as ts2max,
Field3_min, (select max(TimeStamp) from table1 where Field3 = Field3_min) as ts3min,
Field3_max, (select max(TimeStamp) from table1 where Field3 = Field3_max) as ts3max,
Field4_min, (select max(TimeStamp) from table1 where Field4 = Field4_min) as ts4min,
Field4_max, (select max(TimeStamp) from table1 where Field4 = Field4_max) as ts4max
from (
select
min(Field1) as Field1_min, max(Field1) as Field1_max,
min(Field2) as Field2_min, max(Field2) as Field2_max,
min(Field3) as Field3_min, max(Field3) as Field3_max,
min(Field4) as Field4_min, max(Field4) as Field4_max
from table1
) S
I have a very simple query (on Oracle 11g) to select 3 fields:
select field1, field2, field3, count(*) from table
where...
group by field1, field2, field3
having count(*) > 10;
Now, what I need, is exclude "field3" from the "group by" since I only need field 1 and 2 to be grouped, but I also need field3 in the output.
As far I know, all the fields in the select must be reported also in "group by", so how can I handle that?
Thanks
Lucas
select t.field1, t.field2, t.field3, tc.Count
from table t
inner join (
select field1, field2, count(*) as Count
from table
where...
group by field1, field2
having count(*) > 10
) tc on t.field1 = tc.field1 and t.field2 = tc.field2
Use the analytical version of the "count" function:
select * from (
select field1, field2, field3, count(*) over(partition by field1, field2) mycounter
from table )
--simulate the having clause
where mycounter > 10;
If you don't group by field3 anymore, there can suddenly be different field3 per group. You must decide which one to show, e.g. the maximum:
select field1, field2, max(field3), count(*) from table
where...
group by field1, field2
having count(*) > 10;
The only way I know how to handle that is to first isolate the Field1 and Field2 data and create a new table, then link it back to the original table adding in Field3.
Select Table2.Field1, Table2.Field2, Table1.Field3
From
(Select Field1, max(Field2) as Field2
From Table1) Table2
Where Table2.Field1 = Table1.Field1
And Table2.Field2 = Table1.Field2
Group By
Table2.Field1, Table2.Field2, Table1.Field3