Hi Stefan,
Thanks once again to you and Sjoerd, you have both been extremely helpful!
I have more simple question about integration of the BAT function version.
When I add the scalar version to the SQL catalog I have something like this:
module udf;
command myudf(one:dbl,two:dbl):dbl
address myudf_scalar_function
comment "my udf";
and then in SQL:
create function myudf(one double,two double)
returns double external name udf.myudf;
If I have the BAT version registered in a MAL module like so:
module batudf;
command myudf(one:bat[:oid,:dbl],two[:oid,:dbl]):bat[:oid,:dbl]
address myudf_bat_function
comment "my udf";
should I also register the BAT version in the SQL catalog? It seems that the UDFBATfuse functions in the example are not added.
Does the SQL engine have another mechanism for finding the BAT version?
Best regards and thanks,
Alastair
________________________________________
From: users-list
Hi Stefan,
Thanks again for your advice, I am looking through the BATfuse example and attempting to extrapolate at the minute.
Is the BAT version automagically inserted by optimiser into the query plan?
Yes, indeed ;-)
In the BAT fuse example, are the tests related to tail ordering important or just a hint for future optimisations?
The latter.
I'm not sure if this would be useful for my application of a general floating point function to arbitrarily ordered input parameters.
Not necessarily, in particular if you only aggregate the result afterwards; hence, it should be safe to simple indicate that the result of your function is not (know to be) ordered.
I'm very new to BAT terminology and BATs in general. Is it safe for me to assume the head is dense, sorted and the seqbase is the same as the input?
Yes. In fact, dense (and thus unique and sorted) is nowadays the only option for BAT heads. And if, as in your case, the results BAT has exactly one tuple ("BUN") for each input tuple, then also the dense head of the result should (in fact must) have the same seqbase as the dense head of the input.
I guess that these BAT functions are called from the outputs of "group by" in order to calculate the SUM aggregate for each group?
Almost: the result of your function is use together with the result of a group-by function to then calculate the aggregates for group. Stefan
Best regards and thanks,
Alastair
________________________________________ From: users-list
on behalf of Stefan Manegold Sent: 10 December 2013 19:18 To: Communication channel for MonetDB users Subject: Re: Inline function much faster than UDF in C? Hi Alastair,
please be aware that your function is not an aggregate by itself. Rather, you aggregate (via standard SUM()) over the result of your function.
For documentation and exmaples of how to implement scalar and bulk versions of UDFs, please see http://dev.monetdb.org/hg/MonetDB/file/tip/sql/backends/monet5/UDF/
Best, Stefan
----- Original Message -----
Hi Sjoerd,
Thanks for your response. I think you are almost certainly right about the slow loop in MAL. I hope that operating in bulk also means I create an implementation using all available SIMD lanes.
Are there any examples in the source of implementing a bulk version of this type of aggregate that I could use as a guide?
Best regards,
Alastair
________________________________________ From: users-list
on behalf of Sjoerd Mullender Sent: 09 December 2013 13:08 To: users-list@monetdb.org Subject: Re: Inline function much faster than UDF in C? -----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1
To get the most out of a C implementation, you need both a scalar version (one value at the time), and a bulk version (complete BATs as input). If you only have the former, the code generator will generate a slow loop in MAL calling the scalar function. And then it is very well possible that the bulk versions of the inline expression in your second attempt is a lot faster.
On 2013-12-09 13:47, Alastair McKinley wrote:
Hi everyone,
I have only been using MonetDB for a few weeks now and I have come across a very unexpected result when using User Defined Functions in C.
I have a query which does essentially this:
TABLE small_table ( int col1; float p; );
TABLE big_table ( int col1; int col2; float p; );
SELECT col1,1+SUM(MY_FUNCTION(big.p,small.p)) FROM small_table small inner join big_table big on big.col2 == small.col1 group by big.col1;
My function is f(x,y) = 0.7213*(x*ln(x/x+y) + y*ln(y/x+y))
I wrote an optimised version of this function using sse intrinsics in C and compiled it into MonetDB.
To my surprise, I discovered that writing this function inline in the query like so:
1+SUM(0.7213475*(big.p*LOG(big.p/(big.p+small.p))+small.p*LOG(small.p/(big.p+small.p))))
is a lot faster!
The query takes approx 2 seconds with the C version and less than 0.5 seconds with the inline version in SQL!
Can anyone explain this strange result?
Best regards,
Alastair
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