Scoring Functions inside the Teradata EDW

Scoring Function Names

The names of the scoring functions that are built in Teradata have the following format:
modelname_EM_outputvarname
modelname is the name that was specified in the MODELNAME argument of the %INDTD_PUBLISH_MODEL macro. modelname is always followed by _EM_ in the scoring function name. For more information about the MODELNAME argument, see Running the %INDTD_PUBLISH_MODEL Macro.
outputvarname is derived from the names of the EM_ output variables in the score.xml file that is generated from the SAS Enterprise Miner Score Code Export node. For more information about the score.xml file, see Fixed Variable Names.
One scoring function is created for each EM_ output variable in the score.xml file. For example, if the scoring model DATA step program takes ten inputs and creates three new variables, then three scoring functions are defined, each with the name of an output variable. For example, if you set MODELNAME=credit in the %INDTD_PUBLISH_MODEL macro, and the EM_ output variables are “EM_PREDICTION”, “EM_PROBABILITY”, and “EM_DECISION”, then the name of the scoring functions that are created would be “credit_EM_PREDICTION”, “credit_EM_PROBABILITY”, and “credit_EM_DECISION”.
Note: The scoring function name cannot exceed 30 characters.
CAUTION:
When the scoring function is generated, the names are case insensitive.
Consequently, if you have model names “Model01” and “model01”, and you create two scoring functions, the second scoring function overwrites the first scoring function.

Using the Scoring Functions

The scoring functions are available to use in any SQL expression in the same way that Teradata built-in functions are used. For an example, see Model Publishing Example.
There are four ways to see the scoring functions that are created:
  • From Teradata, log on to the database using a client tool such as BTEQ and submit an SQL statement. The following example assumes that the model name that you used to create the scoring functions is mymodel.
    bteq .logon myserver/myuserid,mypassword;
      select * from dbc.tables where tablename like '%mymodel%';
  • From SAS, use SQL procedure code that produces output in the LST file. The following example assumes that the model name that you used to create the scoring functions is mymodel.
    proc sql noerrorstop;
      connect to teradata (user=user password=pass server=server);
      select *
         from connection to teradata
         (select tablename,tablekind,databasename,LastALterTimeStamp
          from dbc.tables where
          databasename='sas' and tablename like '%mymodel%'
          and tablekind='F');
    
    disconnect teradata;
    quit;
    
    You can also use the SASTRACE and SASTRACELOC system options to generate tracing information. For more information about these system options, see the SAS System Options: Reference.
  • Look at the SampleSQL.txt file that is produced when the %INDTD_PUBLISH_MODEL macro is successfully run. This file can be found in the output directory (OUTDIR argument) that you specify in the macro.
    The SampleSQL.txt file contains basic code that, with modifications, can be used to run your score code inside Teradata.
    For example, the SampleSQL.txt file refers to an ID column in allmush1_intab that is populated with a unique integer from 1 to n, with n being the number of rows in the table. The ID column uniquely identifies each row. You would replace the ID column with your own primary key column.
    Note: The function and table names must be fully qualified if the functions and tables are not in the same database.
    The following example assumes that the model name that you used to create the scoring functions is allmush1.
    drop table allmush1_outtab;
    create table allmush1_outtab(
     id integer
    ,"EM_CLASSIFICATION" varchar(33)
    ,"EM_EVENTPROBABILITY" float
    ,"EM_PROBABILITY" float
    );
    insert into allmush1_outtab(
     id
    ,"EM_CLASSIFICATION"
    ,"EM_EVENTPROBABILITY"
    ,"EM_PROBABILITY"
    )
    select id,
     allmush1_em_classification("BRUISES"
    ,"CAPCOLOR"
    ,"GILLCOLO"
    ,"GILLSIZE"
    ,"HABITAT"
    ,"ODOR"
    ,"POPULAT"
    ,"RINGNUMB"
    ,"RINGTYPE"
    ,"SPOREPC"
    ,"STALKCBR"
    ,"STALKROO"
    ,"STALKSAR"
    ,"STALKSHA"
    ,"VEILCOLO")
      as "EM_CLASSIFICATION",
     allmush1_em_eventprobability("BRUISES"
    ,"CAPCOLOR"
    ,"GILLCOLO"
    ,"GILLSIZE"
    ,"HABITAT"
    ,"ODOR"
    ,"POPULAT"
    ,"RINGNUMB"
    ,"RINGTYPE"
    ,"SPOREPC"
    ,"STALKCBR"
    ,"STALKROO"
    ,"STALKSAR"
    ,"STALKSHA"
    ,"VEILCOLO")
      as "EM_EVENTPROBABILITY",
     allmush1_em_probability("BRUISES"
    ,"CAPCOLOR"
    ,"GILLCOLO"
    ,"GILLSIZE"
    ,"HABITAT"
    ,"ODOR"
    ,"POPULAT"
    ,"RINGNUMB"
    ,"RINGTYPE"
    ,"SPOREPC"
    ,"STALKCBR"
    ,"STALKROO"
    ,"STALKSAR"
    ,"STALKSHA"
    ,"VEILCOLO")
      as "EM_PROBABILITY"
    from allmush1_intab ;
    
  • You can look at the SAS log. A message is printed to the SAS log that states whether a scoring function is successfully or not successfully created or replaced.