How do I create a COUNT column to count the repetitive values?
And I want to keep the table EXACTLY as below but add the last column (count_id).
The values at the left come from a JOIN so they are "equal".
Thanks! (I tried a lot)
You just want count(*) as a window function:
select t.*,
count(*) over (partition by id, name, department) as count_id
from t;
fairly new to PostgreSQL and trying out a few count queries. I'm looking to count and count distinct all values in a table. Pretty straightforward -
CountD Count
351 400
With a query like this:
SELECT COUNT(*)
COUNT(id) AS count_id,
COUNT DISTINCT(id) AS count_d_id
FROM table
I see that I can create a single column this way:
SELECT COUNT(*) FROM (SELECT DISTINCT id FROM table) AS count_d_id
But the title (count_d_id) doesn't come through properly and unsure how can I add an additional column. Guidance appreciated
This is the correct syntax:
SELECT COUNT(id) AS count_id,
COUNT(DISTINCT id) AS count_d_id
FROM table
Your original query aliases the subquery rather than the column. You seem to want:
SELECT COUNT(*) AS count_d_id FROM (SELECT DISTINCT id FROM table) t
-- column alias --^ -- subquery alias --^
I have a table like as shown below
What I would like to do is get the minimum of each subject. Though I am able to do this with row_number function, I would like to do this with groupby and min() approach. But it doesn't work.
row_number approach - works fine
SELECT * FROM (select subject_id,value,id,min_time,max_time,time_1,
row_number() OVER (PARTITION BY subject_id ORDER BY value) AS rank
from table A) WHERE RANK = 1
min() approach - doesn't work
select subject_id,id,min_time,max_time,time_1,min(value) from table A
GROUP BY SUBJECT_ID,id
As you can see just the two columns (subject_id and id) is enough to group the items together. They will help differentiate the group. But why am I not able to use the other columns in select clause. If I use the other columns, I may not get the expected output because time_1 has different values.
I expect my output to be like as shown below
In BigQuery you can use aggregation for this:
SELECT ARRAY_AGG(a ORDER BY value LIMIT 1)[SAFE_OFFSET(1)].*
FROM table A
GROUP BY SUBJECT_ID;
This uses ARRAY_AGG() to aggregate each record (the a in the argument list). ARRAY_AGG() allows you to order the result (by value) and to limit the size of the array. The latter is important for performance.
After you concatenate the arrays, you want the first element. The .* transforms the record referred to by a to the component columns.
I'm not sure why you don't want to use ROW_NUMBER(). If the problem is the lingering rank column, you an easily remove it:
SELECT a.* EXCEPT (rank)
FROM (SELECT a.*,
ROW_NUMBER() OVER (PARTITION BY subject_id ORDER BY value) AS rank
FROM A
) a
WHERE RANK = 1;
Are you looking for something like below-
SELECT
A.subject_id,
A.id,
A.min_time,
A.max_time,
A.time_1,
A.value
FROM table A
INNER JOIN(
SELECT subject_id, MIN(value) Value
FROM table
GROUP BY subject_id
) B ON A.subject_id = B.subject_id
AND A.Value = B.Value
If you do not required to select Time_1 column's value, this following query will work (As I can see values in column min_time and max_time is same for the same group)-
SELECT
A.subject_id,A.id,A.min_time,A.max_time,
--A.time_1,
MIN(A.value)
FROM table A
GROUP BY
A.subject_id,A.id,A.min_time,A.max_time
Finally, the best approach is if you can apply something like CAST(Time_1 AS DATE) on your time column. This will consider only the date part regardless of the time part. The query will be
SELECT
A.subject_id,A.id,A.min_time,A.max_time,
CAST(A.time_1 AS DATE) Time_1,
MIN(A.value)
FROM table A
GROUP BY
A.subject_id,A.id,A.min_time,A.max_time,
CAST(A.time_1 AS DATE)
-- Make sure the syntax of CAST AS DATE
-- in BigQuery is as I written here or bit different.
Below is for BigQuery Standard SQL and is most efficient way for such cases like in your question
#standardSQL
SELECT AS VALUE ARRAY_AGG(t ORDER BY value LIMIT 1)[OFFSET(0)]
FROM `project.dataset.table` t
GROUP BY subject_id
Using ROW_NUMBER is not efficient and in many cases lead to Resources exceeded error.
Note: self join is also very ineffective way of achieving your objective
A bit late to the party, but here is a cte-based approach which made sense to me:
with mins as (
select subject_id, id, min(value) as min_value
from table
group by subject_id, id
)
select distinct t.subject_id, t.id, t.time_1, t.min_time, t.max_time, m.min_value
from table t
join mins m on m.subject_id = t.subject_id and m.id = t.id
I have a postgresql table wherein I have few fields such as id and date. I need to find the max date for that id and show the same into a new field for all the ids. SQLFiddle site was not responding so I have an example in the excel. Here is the screenshot of the data and the output for the table.
You could use the windowing variant of max:
SELECT id, date, MAX(date) OVER (PARTITION BY id)
FROM mytable
Something like this might work:
WITH maxdts AS (
SELECT id, max(dt) maxdt FROM table GROUP BY id
)
SELECT id, date, maxdt FROM table t, maxdts m WHERE t.id = m.id;
Keep in mind without more information that this could be a horribly inefficient query, but it will get you what you need.
If i perform a standard query in SQLite:
SELECT * FROM my_table
I get all records in my table as expected. If i perform following query:
SELECT *, 1 FROM my_table
I get all records as expected with rightmost column holding '1' in all records. But if i perform the query:
SELECT *, COUNT(*) FROM my_table
I get only ONE row (with rightmost column is a correct count).
Why is such results? I'm not very good in SQL, maybe such behavior is expected? It seems very strange and unlogical to me :(.
SELECT *, COUNT(*) FROM my_table is not what you want, and it's not really valid SQL, you have to group by all the columns that's not an aggregate.
You'd want something like
SELECT somecolumn,someothercolumn, COUNT(*)
FROM my_table
GROUP BY somecolumn,someothercolumn
If you want to count the number of records in your table, simply run:
SELECT COUNT(*) FROM your_table;
count(*) is an aggregate function. Aggregate functions need to be grouped for a meaningful results. You can read: count columns group by
If what you want is the total number of records in the table appended to each row you can do something like
SELECT *
FROM my_table
CROSS JOIN (SELECT COUNT(*) AS COUNT_OF_RECS_IN_MY_TABLE
FROM MY_TABLE)