Related
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 am new in postgres and basically have no experience. I have a table with a column includes key and value. I need write a query which return a table with the all the columns of the table and additional columns as key as the column name and the value under it.
My input is like:
id | name|message
12478| A |{img_type:=png,key_id:=f235, client_status:=active, request_status:=open}
12598| B |{img_type:=none,address_id:=c156, client_status:=active, request_status:=closed}
output will be:
id |name| Img_type|Key_id|address_id|Client_status|Request_status
12478| A | png |f235 |NULL |active | open
12598| B | none |NULL |c156 |active | closed
Any help would be greatly appreciated.
The only thing I can think of, is a regular expression to extract the key/value pairs.
select id, name,
(regexp_match(message, '(img_type:=)([^,}]+),{0,1}'))[2] as img_type,
(regexp_match(message, '(key_id:=)([^,}]+),{0,1}'))[2] as key_id,
(regexp_match(message, '(client_status:=)([^,}]+),{0,1}'))[2] as client_status,
(regexp_match(message, '(request_status:=)([^,}]+),{0,1}'))[2] as request_status
from the_table;
regexp_match returns an array of matches. As the regex contains two groups (one for the "key" and one for the "value"), the [2] takes the second element of the array.
This is quite expensive and error prone (e.g. if any of the values contains a , and you need to deal with quoted values). If you have any chance to change the application that stores the value, you should seriously consider changing your code to store a proper JSON value, e.g.
{"img_type": "png", "key_id": "f235", "client_status": "active", "request_status": "open"}'
then you can use e.g. message ->> 'img_type' to retrieve the value for the key img_type
You might also want to consider a properly normalized table, where each of those keys is a real column.
I can do it with function.
I am sure about the performance but here is my suggestion:
CREATE TYPE log_type AS (img_type TEXT, key_id TEXT, address_id TEXT, client_status TEXT, request_status TEXT);
CREATE OR REPLACE FUNCTION populate_log(data TEXT)
RETURNS log_type AS
$func$
DECLARE
r log_type;
BEGIN
select x.* into r
from
(
select
json_object(array_agg(array_data)) as json_data
from (
select unnest(string_to_array(trim(unnest(string_to_array(substring(populate_log.data, '[^{}]+'), ','))), ':=')) as array_data
) d
) d2,
lateral json_to_record(json_data) as x(img_type text, key_id text, address_id text, client_status text, request_status text);
RETURN r;
END
$func$ LANGUAGE plpgsql;
with log_data (id, name, message) as (
values
(12478, 'A', '{img_type:=png,key_id:=f235, client_status:=active, request_status:=open}'),
(12598, 'B', '{img_type:=none,address_id:=c156, client_status:=active, request_status:=closed}')
)
select id, name, l.*
from log_data, lateral populate_log(message) as l;
What you finally write in query will be something like this, imagine that the data is in a table named log_data :
select id, name, l.*
from log_data, lateral populate_log(message) as l;
I suppose that message column is a text, in Postgres it might be an array, in that case you have to remove some conversions, string_to_array(substring(populate_log.data)) -> populate_log.data
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 with following columns:
(ID, row_num, col_num, pix_centroid, pix_val1).
I have more than 1000 records. I am inserting my data using:
insert into pixelbased (row_num, col_num, pix_centroid, pix_val)
select
(ST_PixelAsPolygons(rast, 1)).x as X,
(ST_PixelAsPolygons(rast, 1)).y as Y,
(ST_Centroid((ST_PixelAsPolygons(rast, 1)).geom)) as geom,
(ST_PixelAsPolygons(rast, 1)).val as pix_val1
from mytable
where rid=1`
Now I am trying to insert all the other records as a column and _pix_val1_ column is important for me. All the other columns will remain the same. In the other word, I want the final table to have these columns:
(ID, row_num, col_num, pix_centroid, pix_val1, pix_val2, pix_val3, ....)
Is there a way to do it?
I would want to store this data as a bitmap in a bytea if possible. Here's how to take a series of byte values and turn it into a bytea:
WITH bytes(b) AS (SELECT x % 256 FROM generate_series(1,53000) x)
SELECT ('\x'||string_agg(lpad(to_hex(b),2,'0'),''))::bytea FROM bytes;
You can access fields or ranges of the byte array using the substr function. This bytea is organized as a linear pixel array, but you may find it more useful to organize it into a more traditional bitmap format. Also, if your pixels are more than one byte you may need to cope with big-endian vs little-endian. You could do that in SQL, but it's likely to be much easier in a procedural language like PL/Perl.
Failing that, a multidimensional array would be a somewhat reasonable choice.
Using a generate_series statement as a substitute for your pix_val field for convenient testing, this query produces a two-dimensional array of integers using two aggregation passes:
SELECT ('{'||string_agg(subarray, ',')||'}')::integer[] AS arr
FROM (
SELECT array_agg(x order by x)::text
FROM generate_series(1,53000) x
GROUP BY width_bucket(x, 1, 53001, 100)
) a(subarray);
The unfortunate use of the string literal form of the two dimensional array is made necessary by the fact that array_agg cannot aggregate arrays. In my view this is a real wart in PostgreSQL; in general its multidimensional arrays are odd to work with and inconsistent with how most applications and languages implement arrays.
You can get fields out of the array by indexing it. Example:
regress=> SELECT ('{'||string_agg(subarray, ',')||'}')::integer[] AS arr INTO test FROM (SELECT array_agg(x order by x)::text from generate_series(1,53000) x GROUP BY width_bucket(x, 1, 53001, 100)) a(subarray);
regress=> \d test
Table "public.test"
Column | Type | Modifiers
--------+-----------+-----------
arr | integer[] |
test contains a single array with two dimensions:
regress=> \x
regress=> select array_dims(test.arr), array_ndims(test.arr), array_length(test.arr,1), array_length(test.arr,2) FROM test;
-[ RECORD 1 ]+---------------
array_dims | [1:100][1:530]
array_ndims | 2
array_length | 100
array_length | 530
I can get elements with two-level indexing:
regress=> SELECT test.arr[4][4] FROM test;
arr
------
1594
(1 row)
or a "column" with slicing:
regress=> SELECT test.arr[4:4][1:530] FROM test;
Oddly, this is still a two-dimensional array, the top dimension is just one element deep. You can flatten it (inefficiently) with unnest and array_agg if you need to.
Two-dimensional arrays in PostgreSQL are somewhat weird, as you can see, but so is what you're trying to do.
I'm using oracle database and facing a problem where two id_poduct.nextval is creating as error: ORA-00001: unique constraint (SYSTEM.SYS_C004166) violated
It is a primary key. To use all is a requirement. Can I use 2 .nextval in a statement?
insert all
into sale_product values (id_product.nextval, id.currval, 'hello', 123, 1)
into sale_product values (id_product.nextval, id.currval, 'hi', 123, 1)
select * from dual;
insert into sale_product
select id_product.nextval, id.currval, a, b, c
from
(
select 'hello' a, 123 b, 1 c from dual union all
select 'hi' a, 123 b, 1 c from dual
);
This doesn't use the insert all syntax, but it works the same way if you are only inserting into the same table.
The value of id_product.NEXTVAL in the first INSERT is the same as the second INSERT, hence you'll get the unique constraint violation. if you remove the constraint and perform the insert, you'll notice the duplicate values!
The only way is to perform two bulk INSERTS in sequence or to have two seperate sequences with a different range, the latter would require an awful lot of coding and checking.
create table temp(id number ,id2 number);
insert all
into temp values (supplier_seq.nextval, supplier_seq.currval)
into temp values (supplier_seq.nextval, supplier_seq.currval)
select * from dual;
ID ID2
---------- ----------
2 2
2 2
Refrence
The subquery of the multitable insert statement cannot use a sequence
http://docs.oracle.com/cd/B19306_01/server.102/b14200/statements_9014.htm#i2080134