Related
I have a table cusers with a primary key:
primary key(uid, lid, cnt)
And I try to insert some values into the table:
insert into cusers (uid, lid, cnt, dyn, ts)
values
(A, B, C, (
select C - cnt
from cusers
where uid = A and lid = B
order by ts desc
limit 1
), now())
on conflict do nothing
Quite often (with the possibility of 98%) a row cannot be inserted to cusers because it violates the primary key constraint, so hard select queries do not need to be executed at all. But as I can see PostgreSQL first counts the select query as a result of dyn column and only then rejects row because of uid, lid, cnt violation.
What is the best way to insert rows quickly in such situation?
Another explanation
I have a system where one row depends on another. Here is an example:
(x, x, 2, 2, <timestamp>)
(x, x, 5, 3, <timestamp>)
Two columns contain an absolute value (2 and 5) and relative value (2, 5 - 2). Each time I insert new row it should:
avoid same rows (see primary key constraint)
if new row differs, it should count a difference and put it into the dyn column (so I take the last inserted row for the user according to the timestamp and subtract values).
Another solution I've found is to use returning uid, lid, ts for inserts and get user ids which were really inserted - this is how I know they have differences from existing rows. Then I update inserted values:
update cusers
set dyn = (
select max(cnt) - min(cnt)
from (
select cnt
from cusers
where uid = A and lid = B
order by ts desc
limit 2) Table
)
where uid = A and lid = B and ts = TS
But it is not a fast approach either, as it seeks all over the ts column to find the two last inserted rows for each user. I need a fast insert query as I insert millions of rows at a time (but I do not write duplicates).
What the solution can be? May be I need a new index for this? Thanks in advance.
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)
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)
When using a Table Value Constructor (http://msdn.microsoft.com/en-us/library/dd776382(v=sql.100).aspx) to insert multiple rows, is the order of any identity column populated guaranteed to match the rows in the TVC?
E.g.
CREATE TABLE A (a int identity(1, 1), b int)
INSERT INTO A(b) VALUES (1), (2)
Are the values of a guaranteed by the engine to be assigned in the same order as b, i.e. in this case so they match a=1, b=1 and a=2, b=2.
Piggybacking on my comment above, and knowing that the behavior of an insert / select+order by will guarantee generation of identity order (#4: from this blog)
You can use the table value constructor in the following fashion to accomplish your goal (not sure if this satisfies your other constraints) assuming you wanted your identity generation to be based on category id.
insert into thetable(CategoryId, CategoryName)
select *
from
(values
(101, 'Bikes'),
(103, 'Clothes'),
(102, 'Accessories')
) AS Category(CategoryID, CategoryName)
order by CategoryId
It depends as long as your inserting the records in one shot . For example after inserting if you delete the record where a=2 and then again re insert the value b=2 ,then identity column's value will be the max(a)+1
To demonstrate
DECLARE #Sample TABLE
(a int identity(1, 1), b int)
Insert into #Sample values (1),(2)
a b
1 1
2 2
Delete from #Sample where a=2
Insert into #Sample values (2)
Select * from #Sample
a b
1 1
3 2
I have a table with many(+1000) columns and rows(~1M). The columns have either the value 1 , or are NULL.
I want to be able to select, for a specific row (user) retrieve the column names that have a value of 1.
Since there are many columns on the table, specifying the columns would yield a extremely long query.
You're doing something SQL is quite bad at - dynamic access to columns, or treating a row as a set. It'd be nice if this were easier, but it doesn't work well with SQL's typed nature and the concept of a relation. Working with your data set in its current form is going to be frustrating; consider storing an array, json, or hstore of values instead.
Actually, for this particular data model, you could probably use a bitfield. See bit(n) and bit varying(n).
It's still possible to make a working query with your current model PostgreSQL extensions though.
Given sample:
CREATE TABLE blah (id serial primary key, a integer, b integer, c integer);
INSERT INTO blah(a,b,c) VALUES (NULL, NULL, 1), (1, NULL, 1), (NULL, NULL, NULL), (1, 1, 1);
I would unpivot each row into a key/value set using hstore (or in newer PostgreSQL versions, the json functions). SQL its self provides no way to dynamically access columns, so we have to use an extension. So:
SELECT id, hs FROM blah, LATERAL hstore(blah) hs;
then extract the hstores to sets:
SELECT id, k, v FROM blah, LATERAL each(hstore(blah)) kv(k,v);
... at which point your can filter for values matching the criteria. Note that all columns have been converted to text, so you may want to cast it back:
SELECT id, k FROM blah, LATERAL each(hstore(blah)) kv(k,v) WHERE v::integer = 1;
You also need to exclude id from matching, so:
regress=> SELECT id, k FROM blah, LATERAL each(hstore(blah)) kv(k,v) WHERE v::integer = 1 AND
k <> 'id';
id | k
----+---
1 | c
2 | a
2 | c
4 | a
4 | b
4 | c
(6 rows)