Oracle SQL

Tag Archives: pipelined functions

“Collection iterator pickler fetch”: pipelined vs simple table functions

Posted on by Posted in oracle, PL/SQL, PL/SQL optimization, query optimizing, SQL, troubleshooting 2 Comments

Alex R recently discovered interesting thing: in SQL pipelined functions work much faster than simple non-pipelined table functions, so if you already have simple non-pipelined table function and want to get its results in sql (select * from table(fff)), it’s much better to create another pipelined function which will get and return its results through PIPE ROW().

A bit more details:

Assume we need to return collection “RESULT” from PL/SQL function into SQL query “select * from table(function_F(…))”.
If we create 2 similar functions: pipelined f_pipe and simple non-pipelined f_non_pipe, 

create or replace function f_pipe(n int) return tt_id_value pipelined 
as
  result tt_id_value;
begin
  ...
  for i in 1..n loop
    pipe row (result(i));
  end loop;
end f_pipe;
/
create or replace function f_non_pipe(n int) return tt_id_value 
as
  result tt_id_value;
begin
  ...
  return result;
end f_non_pipe;
/
Full functions definitions 
create or replace type to_id_value as object (id int, value int)
/
create or replace type tt_id_value as table of to_id_value
/
create or replace function f_pipe(n int) return tt_id_value pipelined 
as
  result tt_id_value;
  
  procedure gen is
  begin
     result:=tt_id_value();
     result.extend(n);
     for i in 1..n loop
        result(i):=to_id_value(i, 1);
     end loop;
  end;    
begin
  gen();
  for i in 1..n loop
    pipe row (result(i));
  end loop;
end f_pipe;
/
create or replace function f_non_pipe(n int) return tt_id_value 
as
  result tt_id_value;
  
  procedure gen is
  begin
     result:=tt_id_value();
     result.extend(n);
     for i in 1..n loop
        result(i):=to_id_value(i, 1);
     end loop;
  end;    
begin
  gen();
  return result;
end f_non_pipe;
/
create or replace function f_pipe_for_nonpipe(n int) return tt_id_value pipelined 
as
  result tt_id_value;
begin
  result:=f_non_pipe(n);
  for i in 1..result.count loop
    pipe row (result(i));
  end loop;
end;
/
create or replace function f_udf_pipe(n int) return tt_id_value pipelined 
as
  result tt_id_value;
  
  procedure gen is
  begin
     result:=tt_id_value();
     result.extend(n);
     for i in 1..n loop
        result(i):=to_id_value(i, 1);
     end loop;
  end;    
begin
  gen();
  for i in 1..n loop
    pipe row (result(i));
  end loop;
end;
/
create or replace function f_udf_non_pipe(n int) return tt_id_value 
as
  result tt_id_value;
  
  procedure gen is
  begin
     result:=tt_id_value();
     result.extend(n);
     for i in 1..n loop
        result(i):=to_id_value(i, 1);
     end loop;
  end;    
begin
  gen();
  return result;
end;
/

[collapse]
Test queries 

set echo on feed only timing on;
--alter session set optimizer_adaptive_plans=false;
--alter session set "_optimizer_use_feedback"=false;

select sum(id * value) s from table(f_pipe(&1));
select sum(id * value) s from table(f_non_pipe(&1));
select sum(id * value) s from table(f_pipe_for_nonpipe(&1));
select sum(id * value) s from table(f_udf_pipe(&1));
select sum(id * value) s from table(f_udf_non_pipe(&1));
with function f_inline_non_pipe(n int) return tt_id_value 
as
  result tt_id_value;
begin
     result:=tt_id_value();
     result.extend(n);
     for i in 1..n loop
        result(i):=to_id_value(i, 1);
     end loop;
     return result;
end;
select sum(id * value) s from table(f_inline_non_pipe(&1));
/
set timing off echo off feed on;

[collapse]

we’ll find that the function with simple “return result” works at least twice slower than pipelined function:

Function 1 000 000 elements 100 000 elements
F_PIPE 2.46 0.20
F_NON_PIPE 4.39 0.44
F_PIPE_FOR_NONPIPE 2.61 0.26
F_UDF_PIPE 2.06 0.20
F_UDF_NON_PIPE 4.46 0.44

I was really surprised that even “COLLECTION ITERATOR PICKLER FETCH” with F_PIPE_FOR_NONPIPE that gets result of F_NON_PIPE and returns it through PIPE ROW() works almost twice faster than F_NON_PIPE, so I decided to analyze it using stapflame by Frits Hoogland.

I added “dbms_lock.sleep(1)” into both of these function after collection generation, to compare the difference only between “pipe row” in loop and “return result”:

Modified functions 

create or replace function f_pipe(n int) return tt_id_value pipelined 
as
  result tt_id_value;
  
  procedure gen is
  begin
     result:=tt_id_value();
     result.extend(n);
     for i in 1..n loop
        result(i):=to_id_value(i, 1);
     end loop;
  end;    
begin
  gen();
  dbms_lock.sleep(1);
  for i in 1..n loop
    pipe row (result(i));
  end loop;
end f_pipe;
/
create or replace function f_non_pipe(n int) return tt_id_value 
as
  result tt_id_value;
  
  procedure gen is
  begin
     result:=tt_id_value();
     result.extend(n);
     for i in 1..n loop
        result(i):=to_id_value(i, 1);
     end loop;
  end;    
begin
  gen();
  dbms_lock.sleep(1);
  return result;
end f_non_pipe;
/

[collapse]

And stapflame showed that almost all overhead was consumed by the function “kgmpoa_Assign_Out_Arguments”:

I don’t know what this function is doing exactly, but we can see that oracle assign collection a bit later.
From other functions in this stack(pmucpkl, kopp2isize, kopp2colsize, kopp2atsize(attribute?), kopuadt) I suspect that is some type of preprocessiong of return arguments.
What do you think about it?

Full stapflame output:
stapflame_nonpipe
stapflame_pipe