The following code that executes without any issue:
Select
#ICDCodes.ICD_Code,
#ICDCodes.Description,
Count(#DiseaseIndex.VstIntID) AS 'Total Count',
Sum(DATEDIFF(dd,#DiseaseIndex.AdmitDtSrt,#DiseaseIndex.DschrgDtTm )) as 'Total LOS',
ISNULL(AVG(CONVERT(NUMERIC(8,2),DATEDIFF(DAY,#DiseaseIndex.AdmitDtSrt,#DiseaseIndex.DschrgDtTm))),0) as 'Total Avg LOS'
FROM #DiseaseIndex LEFT JOIN #ICDCodes on #DiseaseIndex.VstIntID = #ICDCodes.VstIntID
WHERE ICD_Type IN ('P','S')
GROUP BY #ICDCodes.ICD_Code, #ICDCodes.Descriptio
but this code throws an error:
SELECT
#ICDCodes.ICD_Code,
#ICDCodes.Description,
Count(#DiseaseIndex.VstIntID) AS 'Total Count',
Sum(CAST(DATEDIFF(dd,#DiseaseIndex.AdmitDtSrt,#DiseaseIndex.DschrgDtTm )AS NUMERIC(8,2))) AS 'Total LOS',
ISNULL(CAST(DATEDIFF(DAY,#DiseaseIndex.AdmitDtSrt,#DiseaseIndex.DschrgDtTm) AS NUMERIC(8,2)),0) as 'Total Avg LOS'
FROM #DiseaseIndex LEFT JOIN #ICDCodes on #DiseaseIndex.VstIntID = #ICDCodes.VstIntID
WHERE ICD_Type IN ('P','S')
GROUP BY #ICDCodes.ICD_Code, #ICDCodes.Description`
This is the Error it generates:
Msg 8120, Level 16, State 1, Line 191
Column '#DiseaseIndex.AdmitDtSrt' is invalid in the select list because it is not contained in either an aggregate function or the GROUP BY clause.
Msg 8120, Level 16, State 1, Line 191
Column '#DiseaseIndex.DschrgDtTm' is invalid in the select list because it is not contained in either an aggregate function or the GROUP BY clause.
Basically it is the same code with the exception that one set uses CAST() and the other one uses CONVERT().
Can someone explain why the CAST requires adding the dates to the GROUP BY statement while the CONVERT does not?
Thanks in advance
Update
In the second query you've forgot the AVG:
first query:
ISNULL(AVG(CONVERT(NUMERIC(8,2),DATEDIFF(DAY,#DiseaseIndex.AdmitDtSrt,#DiseaseIndex.DschrgDtTm))),0) as 'Total Avg LOS
second query:
ISNULL(CAST(DATEDIFF(DAY,#DiseaseIndex.AdmitDtSrt,#DiseaseIndex.DschrgDtTm) AS NUMERIC(8,2)),0) as 'Total Avg LOS'
First version:
(This was correct for the first version of the question.)
This is because you use NUMERIC(8,2) in the convert, but DECIMAL(8,2) in the cast.
Though numeric and decimal are documented to be interchangeable synonyms, having a numeric in he group by clause and a decimal in the select clause will raise that error.
Here is a simple demo:
DECLARE #T AS TABLE
(
col1 int,
col2 int
)
INSERT INTO #T VALUES
(1,1),(2,1),(3,1),
(4,2),(5,2),(6,2),
(7,3)
SELECT CAST(Col2 as NUMERIC(8,2)),
AVG(Col1)
FROM #T
GROUP BY CONVERT(DECIMAL(8,2), Col2)
Results:
Column '#T.col2' is invalid in the select list because it is not contained in either an aggregate function or the GROUP BY clause.
However, if you change the select to decimal or the group by to numeric, the error message is gone and the select returns the result set:
SELECT CAST(Col2 as DECIMAL(8,2)),
AVG(Col1)
FROM #T
GROUP BY CONVERT(DECIMAL(8,2), Col2)
Results:
1.00 2
2.00 5
3.00 7
See a live demo on rextester
Related
Determine the max value of an attribute that has values like below,
GROUPNAME
A-1000
C-1001
A-1002
Expected Output
1002
I tried the below query, and it is giving the output as 1001 instead of 1002, the max value is based on the alphabet rather than the number,
select max(groupname) from table where type in ('A','C') and customer is null
Output
1001
We can use a limit query here:
SELECT *
FROM yourTable
WHERE type IN ('A', 'C') AND customer IS NULL
ORDER BY CAST(SUBSTR(groupname, INSTR(groupname, '-') + 1) AS INT) DESC
LIMIT 1;
The strategy above is to isolate the number which comes after the dash, cast it to an integer, then use that for sorting.
Does any one know how to create crosstab queries in PostgreSQL?
For example I have the following table:
Section Status Count
A Active 1
A Inactive 2
B Active 4
B Inactive 5
I would like the query to return the following crosstab:
Section Active Inactive
A 1 2
B 4 5
Is this possible?
Install the additional module tablefunc once per database, which provides the function crosstab(). Since Postgres 9.1 you can use CREATE EXTENSION for that:
CREATE EXTENSION IF NOT EXISTS tablefunc;
Improved test case
CREATE TABLE tbl (
section text
, status text
, ct integer -- "count" is a reserved word in standard SQL
);
INSERT INTO tbl VALUES
('A', 'Active', 1), ('A', 'Inactive', 2)
, ('B', 'Active', 4), ('B', 'Inactive', 5)
, ('C', 'Inactive', 7); -- ('C', 'Active') is missing
Simple form - not fit for missing attributes
crosstab(text) with 1 input parameter:
SELECT *
FROM crosstab(
'SELECT section, status, ct
FROM tbl
ORDER BY 1,2' -- needs to be "ORDER BY 1,2" here
) AS ct ("Section" text, "Active" int, "Inactive" int);
Returns:
Section | Active | Inactive
---------+--------+----------
A | 1 | 2
B | 4 | 5
C | 7 | -- !!
No need for casting and renaming.
Note the incorrect result for C: the value 7 is filled in for the first column. Sometimes, this behavior is desirable, but not for this use case.
The simple form is also limited to exactly three columns in the provided input query: row_name, category, value. There is no room for extra columns like in the 2-parameter alternative below.
Safe form
crosstab(text, text) with 2 input parameters:
SELECT *
FROM crosstab(
'SELECT section, status, ct
FROM tbl
ORDER BY 1,2' -- could also just be "ORDER BY 1" here
, $$VALUES ('Active'::text), ('Inactive')$$
) AS ct ("Section" text, "Active" int, "Inactive" int);
Returns:
Section | Active | Inactive
---------+--------+----------
A | 1 | 2
B | 4 | 5
C | | 7 -- !!
Note the correct result for C.
The second parameter can be any query that returns one row per attribute matching the order of the column definition at the end. Often you will want to query distinct attributes from the underlying table like this:
'SELECT DISTINCT attribute FROM tbl ORDER BY 1'
That's in the manual.
Since you have to spell out all columns in a column definition list anyway (except for pre-defined crosstabN() variants), it is typically more efficient to provide a short list in a VALUES expression like demonstrated:
$$VALUES ('Active'::text), ('Inactive')$$)
Or (not in the manual):
$$SELECT unnest('{Active,Inactive}'::text[])$$ -- short syntax for long lists
I used dollar quoting to make quoting easier.
You can even output columns with different data types with crosstab(text, text) - as long as the text representation of the value column is valid input for the target type. This way you might have attributes of different kind and output text, date, numeric etc. for respective attributes. There is a code example at the end of the chapter crosstab(text, text) in the manual.
db<>fiddle here
Effect of excess input rows
Excess input rows are handled differently - duplicate rows for the same ("row_name", "category") combination - (section, status) in the above example.
The 1-parameter form fills in available value columns from left to right. Excess values are discarded.
Earlier input rows win.
The 2-parameter form assigns each input value to its dedicated column, overwriting any previous assignment.
Later input rows win.
Typically, you don't have duplicates to begin with. But if you do, carefully adjust the sort order to your requirements - and document what's happening.
Or get fast arbitrary results if you don't care. Just be aware of the effect.
Advanced examples
Pivot on Multiple Columns using Tablefunc - also demonstrating mentioned "extra columns"
Dynamic alternative to pivot with CASE and GROUP BY
\crosstabview in psql
Postgres 9.6 added this meta-command to its default interactive terminal psql. You can run the query you would use as first crosstab() parameter and feed it to \crosstabview (immediately or in the next step). Like:
db=> SELECT section, status, ct FROM tbl \crosstabview
Similar result as above, but it's a representation feature on the client side exclusively. Input rows are treated slightly differently, hence ORDER BY is not required. Details for \crosstabview in the manual. There are more code examples at the bottom of that page.
Related answer on dba.SE by Daniel Vérité (the author of the psql feature):
How do I generate a pivoted CROSS JOIN where the resulting table definition is unknown?
SELECT section,
SUM(CASE status WHEN 'Active' THEN count ELSE 0 END) AS active, --here you pivot each status value as a separate column explicitly
SUM(CASE status WHEN 'Inactive' THEN count ELSE 0 END) AS inactive --here you pivot each status value as a separate column explicitly
FROM t
GROUP BY section
You can use the crosstab() function of the additional module tablefunc - which you have to install once per database. Since PostgreSQL 9.1 you can use CREATE EXTENSION for that:
CREATE EXTENSION tablefunc;
In your case, I believe it would look something like this:
CREATE TABLE t (Section CHAR(1), Status VARCHAR(10), Count integer);
INSERT INTO t VALUES ('A', 'Active', 1);
INSERT INTO t VALUES ('A', 'Inactive', 2);
INSERT INTO t VALUES ('B', 'Active', 4);
INSERT INTO t VALUES ('B', 'Inactive', 5);
SELECT row_name AS Section,
category_1::integer AS Active,
category_2::integer AS Inactive
FROM crosstab('select section::text, status, count::text from t',2)
AS ct (row_name text, category_1 text, category_2 text);
DB Fiddle here:
Everything works: https://dbfiddle.uk/iKCW9Uhh
Without CREATE EXTENSION tablefunc; you get this error: https://dbfiddle.uk/j8W1CMvI
ERROR: function crosstab(unknown, integer) does not exist
LINE 4: FROM crosstab('select section::text, status, count::text fro...
^
HINT: No function matches the given name and argument types. You might need to add explicit type casts.
Solution with JSON aggregation:
CREATE TEMP TABLE t (
section text
, status text
, ct integer -- don't use "count" as column name.
);
INSERT INTO t VALUES
('A', 'Active', 1), ('A', 'Inactive', 2)
, ('B', 'Active', 4), ('B', 'Inactive', 5)
, ('C', 'Inactive', 7);
SELECT section,
(obj ->> 'Active')::int AS active,
(obj ->> 'Inactive')::int AS inactive
FROM (SELECT section, json_object_agg(status,ct) AS obj
FROM t
GROUP BY section
)X
Sorry this isn't complete because I can't test it here, but it may get you off in the right direction. I'm translating from something I use that makes a similar query:
select mt.section, mt1.count as Active, mt2.count as Inactive
from mytable mt
left join (select section, count from mytable where status='Active')mt1
on mt.section = mt1.section
left join (select section, count from mytable where status='Inactive')mt2
on mt.section = mt2.section
group by mt.section,
mt1.count,
mt2.count
order by mt.section asc;
The code I'm working from is:
select m.typeID, m1.highBid, m2.lowAsk, m1.highBid - m2.lowAsk as diff, 100*(m1.highBid - m2.lowAsk)/m2.lowAsk as diffPercent
from mktTrades m
left join (select typeID,MAX(price) as highBid from mktTrades where bid=1 group by typeID)m1
on m.typeID = m1.typeID
left join (select typeID,MIN(price) as lowAsk from mktTrades where bid=0 group by typeID)m2
on m1.typeID = m2.typeID
group by m.typeID,
m1.highBid,
m2.lowAsk
order by diffPercent desc;
which will return a typeID, the highest price bid and the lowest price asked and the difference between the two (a positive difference would mean something could be bought for less than it can be sold).
There's a different dynamic method that I've devised, one that employs a dynamic rec. type (a temp table, built via an anonymous procedure) & JSON. This may be useful for an end-user who can't install the tablefunc/crosstab extension, but can still create temp tables or run anon. proc's.
The example assumes all the xtab columns are the same type (INTEGER), but the # of columns is data-driven & variadic. That said, JSON aggregate functions do allow for mixed data types, so there's potential for innovation via the use of embedded composite (mixed) types.
The real meat of it can be reduced down to one step if you want to statically define the rec. type inside the JSON recordset function (via nested SELECTs that emit a composite type).
dbfiddle.uk
https://dbfiddle.uk/N1EzugHk
Crosstab function is available under the tablefunc extension. You'll have to create this extension one time for the database.
CREATE EXTENSION tablefunc;
You can use the below code to create pivot table using cross tab:
create table test_Crosstab( section text,
status text,
count numeric)
insert into test_Crosstab values ( 'A','Active',1)
,( 'A','Inactive',2)
,( 'B','Active',4)
,( 'B','Inactive',5)
select * from crosstab(
'select section
,status
,count
from test_crosstab'
)as ctab ("Section" text,"Active" numeric,"Inactive" numeric)
I have a table containing transactions with an amount. I want to create a batch of transactions so that the sum of amount of each 'group by' is negative.
My problematic is to get all ids of the rows concerned by a 'group by' where each group is validate by a sum condition.
I find many solutions which don't work for me.
The best solution I found is to request the db a first time with the 'group by' and the sum, then return ids to finally request the db another time with all of them.
Here an example of what I would like (it doesn't work!) :
SELECT * FROM transaction_table transaction
AND transaction.id IN (
select string_agg(grouped::character varying, ',' ) from (
SELECT array_agg(transaction2.id) as grouped FROM transaction_table transaction2
WHERE transaction2.c_scte='c'
AND (same conditions)
GROUP BY
transaction2.motto ,
transaction2.accountBnf ,
transaction2.payment ,
transaction2.accountClt
HAVING sum(transaction2.amount)<0
)
);
the result of the array_agg is like:
{39758,39759}
{39757,39756,39755,39743,39727,39713}
and the string_agg is :
{39758,39759},{39757,39756,39755,39743,39727,39713}
Now I just need to use them but I don't know how to...
unfortunatly, it doesn't work because of type casting :
ERROR: operator does not exist: integer = integer[]
Indice : No operator matches the given name and argument type(s). You might need to add explicit type casts.
Maybe you are looking for
SELECT id, motto, accountbnf, payment, accountclnt, amount
FROM (SELECT id, motto, accountbnf, payment, accountclnt, amount,
sum(amount)
OVER (PARTITION BY motto, accountbnf, payment, accountclnt)
AS group_total
FROM transaction_table) AS q
WHERE group_total < 0;
The inner SELECT adds an additional column using a window function that calculates the sum for each group, and the outer query removes all results where that sum is not negative.
Finally I found this option using the 'unnest' method. It works perfectly.
Array_agg bring together all ids in different array
unnest flattened all of them
This comes from here
SELECT * FROM transaction_table transaction
WHERE transaction.id = ANY(
SELECT unnest(array_agg(transaction2.id)) as grouped FROM transaction_table transaction2
WHERE transaction2.c_scte='c'
AND (same conditions)
GROUP BY
transaction2.motto ,
transaction2.accountBnf ,
transaction2.payment ,
transaction2.accountClt
HAVING sum(transaction2.amount)<0
);
The problem with this solution is that hibernate doesn't take into account the array_agg method.
Does any one know how to create crosstab queries in PostgreSQL?
For example I have the following table:
Section Status Count
A Active 1
A Inactive 2
B Active 4
B Inactive 5
I would like the query to return the following crosstab:
Section Active Inactive
A 1 2
B 4 5
Is this possible?
Install the additional module tablefunc once per database, which provides the function crosstab(). Since Postgres 9.1 you can use CREATE EXTENSION for that:
CREATE EXTENSION IF NOT EXISTS tablefunc;
Improved test case
CREATE TABLE tbl (
section text
, status text
, ct integer -- "count" is a reserved word in standard SQL
);
INSERT INTO tbl VALUES
('A', 'Active', 1), ('A', 'Inactive', 2)
, ('B', 'Active', 4), ('B', 'Inactive', 5)
, ('C', 'Inactive', 7); -- ('C', 'Active') is missing
Simple form - not fit for missing attributes
crosstab(text) with 1 input parameter:
SELECT *
FROM crosstab(
'SELECT section, status, ct
FROM tbl
ORDER BY 1,2' -- needs to be "ORDER BY 1,2" here
) AS ct ("Section" text, "Active" int, "Inactive" int);
Returns:
Section | Active | Inactive
---------+--------+----------
A | 1 | 2
B | 4 | 5
C | 7 | -- !!
No need for casting and renaming.
Note the incorrect result for C: the value 7 is filled in for the first column. Sometimes, this behavior is desirable, but not for this use case.
The simple form is also limited to exactly three columns in the provided input query: row_name, category, value. There is no room for extra columns like in the 2-parameter alternative below.
Safe form
crosstab(text, text) with 2 input parameters:
SELECT *
FROM crosstab(
'SELECT section, status, ct
FROM tbl
ORDER BY 1,2' -- could also just be "ORDER BY 1" here
, $$VALUES ('Active'::text), ('Inactive')$$
) AS ct ("Section" text, "Active" int, "Inactive" int);
Returns:
Section | Active | Inactive
---------+--------+----------
A | 1 | 2
B | 4 | 5
C | | 7 -- !!
Note the correct result for C.
The second parameter can be any query that returns one row per attribute matching the order of the column definition at the end. Often you will want to query distinct attributes from the underlying table like this:
'SELECT DISTINCT attribute FROM tbl ORDER BY 1'
That's in the manual.
Since you have to spell out all columns in a column definition list anyway (except for pre-defined crosstabN() variants), it is typically more efficient to provide a short list in a VALUES expression like demonstrated:
$$VALUES ('Active'::text), ('Inactive')$$)
Or (not in the manual):
$$SELECT unnest('{Active,Inactive}'::text[])$$ -- short syntax for long lists
I used dollar quoting to make quoting easier.
You can even output columns with different data types with crosstab(text, text) - as long as the text representation of the value column is valid input for the target type. This way you might have attributes of different kind and output text, date, numeric etc. for respective attributes. There is a code example at the end of the chapter crosstab(text, text) in the manual.
db<>fiddle here
Effect of excess input rows
Excess input rows are handled differently - duplicate rows for the same ("row_name", "category") combination - (section, status) in the above example.
The 1-parameter form fills in available value columns from left to right. Excess values are discarded.
Earlier input rows win.
The 2-parameter form assigns each input value to its dedicated column, overwriting any previous assignment.
Later input rows win.
Typically, you don't have duplicates to begin with. But if you do, carefully adjust the sort order to your requirements - and document what's happening.
Or get fast arbitrary results if you don't care. Just be aware of the effect.
Advanced examples
Pivot on Multiple Columns using Tablefunc - also demonstrating mentioned "extra columns"
Dynamic alternative to pivot with CASE and GROUP BY
\crosstabview in psql
Postgres 9.6 added this meta-command to its default interactive terminal psql. You can run the query you would use as first crosstab() parameter and feed it to \crosstabview (immediately or in the next step). Like:
db=> SELECT section, status, ct FROM tbl \crosstabview
Similar result as above, but it's a representation feature on the client side exclusively. Input rows are treated slightly differently, hence ORDER BY is not required. Details for \crosstabview in the manual. There are more code examples at the bottom of that page.
Related answer on dba.SE by Daniel Vérité (the author of the psql feature):
How do I generate a pivoted CROSS JOIN where the resulting table definition is unknown?
SELECT section,
SUM(CASE status WHEN 'Active' THEN count ELSE 0 END) AS active, --here you pivot each status value as a separate column explicitly
SUM(CASE status WHEN 'Inactive' THEN count ELSE 0 END) AS inactive --here you pivot each status value as a separate column explicitly
FROM t
GROUP BY section
You can use the crosstab() function of the additional module tablefunc - which you have to install once per database. Since PostgreSQL 9.1 you can use CREATE EXTENSION for that:
CREATE EXTENSION tablefunc;
In your case, I believe it would look something like this:
CREATE TABLE t (Section CHAR(1), Status VARCHAR(10), Count integer);
INSERT INTO t VALUES ('A', 'Active', 1);
INSERT INTO t VALUES ('A', 'Inactive', 2);
INSERT INTO t VALUES ('B', 'Active', 4);
INSERT INTO t VALUES ('B', 'Inactive', 5);
SELECT row_name AS Section,
category_1::integer AS Active,
category_2::integer AS Inactive
FROM crosstab('select section::text, status, count::text from t',2)
AS ct (row_name text, category_1 text, category_2 text);
DB Fiddle here:
Everything works: https://dbfiddle.uk/iKCW9Uhh
Without CREATE EXTENSION tablefunc; you get this error: https://dbfiddle.uk/j8W1CMvI
ERROR: function crosstab(unknown, integer) does not exist
LINE 4: FROM crosstab('select section::text, status, count::text fro...
^
HINT: No function matches the given name and argument types. You might need to add explicit type casts.
Solution with JSON aggregation:
CREATE TEMP TABLE t (
section text
, status text
, ct integer -- don't use "count" as column name.
);
INSERT INTO t VALUES
('A', 'Active', 1), ('A', 'Inactive', 2)
, ('B', 'Active', 4), ('B', 'Inactive', 5)
, ('C', 'Inactive', 7);
SELECT section,
(obj ->> 'Active')::int AS active,
(obj ->> 'Inactive')::int AS inactive
FROM (SELECT section, json_object_agg(status,ct) AS obj
FROM t
GROUP BY section
)X
Sorry this isn't complete because I can't test it here, but it may get you off in the right direction. I'm translating from something I use that makes a similar query:
select mt.section, mt1.count as Active, mt2.count as Inactive
from mytable mt
left join (select section, count from mytable where status='Active')mt1
on mt.section = mt1.section
left join (select section, count from mytable where status='Inactive')mt2
on mt.section = mt2.section
group by mt.section,
mt1.count,
mt2.count
order by mt.section asc;
The code I'm working from is:
select m.typeID, m1.highBid, m2.lowAsk, m1.highBid - m2.lowAsk as diff, 100*(m1.highBid - m2.lowAsk)/m2.lowAsk as diffPercent
from mktTrades m
left join (select typeID,MAX(price) as highBid from mktTrades where bid=1 group by typeID)m1
on m.typeID = m1.typeID
left join (select typeID,MIN(price) as lowAsk from mktTrades where bid=0 group by typeID)m2
on m1.typeID = m2.typeID
group by m.typeID,
m1.highBid,
m2.lowAsk
order by diffPercent desc;
which will return a typeID, the highest price bid and the lowest price asked and the difference between the two (a positive difference would mean something could be bought for less than it can be sold).
There's a different dynamic method that I've devised, one that employs a dynamic rec. type (a temp table, built via an anonymous procedure) & JSON. This may be useful for an end-user who can't install the tablefunc/crosstab extension, but can still create temp tables or run anon. proc's.
The example assumes all the xtab columns are the same type (INTEGER), but the # of columns is data-driven & variadic. That said, JSON aggregate functions do allow for mixed data types, so there's potential for innovation via the use of embedded composite (mixed) types.
The real meat of it can be reduced down to one step if you want to statically define the rec. type inside the JSON recordset function (via nested SELECTs that emit a composite type).
dbfiddle.uk
https://dbfiddle.uk/N1EzugHk
Crosstab function is available under the tablefunc extension. You'll have to create this extension one time for the database.
CREATE EXTENSION tablefunc;
You can use the below code to create pivot table using cross tab:
create table test_Crosstab( section text,
status text,
count numeric)
insert into test_Crosstab values ( 'A','Active',1)
,( 'A','Inactive',2)
,( 'B','Active',4)
,( 'B','Inactive',5)
select * from crosstab(
'select section
,status
,count
from test_crosstab'
)as ctab ("Section" text,"Active" numeric,"Inactive" numeric)
How to trim first three characters of a column in select query in DB2?. I tried below query but did not work
SELECT
MIN(Column1),UPPER(RIGHT(Column2, LENGTH(Column2 - 3))) AS TEST
FROM TEST_TABLE
GROUP BY UPPER(Column2)
ORDER BY UPPER(Column2);
I got below exception
The statement cannot be processed.
User response:
Correct the statement by including the expression in the GROUP BY clause
that are in the SELECT clause, HAVING clause, or ORDER BY clause or by
removing the column function from the SELECT statement.
sqlcode: -119
sqlstate: 42803
You can simply use substring function to do the same.
SELECT
MIN(Column1),substr(Column2,4) AS TEST
FROM TEST_TABLE
GROUP BY UPPER(substr(Column2,4))
ORDER BY UPPER(substr(Column2,4));
Just do:
SELECT
MIN(Column1),UPPER(substr(Column2, 4)) AS TEST
FROM TEST_TABLE
GROUP BY UPPER(substr(Column2, 4))
ORDER BY 2;