PostgreSQL - rounding floating point numbers - postgresql

I have a newbie question about floating point numbers in PostgreSQL 9.2.
Is there a function to round a floating point number directly, i.e. without having to convert the number to a numeric type first?
Also, I would like to know whether there is a function to round by an arbitrary unit of measure, such as to nearest 0.05?
When casting the number into a decimal form first, the following query works perfectly:
SELECT round(1/3.::numeric,4);
round
--------
0.3333
(1 row)
Time: 0.917 ms
However, what really I'd like to achieve is something like the following:
SELECT round(1/3.::float,4);
which currently gives me the following error:
ERROR: function round(double precision, integer) does not exist at character 8
Time: 0.949 ms
Thanks

Your workaround solution works with any version of PostgreSQL,
SELECT round(1/3.::numeric,4);
But the answer for "Is there a function to round a floating point number directly?", is no.
The cast problem
You are reporting a well-known "bug", there is a lack of overloads in some PostgreSQL functions... Why (???): I think "it is a lack" (!), but #CraigRinger, #Catcall (see comments at Craig's anser) and the PostgreSQL team agree about "PostgreSQL's historic rationale".
The solution is to develop a centralized and reusable "library of snippets", like pg_pubLib. It implements the strategy described below.
Overloading as casting strategy
You can overload the build-in ROUND function with,
CREATE FUNCTION ROUND(float,int) RETURNS NUMERIC AS $f$
SELECT ROUND($1::numeric,$2);
$f$ language SQL IMMUTABLE;
Now your dream will be reality, try
SELECT round(1/3.,4); -- 0.3333 numeric
It returns a (decimal) NUMERIC datatype, that is fine for some applications... An alternative is to use round(1/3.,4)::float or to create a round_tofloat() function.
Other alternative, to preserve input datatype and use all range of accuracy-precision of a floating point number (see IanKenney's answer), is to return a float when the accuracy is defined,
CREATE or replace FUNCTION ROUND(
input float, -- the input number
accuracy float -- accuracy
) RETURNS float AS $f$
SELECT ROUND($1/accuracy)*accuracy
$f$ language SQL IMMUTABLE;
COMMENT ON FUNCTION ROUND(float,float) IS 'ROUND by accuracy.';
Try
SELECT round(21.04, 0.05); -- 21.05
SELECT round(21.04, 5::float); -- 20
SELECT round(pi(), 0.0001); -- 3.1416
SELECT round(1/3., 0.0001); -- 0.33330000000000004 (ops!)
To avoid floating-pont truncation (internal information loss), you can "clean" the result, for example truncating on 9 digits:
CREATE or replace FUNCTION ROUND9(
input float, -- the input number
accuracy float -- accuracy
) RETURNS float AS $f$
SELECT (ROUND($1/accuracy)*accuracy)::numeric(99,9)::float
$f$ language SQL IMMUTABLE;
Try
SELECT round9(1/3., 0.00001); -- 0.33333 float, solved!
SELECT round9(1/3., 0.005); -- 0.335 float, ok!
PS: the command \df round, on psql after overloadings, will show something like this table
Schema | Name | Result | Argument
------------+-------+---------+------------------
myschema | round | numeric | float, int
myschema | round | float | float, float
pg_catalog | round | float | float
pg_catalog | round | numeric | numeric
pg_catalog | round | numeric | numeric, int
where float is synonymous of double precision and myschema is public when you not use a schema. The pg_catalog functions are the default ones, see at Guide the build-in math functions.
More details
See a complete Wiki answer here.

You can accomplish this by doing something along the lines of
select round( (21.04 /0.05 ),0)*0.05
where 21.04 is the number to round and 0.05 is the accuracy.

Related

Preventing integer division by casting one of the operands as non-integer

Do I have to cast both the numerator and the denominator to a non-integer data type to prevent integer division?
It is enough to cast one of the operands (either the numerator or the denominator) to prevent integer division, as the manual says. Casting both is not necessary:
select 2 / 4; -- 0
select 2::numeric / 4; -- 0.50000000000000000000
select 2 / 4::numeric; -- 0.50000000000000000000
select 2::numeric / 4::numeric; -- 0.50000000000000000000
SEE ALSO:
PostgreSQL manual: Numeric Types
PostgreSQL manual: Mathematical Functions and Operators
PostgreSQL: When casting an integer to a non-integer type to force floating point division in PostgreSQL, which number type should I use?
These have 2 casts, while only 1 cast is needed:
How to divide COUNT(CASE ) by COUNT()
Result from division with INT in Postgres other then MySQL

Understand rounded results after division involving floating point types

In Postgres 14, I see rounded results that do not make sense to me. Trying to understand what is going on. In all cases I am dividing 19 by 3.
Casting either integer value to a real:
SELECT 19::real /3;
yields a value of 6.333333333333333
SELECT 19/3::real;
yields a value of 6.333333333333333
However, casting both sides to real yields:
SELECT 19::real/3::real;
yields a value of 6.3333335
Interestingly enough, if I cast both sides to double precision or float, the answer is 6.333333333333333
Also
SELECT 19.0 / 3.0;
yields 6.333333333333333
SELECT 19.0::real / 3.0::real;
yields 6.3333335
SELECT ( 16.0 / 3.0) :: real;
yields 6.3333335
I now see that:
SELECT 6.333333333333333::real;
yields 6.33333335
So the real issue seems to be:
Why are we rounding in this weird way (I know that real / floats are inexact but this seems extreme.)
What data type is 19::real / 3;
Why are we rounding in this weird way? (I know that real / floats are inexact but this seems extreme.)
Because real (float4) only uses 4 bytes for storage, and that's the closest possible value it can encode.
What data type is 19::real / 3;?
Check with pg_typeof() if your client does not indicate the column type (like pgAdmin4 does).
test=> SELECT pg_typeof(19::real / 3);
pg_typeof
------------------
double precision
(1 row)
test=> SELECT pg_typeof(19/3::real);
pg_typeof
------------------
double precision
(1 row)
test=> SELECT pg_typeof(19::real/3::real);
pg_typeof
-----------
real
(1 row)
This is the complete list of available division operators involving real:
test=> SELECT oprleft::regtype, oprright::regtype, oprresult::regtype
test-> FROM pg_operator
test-> WHERE oprname = '/'
test-> AND 'real'::regtype IN (oprleft, oprright);
oprleft | oprright | oprresult
------------------+------------------+------------------
real | real | real
money | real | money
real | double precision | double precision
double precision | real | double precision
(4 rows)
For combinations of types that have no exact match here, Postgres finds the closest match according to its operator resolution rules. Postgres aims to preserve precision, so the only division that produces real is real / real. All other variants produce double precision (float8). (money being a corner case exception.)

Odd behavior with overloaded function in Postgres 13.3

I've added a pair of overloaded functions to handle safe vision, optionally with rounding, in PG 13.3. I've run some simple example cases through the routines and, in one case, the output varies unexpectedly. I'm hoping that someone can shed some light on what might be causing this inconsistency. First off, here is the code for the div_safe (anycompatible, anycompatible) : real and div_safe (anycompatible, anycompatible, integer) : real functions. (I tried replacing integer with anycompatible in that third parameter, it made no difference.)
------------------------------
-- No rounding
------------------------------
CREATE OR REPLACE FUNCTION tools.div_safe(
numerator anycompatible,
denominator anycompatible)
RETURNS real
AS $BODY$
SELECT numerator/NULLIF(denominator,0)::real
$BODY$
LANGUAGE SQL;
COMMENT ON FUNCTION tools.div_safe (anycompatible, anycompatible) IS
'Pass in any two values that are, or can be coerced into, numbers, and get a safe division real result.';
------------------------------
-- Rounding
------------------------------
CREATE OR REPLACE FUNCTION tools.div_safe(
numerator anycompatible,
denominator anycompatible,
rounding_in integer)
RETURNS real
AS $BODY$
SELECT ROUND(numerator/NULLIF(denominator,0)::numeric, rounding_in)::real
$BODY$
LANGUAGE sql;
COMMENT ON FUNCTION tools.div_safe (anycompatible, anycompatible, integer) IS
'Pass in any two values that are, or can be coerced into, numbers, the number of rounding digits, and get back a rounded, safe division real result.';
I threw together these checks, as I was working out the code:
-- (real, int))
select '5.1/nullif(null,0)', 5.1/nullif(null,0) as result union all
select 'div_safe(5.1,0)', div_safe(5.1, 0) as result union all
-- (0, 0)
select '0/nullif(0,0)', 5.1/nullif(null,0) as result union all
select 'div_safe(0, 0)', div_safe(0, 0) as result union all
-- (int, int)
select '5/nullif(8,0)::real', 5/nullif(8,0)::real as result union all
select 'div_safe(5,8)', div_safe(5, 8) as result union all
-- (string, int)
select 'div_safe(''5'',8)', div_safe('5', 8) as result union all
select 'div_safe(''8'',5)', div_safe('8', 5) as result union all
-- Rounding: Have to convert real result to numeric to pass it into ROUND (numeric, integer)
select 'round(div_safe(10,3)::numeric, 2)',
round(div_safe(10,3)::numeric, 2) as result union all
-- Pass a third parameter to specify rounding:
select 'div_safe(20,13,2)', div_safe(20, 13, 2) as result
+-----------------------------------+--------------------+
| ?column? | result |
+-----------------------------------+--------------------+
| 5.1/nullif(null,0) | NULL |
| div_safe(5.1,0) | NULL |
| 0/nullif(0,0) | NULL |
| div_safe(0, 0) | NULL |
| 5/nullif(8,0)::real | 0.625 |
| div_safe(5,8) | 0.625 |
| div_safe('5',8) | 0.625 |
| div_safe('8',5) | 1.600000023841858 |
| round(div_safe(10,3)::numeric, 2) | 3.33 |
| div_safe(20,13,2) | 1.5399999618530273 |
+-----------------------------------+--------------------+
The last line looks wrong to me, it should be rounded to 1.54. I've discovered that I get this behavior in the presence of one of the other tests. Specifically:
select '5/nullif(8,0)::real', 5/nullif(8,0)::real as result union all
Without that, the final line returns 1.54, as expected.
Can anyone shed some light on what's going on? Is it something to do with the combination of anycompatible with UNION ALL? Something incredibly simple that I'm missing?
And, if anyone knows, is there a chance that anynum might be added as a pseudo-type in the future?
Follow-up regarding inconsistent output
I've already gotten a helpful answer to my original question (thanks!), and am following up on a follow-on point. Namely, why does my function round data before returning it, and then the value is changed in the final result. It think that there's something fundamental I'm missing here, and it's not obvious. I figured that I needed to confirm that the right version of the function is being called, and RAISE NOTIFICATION to get at the values, as seen inside the method. This new version is div_safe_p (anycompatible, anycompatible, integer) : real, and is written in PL/PgSQL:
------------------------------
-- Rounding
------------------------------
drop function if exists tools.div_safe_p(anycompatible,anycompatible,integer);
CREATE OR REPLACE FUNCTION tools.div_safe_p(
numerator anycompatible,
denominator anycompatible,
rounding_in integer)
RETURNS real
AS $BODY$
DECLARE
result_r real := 0;
BEGIN
SELECT ROUND(numerator/NULLIF(denominator,0)::numeric, rounding_in)::real INTO result_r;
RAISE NOTICE 'Calling div_safe_p(%, %, %) : %', numerator, denominator, rounding_in, result_r;
RETURN result_r;
END
$BODY$
LANGUAGE plpgsql;
COMMENT ON FUNCTION tools.div_safe_p (anycompatible, anycompatible, integer) IS
'Pass in any two values that are, or can be coerced into, numbers, the number of roudning digits, and get back a rounded, safe division real result.';
Here's a sample call, and output:
select 5/nullif(8,0)::real union all
select div_safe_p(10,3, 2)::real
+--------------------+
| ?column? |
+--------------------+
| 0.625 |
| 3.3299999237060547 |
+--------------------+
The result of div_safe_p appears to be converted to a double, not a real. Check the RAISE NOTICE console output, the function returned 3.33:
NOTICE: Calling div_safe_p(10, 3, 2) : 3.33
Yes, this 3.33 is shown as 3.3299999237060547. I'm not clear why the value is modified from how it's returned from the function. I also can't reproduce the transformation by converting the value by hand. Both select 3.33::real and select 3.33::double precision return 3.33.
Another variant, the same as the original except without the ::real castings:
select 5/nullif(8,0) union all
select div_safe_p(10,3, 2)
+----------+
| ?column? |
+----------+
| 0 |
| 3.33 |
+----------+
It certainly looks like the first value encountered is guiding the column typing, as answered already. However, I'm stumped as to why this changes the behavior of the function itself. Or, at least changes how the output is interpreted.
If this sounds like a fine point...maybe it is. When I run into peculiarities that I can't explain, I hope to figure out what's going on so that I can predict and troubleshoot more complex examples in the future.
Thanks for any illumination!
This is as expected on account of the type resolution rules for UNION:
Select the first non-unknown input type as the candidate type, then consider each other non-unknown input type, left to right.
Now the first non-NULL data type is double precision (see the type resolution rules for operators), so all results get cast to double precision resulting in the imprecision being visible. Without that test, the result is of type real, so PostgreSQL shows few enough digits to hide the imprecision.
It is useful to use the pg_typeof function to show the data type, that will clear things up:
SELECT pg_typeof(v)
FROM (SELECT NULL
UNION ALL
SELECT 2::real / 3::real
UNION ALL
SELECT pi()) AS t(v);
pg_typeof
══════════════════
double precision
double precision
double precision
(3 rows)

How to get cosine distance between two vectors in postgres?

I am wondering if there is a way to get cosine distance of two vectors in postgres.
For storing vectors I am using CUBE data type.
Below is my table definition:
test=# \d vectors
Table "public.vectors"
Column | Type | Collation | Nullable | Default
--------+---------+-----------+----------+-------------------------------------
id | integer | | not null | nextval('vectors_id_seq'::regclass)
vector | cube | | |
Also, sample data is given below:
test=# select * from vectors order by id desc limit 2;
id | vector
---------+------------------------------------------
2000000 | (109, 568, 787, 938, 948, 126, 271, 499)
1999999 | (139, 365, 222, 653, 313, 103, 215, 796)
I actually can write my own PLPGSql function for this, but wanted to avoid this as it might not be efficient.
About your table
First of all, I believe you should change your data type to plain array.
CREATE TABLE public.vector (
id serial NOT NULL,
vctor double precision [3] --for three dimensional vectors; of course you can change the dimension or leave it unbounded if you need it.
);
INSERT INTO public.vector (vctor) VALUES (ARRAY[2,3,4]);
INSERT INTO public.vector (vctor) VALUES (ARRAY[3,4,5]);
So
SELECT * FROM public.vector;
Will result in the following data
id | vctor
------|---------
1 | {2,3,4}
2 | {3,4,5}
Maybe not the answer you expected but consider this
As you may know already, calculating the cosine between the vectors involves calculating the magnitudes. I don't think the problem is the algorithm but the implementation; it requires calculating squares and square roots that is expensive for a RDBMS.
Now, talking about efficiency; the server process does not take the load when calling mathematical functions. In PostgreSQL, the mathematical functions (look here) run from the C library so they are pretty efficient. However, in the end, the host has to assign some resources to make these calculations.
I would indeed think carefully before implementing these rather costly operations inside the server. But there is not a right answer; it depends on how you are using the database. For example if it is a production database with thousands of concurrent users, I would move this kind of calculation elsewhere (a middle layer or a user application.) But if there are few users and your database is for a small research operation, then it is fine to implement it as a stored procedure or a process running inside your server but keep in mind this will affect scalability or portability. Of course, there are more considerations like how many rows will be processed, or whether or not you intend to fire triggers, etc.
Consider other alternatives
Make a client app
You can do a fast and decent program in VB or the language of your choice. And let the client app make the heavy calculation and use the database for what it does best that is storing and retrieving data.
Store the data differently
For this particular example, you could store the unit vectors plus the magnitude. In this way, finding the cosine between any two vectors reduces simply to the dot product of the unit vectors (only multiplication and division and no squares nor square roots.)
CREATE TABLE public.vector (
id serial NOT NULL,
uvctor double precision [3], --for three dimensional vectors; of course you can change the dimension or make it decimal if you need it
magnitude double precision
);
INSERT INTO public.vector (vctor) VALUES (ARRAY[0.3714, 0.5571, 0.7428], 5.385); -- {Ux, Uy, Uz}, ||V|| where V = [2, 3, 4];
INSERT INTO public.vector (vctor) VALUES (ARRAY[0.4243, 0.5657, 0.7071], 7.071); -- {Ux, Uy, Uz}, ||V|| where V = [3, 4, 5];
SELECT a.vctor as a, b.vctor as b, 1-(a.uvctor[1] * b.uvctor[1] + a.uvctor[2] * b.uvctor[2] + a.uvctor[3] * b.uvctor[3]) as cosine_distance FROM public.vector a
JOIN public.vector b ON a.id != b.id;
Resulting in
a | b | cosine_distance
-----------------------------|------------------------------|------------------
{0.3714,0.5571,0.7428,5.385} | {0.4243,0.5657,0.7071,7.071} | 0.00202963
{0.4243,0.5657,0.7071,7.071} | {0.3714,0.5571,0.7428,5.385} | 0.00202963
Even if you have to calculate the magnitude of the vector inside the server, you will make it once per vector and not every time you need to get the distance between two of them. This becomes more important as the number of rows is increasing. For 1000 vectors for example, you would have to calculate the magnitude 999000 times if you wanted to obtain the cosine difference between any two vectors using the original vector components.
Any combination of the above
Conclusion
When we pursue efficiency, most of the times there is not a canonical answer. Instead we have trade-offs that we have to consider and evaluate. It always depends on the ultimate goal we need to achieve. Databases are excellent for storing and retrieving data; they can definitely make other things but that comes with an added cost. If we can live with the added overhead then it's fine; otherwise we have to consider alternatives.
you can take reference to my code.
--for calculation of norm vector --
CREATE or REPLACE FUNCTION public.vector_norm(IN vector double precision[])
RETURNS double precision AS
$BODY$
BEGIN
RETURN(SELECT SQRT(SUM(pow)) FROM (SELECT POWER(e,2) as pow from unnest(vector) as e) as norm);
END;
$BODY$ LANGUAGE 'plpgsql';
ALTER FUNCTION public.vector_norm(double precision[]) OWNER TO postgres;
COMMENT ON FUNCTION public.vector_norm(double precision[]) IS 'This function is used to find a norm of vectors.';
--call function--
select public.vector_norm('{ 0.039968978613615,0.357211461290717,0.753132887650281,0.760665621142834,0.20826127845794}')
--for caculation of dot_product--
CREATE OR REPLACE FUNCTION public.dot_product(IN vector1 double precision[], IN vector2 double precision[])
RETURNS double precision
AS $BODY$
BEGIN
RETURN(SELECT sum(mul) FROM (SELECT v1e*v2e as mul FROM unnest(vector1, vector2) AS t(v1e,v2e)) AS denominator);
END;
$BODY$ LANGUAGE 'plpgsql';
ALTER FUNCTION public.dot_product(double precision[], double precision[]) OWNER TO postgres;
COMMENT ON FUNCTION public.dot_product(double precision[], double precision[])
IS 'This function is used to find a cosine similarity between two multi-dimensional vectors.';
--call fuction--
SELECT public.dot_product(ARRAY[ 0.039968978613615,0.357211461290717,0.753132887650281,0.760665621142834,0.20826127845794],ARRAY[ 0.039968978613615,0.357211461290717,0.753132887650281,0.760665621142834,0.20826127845794])
--for calculatuion of cosine similarity--
CREATE OR REPLACE FUNCTION public.cosine_similarity(IN vector1 double precision[], IN vector2 double precision[])
RETURNS double precision
LANGUAGE 'plpgsql'
AS $BODY$
BEGIN
RETURN(select ((select public.dot_product(ARRAY[ 0.63434,0.23487,0.324323], ARRAY[ 0.63434,0.23487,0.324323]) as dot_pod)/((select public.vector_norm(ARRAY[ 0.63434,0.23487,0.324323]) as norm1) * (select public.vector_norm(ARRAY[ 0.63434,0.23487,0.324323]) as norm2))) AS similarity_value)
END;
$BODY$;
ALTER FUNCTION public.cosine_similarity(double precision[], double precision[])
OWNER TO postgres;
COMMENT ON FUNCTION public.cosine_similarity(double precision[], double precision[])
IS 'this function is used to find a cosine similarity between two vector';

PostgreSql round() giving Error [duplicate]

I am using PostgreSQL via the Ruby gem 'sequel'.
I'm trying to round to two decimal places.
Here's my code:
SELECT ROUND(AVG(some_column),2)
FROM table
I get the following error:
PG::Error: ERROR: function round(double precision, integer) does
not exist (Sequel::DatabaseError)
I get no error when I run the following code:
SELECT ROUND(AVG(some_column))
FROM table
Does anyone know what I am doing wrong?
PostgreSQL does not define round(double precision, integer). For reasons #Mike Sherrill 'Cat Recall' explains in the comments, the version of round that takes a precision is only available for numeric.
regress=> SELECT round( float8 '3.1415927', 2 );
ERROR: function round(double precision, integer) does not exist
regress=> \df *round*
List of functions
Schema | Name | Result data type | Argument data types | Type
------------+--------+------------------+---------------------+--------
pg_catalog | dround | double precision | double precision | normal
pg_catalog | round | double precision | double precision | normal
pg_catalog | round | numeric | numeric | normal
pg_catalog | round | numeric | numeric, integer | normal
(4 rows)
regress=> SELECT round( CAST(float8 '3.1415927' as numeric), 2);
round
-------
3.14
(1 row)
(In the above, note that float8 is just a shorthand alias for double precision. You can see that PostgreSQL is expanding it in the output).
You must cast the value to be rounded to numeric to use the two-argument form of round. Just append ::numeric for the shorthand cast, like round(val::numeric,2).
If you're formatting for display to the user, don't use round. Use to_char (see: data type formatting functions in the manual), which lets you specify a format and gives you a text result that isn't affected by whatever weirdness your client language might do with numeric values. For example:
regress=> SELECT to_char(float8 '3.1415927', 'FM999999999.00');
to_char
---------------
3.14
(1 row)
to_char will round numbers for you as part of formatting. The FM prefix tells to_char that you don't want any padding with leading spaces.
        ((this is a Wiki! please edit to enhance!))
Try also the old syntax for casting,
SELECT ROUND( AVG(some_column)::numeric, 2 ) FROM table;
works with any version of PostgreSQL. ...But, as definitive solution, you can overload the ROUND function.
Overloading as casting strategy
CREATE FUNCTION ROUND(float,int) RETURNS NUMERIC AS $f$
SELECT ROUND( CAST($1 AS numeric), $2 )
$f$ language SQL IMMUTABLE;
Now your instruction will works fine, try this complete comparison:
SELECT trunc(n,3), round(n,3) n_round, round(f,3) f_round,
pg_typeof(n) n_type, pg_typeof(f) f_type, pg_typeof(round(f,3)) f_round_type
FROM (SELECT 2.0/3.0, 2/3::float) t(n,f);
trunc
n_round
f_round
n_type
f_type
f_round_type
0.666
0.667
0.667
numeric
double precision
numeric
The ROUND(float,int) function is f_round, it returns a (decimal) NUMERIC datatype, that is fine for some applications: problem solved!
In another applications we need a float also as result. An alternative is to use round(f,3)::float or to create a round_tofloat() function.
Other alternative, overloading ROUND function again, and using all range of accuracy-precision of a floating point number, is to return a float when the accuracy is defined (see IanKenney's answer),
CREATE FUNCTION ROUND(
input float, -- the input number
accuracy float -- accuracy, the "counting unit"
) RETURNS float AS $f$
SELECT ROUND($1/accuracy)*accuracy
$f$ language SQL IMMUTABLE;
Try
SELECT round(21.04, 0.05); -- 21.05 float!
SELECT round(21.04, 5::float); -- 20
SELECT round(1/3., 0.0001); -- 0.3333
SELECT round(2.8+1/3., 0.5); -- 3.15
SELECT round(pi(), 0.0001); -- 3.1416
PS: the command \df round, on psql after overloadings, will show something like this table
Schema | Name | Result | Argument
------------+-------+---------+------------------
myschema | round | numeric | float, int
myschema | round | float | float, float
pg_catalog | round | float | float
pg_catalog | round | numeric | numeric
pg_catalog | round | numeric | numeric, int
where float is synonymous of double precision and myschema is public when you not use a schema. The pg_catalog functions are the default ones, see at Guide the build-in math functions.
Rounding and formating
The to_char function apply internally the round procedure, so, when your aim is only to show a final result in the terminal, you can use the FM modifier as a prefix to a numeric format pattern:
SELECT round(x::numeric,2), trunc(x::numeric,2), to_char(x, 'FM99.99')
FROM (SELECT 2.0/3) t(x);
round
trunc
to_char
0.67
0.66
.67
NOTES
Cause of the problem
There are a lack of overloads in some PostgreSQL functions, why (???): I think "it is a lack" (!), but #CraigRinger, #Catcall and the PostgreSQL team agree about "pg's historic rationale".
Note about performance and reuse
The build-in functions, such as ROUND of the pg_catalog, can be overloaded with no performance loss, when compared to direct cast encoding. Two precautions must be taken when implementing user-defined cast functions for high performance:
The IMMUTABLE clause is very important for code snippets like this, because, as said in the Guide: "allows the optimizer to pre-evaluate the function when a query calls it with constant arguments"
PLpgSQL is the preferred language, except for "pure SQL". For JIT optimizations (and sometimes for parallelism) language SQL can obtain better optimizations. Is something like copy/paste small piece of code instead of use a function call.
Conclusion: the above ROUND(float,int) function, after optimizations, is so fast than #CraigRinger's answer; it will compile to (exactly) the same internal representation. So, although it is not standard for PostgreSQL, it can be standard for your projects, by a centralized and reusable "library of snippets", like pg_pubLib.
Round to the nth bit or other numeric representation
Some people argue that it doesn't make sense for PostgreSQL to round a number of float datatype, because float is a binary representation, it requires rounding the number of bits or its hexadecimal representation.
Well, let's solve the problem, adding an exotic suggestion... The aim here is to return a float type in another overloaded function,   ROUND(float, text, int) RETURNS float The text is to offer a choice between
'dec' for "decimal representation",
'bin' for "binary" representation and
'hex' for hexadecimal representation.
So, in different representations we have a different interpretation about the number of digits to be rounded. Rounding a number x with an approximate shorter value, with less "fractionary digits" (tham its original d digits), will be shorter when d is couting binary digits instead decimal or hexadecimal.
It is not easy without C++, using "pure SQL", but this code snippets will illustrate and can be used as workaround:
-- Looking for a round_bin() function! this is only a workaround:
CREATE FUNCTION trunc_bin(x bigint, t int) RETURNS bigint AS $f$
SELECT ((x::bit(64) >> t) << t)::bigint;
$f$ language SQL IMMUTABLE;
CREATE FUNCTION ROUND(
x float,
xtype text, -- 'bin', 'dec' or 'hex'
xdigits int DEFAULT 0
)
RETURNS FLOAT AS $f$
SELECT CASE
WHEN xtype NOT IN ('dec','bin','hex') THEN 'NaN'::float
WHEN xdigits=0 THEN ROUND(x)
WHEN xtype='dec' THEN ROUND(x::numeric,xdigits)
ELSE (s1 ||'.'|| s2)::float
END
FROM (
SELECT s1,
lpad(
trunc_bin( s2::bigint, CASE WHEN xd<bin_bits THEN bin_bits - xd ELSE 0 END )::text,
l2,
'0'
) AS s2
FROM (
SELECT *,
(floor( log(2,s2::numeric) ) +1)::int AS bin_bits, -- most significant bit position
CASE WHEN xtype='hex' THEN xdigits*4 ELSE xdigits END AS xd
FROM (
SELECT s[1] AS s1, s[2] AS s2, length(s[2]) AS l2
FROM (SELECT regexp_split_to_array(x::text,'\.')) t1a(s)
) t1b
) t1c
) t2
$f$ language SQL IMMUTABLE;
Try
SELECT round(1/3.,'dec',4); -- 0.3333 float!
SELECT round(2.8+1/3.,'dec',1); -- 3.1 float!
SELECT round(2.8+1/3.,'dec'); -- ERROR, need to cast string
SELECT round(2.8+1/3.,'dec'::text); -- 3 float
SELECT round(2.8+1/3.,'dec',0); -- 3 float
SELECT round(2.8+1/3.,'hex',0); -- 3 float (no change)
SELECT round(2.8+1/3.,'hex',1); -- 3.1266
SELECT round(2.8+1/3.,'hex',3); -- 3.13331578486784
SELECT round(2.8+1/3.,'bin',1); -- 3.1125899906842625
SELECT round(2.8+1/3.,'bin',6); -- 3.1301821767286784
SELECT round(2.8+1/3.,'bin',12); -- 3.13331578486784
And \df round have also:
Schema | Name | Result | Argument
------------+-------+---------+---------------
myschema | round | float | x float, xtype text, xdigits int DEFAULT 0
Try with this:
SELECT to_char (2/3::float, 'FM999999990.00');
-- RESULT: 0.67
Or simply:
SELECT round (2/3::DECIMAL, 2)::TEXT
-- RESULT: 0.67
you can use the function below
SELECT TRUNC(14.568,2);
the result will show :
14.56
you can also cast your variable to the desire type :
SELECT TRUNC(YOUR_VAR::numeric,2)
SELECT ROUND(SUM(amount)::numeric, 2) AS total_amount
FROM transactions
Gives: 200234.08
Try casting your column to a numeric like:
SELECT ROUND(cast(some_column as numeric),2) FROM table
According to Bryan's response you can do this to limit decimals in a query. I convert from km/h to m/s and display it in dygraphs but when I did it in dygraphs it looked weird. Looks fine when doing the calculation in the query instead. This is on postgresql 9.5.1.
select date,(wind_speed/3.6)::numeric(7,1) from readings;
Error:function round(double precision, integer) does not exist
Solution: You need to addtype cast then it will work
Ex: round(extract(second from job_end_time_t)::integer,0)