How to add a row with null data in final query?
I have got a table with data:
table1
country date price
USA 2001-01-25 2
RUS 2001-01-25 17
GER 2001-01-25 30
USA 2001-02-25 11
RUS 2001-02-25 22
RUS 2001-02-26 25
I can get all countries with
SELECT DISTINCT country FROM table1;
country
USA
RUS
GER
And get all prices for the month
SELECT sum(price), country FROM table1 WHERE date >= '2001-02-01' AND date < '2001-03-01' GROUP BY country, price;
sum(price) country
11 USA
47 RUS
But I also want to see one row for country 'GER'
sum(price) country
11 USA
47 RUS
0 GER
How to do it easy in clickhouse?
clickhouse
add a comment |
I have got a table with data:
table1
country date price
USA 2001-01-25 2
RUS 2001-01-25 17
GER 2001-01-25 30
USA 2001-02-25 11
RUS 2001-02-25 22
RUS 2001-02-26 25
I can get all countries with
SELECT DISTINCT country FROM table1;
country
USA
RUS
GER
And get all prices for the month
SELECT sum(price), country FROM table1 WHERE date >= '2001-02-01' AND date < '2001-03-01' GROUP BY country, price;
sum(price) country
11 USA
47 RUS
But I also want to see one row for country 'GER'
sum(price) country
11 USA
47 RUS
0 GER
How to do it easy in clickhouse?
clickhouse
add a comment |
I have got a table with data:
table1
country date price
USA 2001-01-25 2
RUS 2001-01-25 17
GER 2001-01-25 30
USA 2001-02-25 11
RUS 2001-02-25 22
RUS 2001-02-26 25
I can get all countries with
SELECT DISTINCT country FROM table1;
country
USA
RUS
GER
And get all prices for the month
SELECT sum(price), country FROM table1 WHERE date >= '2001-02-01' AND date < '2001-03-01' GROUP BY country, price;
sum(price) country
11 USA
47 RUS
But I also want to see one row for country 'GER'
sum(price) country
11 USA
47 RUS
0 GER
How to do it easy in clickhouse?
clickhouse
I have got a table with data:
table1
country date price
USA 2001-01-25 2
RUS 2001-01-25 17
GER 2001-01-25 30
USA 2001-02-25 11
RUS 2001-02-25 22
RUS 2001-02-26 25
I can get all countries with
SELECT DISTINCT country FROM table1;
country
USA
RUS
GER
And get all prices for the month
SELECT sum(price), country FROM table1 WHERE date >= '2001-02-01' AND date < '2001-03-01' GROUP BY country, price;
sum(price) country
11 USA
47 RUS
But I also want to see one row for country 'GER'
sum(price) country
11 USA
47 RUS
0 GER
How to do it easy in clickhouse?
clickhouse
clickhouse
asked Nov 14 '18 at 10:39
JensJens
1069
1069
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
Use conditional aggregation:
SELECT
country,
SUM(CASE WHEN date >= '2001-02-01' AND date < '2001-03-01'
THEN price ELSE 0 END) AS prices
FROM table1
GROUP BY country;
The problem with your current WHERE clause is that it will filter off countries which have no matching price at all during the month of February, 2001.
If the above solution be not performant, we can writing this as a join of a table containing all countries to table1:
SELECT c.country, COALESCE(t.prices, 0) AS prices
FROM (SELECT DISTINCT country FROM table1) c
LEFT JOIN
(
SELECT country, SUM(prices) AS prices
FROM table1
WHERE date >= '2001-02-01' AND date < '2001-03-01'
GROUP BY country
) t
ON c.country = t.country;
It doesn't return row with 0
– Jens
Nov 14 '18 at 12:30
@Jens I don't know much about Clickhouse SQL, but my answer is definitely working with your sample data on SQL Server. See the demo here.
– Tim Biegeleisen
Nov 14 '18 at 13:27
It works with NULL instead of 0. Thank you!
– Jens
Nov 14 '18 at 14:27
This has the potential to be quite expensive withing large datasets when partitioning by date.
– ecyshor
Nov 14 '18 at 18:12
@ecyshor I updated my answer with a join option which might run faster. But it is not clear whether the OP actually has a dedicated table of country names.
– Tim Biegeleisen
Nov 14 '18 at 23:56
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
Use conditional aggregation:
SELECT
country,
SUM(CASE WHEN date >= '2001-02-01' AND date < '2001-03-01'
THEN price ELSE 0 END) AS prices
FROM table1
GROUP BY country;
The problem with your current WHERE clause is that it will filter off countries which have no matching price at all during the month of February, 2001.
If the above solution be not performant, we can writing this as a join of a table containing all countries to table1:
SELECT c.country, COALESCE(t.prices, 0) AS prices
FROM (SELECT DISTINCT country FROM table1) c
LEFT JOIN
(
SELECT country, SUM(prices) AS prices
FROM table1
WHERE date >= '2001-02-01' AND date < '2001-03-01'
GROUP BY country
) t
ON c.country = t.country;
It doesn't return row with 0
– Jens
Nov 14 '18 at 12:30
@Jens I don't know much about Clickhouse SQL, but my answer is definitely working with your sample data on SQL Server. See the demo here.
– Tim Biegeleisen
Nov 14 '18 at 13:27
It works with NULL instead of 0. Thank you!
– Jens
Nov 14 '18 at 14:27
This has the potential to be quite expensive withing large datasets when partitioning by date.
– ecyshor
Nov 14 '18 at 18:12
@ecyshor I updated my answer with a join option which might run faster. But it is not clear whether the OP actually has a dedicated table of country names.
– Tim Biegeleisen
Nov 14 '18 at 23:56
add a comment |
Use conditional aggregation:
SELECT
country,
SUM(CASE WHEN date >= '2001-02-01' AND date < '2001-03-01'
THEN price ELSE 0 END) AS prices
FROM table1
GROUP BY country;
The problem with your current WHERE clause is that it will filter off countries which have no matching price at all during the month of February, 2001.
If the above solution be not performant, we can writing this as a join of a table containing all countries to table1:
SELECT c.country, COALESCE(t.prices, 0) AS prices
FROM (SELECT DISTINCT country FROM table1) c
LEFT JOIN
(
SELECT country, SUM(prices) AS prices
FROM table1
WHERE date >= '2001-02-01' AND date < '2001-03-01'
GROUP BY country
) t
ON c.country = t.country;
It doesn't return row with 0
– Jens
Nov 14 '18 at 12:30
@Jens I don't know much about Clickhouse SQL, but my answer is definitely working with your sample data on SQL Server. See the demo here.
– Tim Biegeleisen
Nov 14 '18 at 13:27
It works with NULL instead of 0. Thank you!
– Jens
Nov 14 '18 at 14:27
This has the potential to be quite expensive withing large datasets when partitioning by date.
– ecyshor
Nov 14 '18 at 18:12
@ecyshor I updated my answer with a join option which might run faster. But it is not clear whether the OP actually has a dedicated table of country names.
– Tim Biegeleisen
Nov 14 '18 at 23:56
add a comment |
Use conditional aggregation:
SELECT
country,
SUM(CASE WHEN date >= '2001-02-01' AND date < '2001-03-01'
THEN price ELSE 0 END) AS prices
FROM table1
GROUP BY country;
The problem with your current WHERE clause is that it will filter off countries which have no matching price at all during the month of February, 2001.
If the above solution be not performant, we can writing this as a join of a table containing all countries to table1:
SELECT c.country, COALESCE(t.prices, 0) AS prices
FROM (SELECT DISTINCT country FROM table1) c
LEFT JOIN
(
SELECT country, SUM(prices) AS prices
FROM table1
WHERE date >= '2001-02-01' AND date < '2001-03-01'
GROUP BY country
) t
ON c.country = t.country;
Use conditional aggregation:
SELECT
country,
SUM(CASE WHEN date >= '2001-02-01' AND date < '2001-03-01'
THEN price ELSE 0 END) AS prices
FROM table1
GROUP BY country;
The problem with your current WHERE clause is that it will filter off countries which have no matching price at all during the month of February, 2001.
If the above solution be not performant, we can writing this as a join of a table containing all countries to table1:
SELECT c.country, COALESCE(t.prices, 0) AS prices
FROM (SELECT DISTINCT country FROM table1) c
LEFT JOIN
(
SELECT country, SUM(prices) AS prices
FROM table1
WHERE date >= '2001-02-01' AND date < '2001-03-01'
GROUP BY country
) t
ON c.country = t.country;
edited Nov 15 '18 at 0:02
answered Nov 14 '18 at 10:42
Tim BiegeleisenTim Biegeleisen
223k1391143
223k1391143
It doesn't return row with 0
– Jens
Nov 14 '18 at 12:30
@Jens I don't know much about Clickhouse SQL, but my answer is definitely working with your sample data on SQL Server. See the demo here.
– Tim Biegeleisen
Nov 14 '18 at 13:27
It works with NULL instead of 0. Thank you!
– Jens
Nov 14 '18 at 14:27
This has the potential to be quite expensive withing large datasets when partitioning by date.
– ecyshor
Nov 14 '18 at 18:12
@ecyshor I updated my answer with a join option which might run faster. But it is not clear whether the OP actually has a dedicated table of country names.
– Tim Biegeleisen
Nov 14 '18 at 23:56
add a comment |
It doesn't return row with 0
– Jens
Nov 14 '18 at 12:30
@Jens I don't know much about Clickhouse SQL, but my answer is definitely working with your sample data on SQL Server. See the demo here.
– Tim Biegeleisen
Nov 14 '18 at 13:27
It works with NULL instead of 0. Thank you!
– Jens
Nov 14 '18 at 14:27
This has the potential to be quite expensive withing large datasets when partitioning by date.
– ecyshor
Nov 14 '18 at 18:12
@ecyshor I updated my answer with a join option which might run faster. But it is not clear whether the OP actually has a dedicated table of country names.
– Tim Biegeleisen
Nov 14 '18 at 23:56
It doesn't return row with 0
– Jens
Nov 14 '18 at 12:30
It doesn't return row with 0
– Jens
Nov 14 '18 at 12:30
@Jens I don't know much about Clickhouse SQL, but my answer is definitely working with your sample data on SQL Server. See the demo here.
– Tim Biegeleisen
Nov 14 '18 at 13:27
@Jens I don't know much about Clickhouse SQL, but my answer is definitely working with your sample data on SQL Server. See the demo here.
– Tim Biegeleisen
Nov 14 '18 at 13:27
It works with NULL instead of 0. Thank you!
– Jens
Nov 14 '18 at 14:27
It works with NULL instead of 0. Thank you!
– Jens
Nov 14 '18 at 14:27
This has the potential to be quite expensive withing large datasets when partitioning by date.
– ecyshor
Nov 14 '18 at 18:12
This has the potential to be quite expensive withing large datasets when partitioning by date.
– ecyshor
Nov 14 '18 at 18:12
@ecyshor I updated my answer with a join option which might run faster. But it is not clear whether the OP actually has a dedicated table of country names.
– Tim Biegeleisen
Nov 14 '18 at 23:56
@ecyshor I updated my answer with a join option which might run faster. But it is not clear whether the OP actually has a dedicated table of country names.
– Tim Biegeleisen
Nov 14 '18 at 23:56
add a comment |
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