I have a table which has some columns that I want to sum up per row. It looks like
ID VALUE1 VALUE2 VALUE3 ... VALUE34
============================
1 1 2 2
1 2 2 5
2 3 4 6
2 4 5 7
I know that to sum two columns I can do
SELECT ID, SUM(VALUE1 + VALUE2)
FROM tableName
GROUP BY ID
Is there any syntactic sugar or something that can help me sum all the 34 values without having to do SUM(VALUE1 + VALUE2 + VALUE3 + ...) ?
If you cannot go with a better data model, what about making use of arrays? This also will allow you to change the number of elements in your table without having to alter it:
create table tableName (
id integer,
valuez integer[]
)
The equivalent of your query would be:
select id, valuez[1] + valuez[2] + ... + valuez[34]
from tableName
But with an array you can unnest and sum:
with sums as (
select id, unnest (valuez) as val
from tableName
)
select id, sum (val)
from sums
group by id
This also simplifies null handling -- simply add where val is not null and you can avoid mass coalescing.
Related
I have a table of IDs and value:
ID Value
X 1
X 1
X 2
Y 5
Y 5
Y 5
Z 3
Z 6
I want to see which ID contains more than 1 different value. In this case return ID X and Y because X contains[1,2] and Z contains [3,6]:
ID
X
Z
I have tried this:
select ID from
(
SELECT ID
,count(*) over (partition by [Value]) as c
FROM mytable
) a
where c>1
But this is not returning the desired answer
I prefer aggregating this way:
SELECT ID
FROM mytable
GROUP BY ID
HAVING MIN(Value) <> MAX(Value);
On many databases, the above HAVING clause will be sargable, meaning that an index on (ID, Value) can be used. The version which checks COUNT(DISTINCT Value) may not be able to use such an index.
Try this,
SELECT ID
FROM mytable
GROUP BY ID
HAVING COUNT(DISTINCT Value) > 1;
Just group them by ID and check wheter it got more than 1 occurrencies in Value field. Something like this
SELECT ID
FROM table
GROUP BY ID
HAVING COUNT(DISTINCT Value) > 1
CREATE TABLE yourtable(
ID VARCHAR(30) NOT NULL
,Value int NOT NULL
);
INSERT INTO yourtable
(ID,Value) VALUES
('X',1),
('X',1),
('X',2),
('Y',5),
('Y',5),
('Y',5),
('Z',3),
('Z',6);
Other approaches are far better,but I used Rank and Subquery to distinguish ID with more than one occurrence.
SELECT ID
FROM (SELECT *,
Rank()
OVER(
partition BY ID
ORDER BY Value) ID2
FROM yourtable) a
WHERE ID2 > 1
dbfiddle
I have the following table tbl:
column1 | column2 | column 3
-----------------------------------
1 | 'value1' | 3
2 | 'value2' | 4
How to do "pivot" with column names to produce output like:
column1 | 1 | 2
column2 | 'value1' |'value2'
column3 | 3 | 4
As has been commented, the issue of data types is undefined in the question.
If you are OK with all result columns being type text (every data type can be converted to text), you can use one of these:
Plain SQL
WITH cte AS (
SELECT nu.*
FROM tbl t
, LATERAL (
VALUES
(1, t.column1::text)
, (2, t.column2)
, (3, t.column3::text)
) nu(rn, c)
)
SELECT *
FROM (TABLE cte OFFSET 0 LIMIT 3) c1
JOIN (TABLE cte OFFSET 3 LIMIT 3) c2 USING (rn);
The same with useful column names:
WITH cte AS (
SELECT nu.*
FROM tbl t
, LATERAL (
VALUES
('column1', t.column1::text)
, ('column2', t.column2)
, ('column3', t.column3::text)
) nu(rn, c)
)
SELECT * FROM (
SELECT *
FROM (TABLE cte OFFSET 0 LIMIT 3) c1
JOIN (TABLE cte OFFSET 3 LIMIT 3) c2 USING (rn)
) t (key, row1, row2);
Works in any modern version of Postgres.
The SQL string has to be adapted to the number of rows and columns. See fiddles below!
Using a document type as stepping stone
Makes for shorter code.
With many rows and many columns, performance of the SQL solution may scale better because the intermediate derived table is smaller.
(The thread is limited as you can't have more than ~ 1600 table columns in Postgres.)
Since everything is converted to text anyway, hstore seems most efficient. See:
Key value pair in PostgreSQL
SELECT key
, arr[1] AS row1
, arr[2] AS row2
FROM (
SELECT x.key, array_agg(x.value) AS arr
FROM tbl t, each(hstore(t)) x
GROUP BY 1
) sub
ORDER BY 1;
Technically speaking we would have to enforce the right sort order when in array_agg(), but that should work without explicit ORDER BY. To be absolutely sure you can add one: array_agg(x.value ORDER BY t.ctid) Using ctid for lack of information.
You can do the same with JSON functions in (Postgres 9.3+). Just replace each(hstore(t) with json_each_text(row_to_json(t). The rest is identical.
These fiddles demonstrate how to scale each query:
Original example with 2 rows of 3 columns:
db<>fiddle here
Scaled up to 3 rows of 4 columns:
db<>fiddle here
(I want to perform a group-by based on the distinct values in a string column that has multiple values
The said column has a list of strings in a standard format separated by commas. The potential values are only a,b,c,d.
For example the column collection (type: String) contains:
Row 1: ["a","b"]
Row 2: ["b","c"]
Row 3: ["b","c","a"]
Row 4: ["d"]`
The expected output is a count of unique values:
collection | count
a | 2
b | 3
c | 2
d | 1
For all the below i used this table:
create table tmp (
id INT auto_increment,
test VARCHAR(255),
PRIMARY KEY (id)
);
insert into tmp (test) values
("a,b"),
("b,c"),
("b,c,a"),
("d")
;
If the possible values are only a,b,c,d you can try one of this:
Tke note that this will only works if you have not so similar values like test and test_new, because then the test would be joined also with all test_new rows and the count would not match
select collection, COUNT(*) as count from tmp JOIN (
select CONCAT("%", tb.collection, "%") as like_collection, collection from (
select "a" COLLATE utf8_general_ci as collection
union select "b" COLLATE utf8_general_ci as collection
union select "c" COLLATE utf8_general_ci as collection
union select "d" COLLATE utf8_general_ci as collection
) tb
) tb1
ON tmp.test LIKE tb1.like_collection
GROUP BY tb1.collection;
Which will give you the result you want
collection | count
a | 2
b | 3
c | 2
d | 1
or you can try this one
SELECT
(SELECT COUNT(*) FROM tmp WHERE test LIKE '%a%') as a_count,
(SELECT COUNT(*) FROM tmp WHERE test LIKE '%b%') as b_count,
(SELECT COUNT(*) FROM tmp WHERE test LIKE '%c%') as c_count,
(SELECT COUNT(*) FROM tmp WHERE test LIKE '%d%') as d_count
;
The result would be like this
a_count | b_count | c_count | d_count
2 | 3 | 2 | 1
What you need to do is to first explode the collection column into separate rows (like a flatMap operation). In redshift the only way to generate new rows is to JOIN - so let's CROSS JOIN your input table with a static table having consecutive numbers, and take only ones having id less or equal to number of elements in the collection. Then we'll use split_part function to read the item at correct index. Once we have the exploaded table, we'll do a simple GROUP BY.
If your items are stored as JSON array strings ('["a", "b", "c"]') then you can use JSON_ARRAY_LENGTH and JSON_EXTRACT_ARRAY_ELEMENT_TEXT instead of REGEXP_COUNT and SPLIT_PART respectively.
with
index as (
select 1 as i
union all select 2
union all select 3
union all select 4 -- could be substituted with 'select row_number() over () as i from arbitrary_table limit 4'
),
agg as (
select 'a,b' as collection
union all select 'b,c'
union all select 'b,c,a'
union all select 'd'
)
select
split_part(collection, ',', i) as item,
count(*)
from index,agg
where regexp_count(agg.collection, ',') + 1 >= index.i -- only get rows where number of items matches
group by 1
I have the following table:
No Item Value
----------------------------
1 A 5
2 B 8
3 C 9
If I use Min function on Value field, then I'll get 5.
My question is, how can I put the MIN value into a new column? Like the following result:
No Item Value newCol
----------------------------
1 A 5 5
2 B 8 5
3 C 9 5
Is it possible to do that?
Thank you.
Something like:
select No, Item, Value, (select min(value) from table)
from table
should do it.
I'd prefer to do the subquery in a join, you'll have to name the field. Something like this;
Sample Data
CREATE TABLE #TestData (No int, item nvarchar(1), value int)
INSERT INTO #TestData (No, item, value)
VALUES
(1,'A',5)
,(2,'B',8)
,(3,'C',9)
Query
SELECT
td.No
,td.item
,td.value
,a.Min_Value
FROM #TestData td
CROSS JOIN
(
SELECT
MIN(Value) Min_Value
FROM #TestData
) a
Result
No item value Min_Value
1 A 5 5
2 B 8 5
3 C 9 5
You could do that even simpler by using an appropriate OVER() clause.
SELECT *
, MIN(Value) OVER () AS [newCol]
FROM Table
This would be simpler and less resource consuming than a (SELECT MIN(Value) FROM TABLE) in the top level SELECT.
Sample code:
DECLARE #tbl TABLE (No int, Item char(1), Value int)
INSERT #tbl VALUES (1, 'A', 5), (2, 'B', 8), (3, 'C', 9)
SELECT *
, MIN(Value) OVER () AS [newCol]
FROM #tbl
Using cross join with min value from table :
SELECT * FROM #Tbl1 CROSS JOIN (SELECT MIN(Value1) Value1 FROM #Tbl1) A
Consider the following table #document_fields
id x y z
------------------
1 foo bar baz
2 one two three
3 aaa bbb ccc
4 123 456 789
The number of columns may vary, as do the column names. I need to pivot the columns into rows like this:
id field value
---------------
1 x foo
1 y bar
1 z baz
2 x one
2 y two
2 z three
.
.
3 z 789
I'm trying to understand the way pivoting in SQL Server works but can't get any further than this:
select
*
into
#document_fields_pivot
from (
select * from (
select *
from #document_fields
) t
pivot (
-- ??
) p
) tbl
Can anyone help me to finish this query / explain me pivoting? Any help is greatly appreciated.
What you want is called UNPIVOT and done like so:
select id,field,value from
#document_fields
unpivot
(
value
for field in (x,y,z)
) as u
order by id,field
Demo
DECLARE #Component table (ComponentId INT,Descr VARCHAR(10),Descr1 VARCHAR(10),Descr2 VARCHAR(10))
INSERT INTO #Component (ComponentId,Descr,Descr1,Descr2)values (1,'foo','bar','baz')
INSERT INTO #Component (ComponentId,Descr,Descr1,Descr2)values (2,'one','two','three')
INSERT INTO #Component (ComponentId,Descr,Descr1,Descr2)values (3,'aaa','bbb','ccc')
INSERT INTO #Component (ComponentId,Descr,Descr1,Descr2)values (3,'123','456','789')
select
ComponentId,Field
from #Component P
UNPIVOT
(
Field
FOR Value
IN (
[Descr],[Descr1],[Descr2]
)
) PivotTable;