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Processing large datasets

Hugo Mildenberger 
With PostgreSQL at least, R can also be used as implementation
language for stored procedures. Hence data transfers between 
processes can be avoided alltogether. 

   http://www.joeconway.com/plr/

Implemention of such a procedure in R appears to be straighforward:
 
   CREATE OR REPLACE FUNCTION overpaid (emp) RETURNS bool AS '
      if (200000 < arg1$salary) {
          return(TRUE)
      }
      if (arg1$age < 30 && 100000 < arg1$salary) {
          return(TRUE)
      }
      return(FALSE)
    ' LANGUAGE 'plr';

  CREATE TABLE emp (name text, age int, salary numeric(10,2));
    INSERT INTO emp VALUES ('Joe', 41, 250000.00);
    INSERT INTO emp VALUES ('Jim', 25, 120000.00);
    INSERT INTO emp VALUES ('Jon', 35, 50000.00);
 

  SELECT name, overpaid(emp) FROM emp;
   name | overpaid
    ------+----------
    Joe  | t
    Jim  | t
    Jon  | f
   (3 rows)


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On Wednesday 25 May 2011 14:12:23 Jonathan Daily wrote:

Thread (14 messages)

Roman Naumenko Processing large datasets May 24 Jonathan Daily Processing large datasets May 25 Roman Naumenko Processing large datasets May 25 Steve Lianoglou Processing large datasets May 25 Roman Naumenko Processing large datasets May 25 Marc Schwartz Processing large datasets May 25 Steve Lianoglou Processing large datasets May 25 Mike Marchywka Processing large datasets/ non answer but Q on writing data frame derivative. May 25 Mike Marchywka Processing large datasets May 25 gbrenes at ssc.wisc.edu the mgcv package can not be loaded May 25 Sarah Goslee the mgcv package can not be loaded May 25 Hugo Mildenberger Processing large datasets May 25 Steve Lianoglou Processing large datasets May 25 Mike Marchywka Processing large datasets May 25