SAP HANA Predictive Analysis Library (PAL)

CREATE TYPE PAL_CONTROL_T AS TABLE("NAME" VARCHAR(100), "INTARGS" INT,
"DOUBLEARGS" DOUBLE,"STRINGARGS" VARCHAR(100));
DROP TYPE PAL_FER_FITTED_T;
CREATE TYPE PAL_FER_FITTED_T AS TABLE("ID" INT,"Fitted" DOUBLE);
DROP table PAL_FER_PDATA_TBL;
CREATE column table PAL_FER_PDATA_TBL("POSITION" INT, "SCHEMA_NAME"
NVARCHAR(256), "TYPE_NAME" NVARCHAR(256), "PARAMETER_TYPE" VARCHAR(7));
insert into PAL_FER_PDATA_TBL values (1,'DM_PAL','PAL_FER_PREDICT_T','in');
insert into PAL_FER_PDATA_TBL values (2,'DM_PAL','PAL_FER_COEFFICIENT_T','in');
insert into PAL_FER_PDATA_TBL values (3,'DM_PAL','PAL_CONTROL_T','in');
insert into PAL_FER_PDATA_TBL values (4,'DM_PAL','PAL_FER_FITTED_T','out');
CALL SYS.AFLLANG_WRAPPER_PROCEDURE_DROP('DM_PAL','PAL_FORECAST_EXPR_PROC');
CALL
SYS.AFLLANG_WRAPPER_PROCEDURE_CREATE('AFLPAL','FORECASTWITHEXPR','DM_PAL','PAL_FO
RECAST_EXPR_PROC',PAL_FER_PDATA_TBL);
DROP TABLE #PAL_CONTROL_TBL;
CREATE LOCAL TEMPORARY COLUMN TABLE #PAL_CONTROL_TBL ("NAME" VARCHAR(100),
"INTARGS" INT, "DOUBLEARGS" DOUBLE,"STRINGARGS" VARCHAR(100));
INSERT INTO #PAL_CONTROL_TBL VALUES ('THREAD_NUMBER',8,null,null);
DROP TABLE PAL_FER_PREDICTDATA_TBL;
CREATE COLUMN TABLE PAL_FER_PREDICTDATA_TBL ("ID" INT,"X1" DOUBLE, "X2" DOUBLE);
INSERT INTO PAL_FER_PREDICTDATA_TBL VALUES (0,0.5,0.3);
INSERT INTO PAL_FER_PREDICTDATA_TBL VALUES (1,4,0.4);
INSERT INTO PAL_FER_PREDICTDATA_TBL VALUES (2,0,1.6);
INSERT INTO PAL_FER_PREDICTDATA_TBL VALUES (3,0.3,0.45);
INSERT INTO PAL_FER_PREDICTDATA_TBL VALUES (4,0.4,1.7);
DROP TABLE PAL_FER_COEEFICIENT_TBL;
CREATE COLUMN TABLE PAL_FER_COEEFICIENT_TBL ("ID" INT,"Ai" DOUBLE);
INSERT INTO PAL_FER_COEEFICIENT_TBL VALUES (0,1.7120914258645001);
INSERT INTO PAL_FER_COEEFICIENT_TBL VALUES (1,0.2652771198483208);
INSERT INTO PAL_FER_COEEFICIENT_TBL VALUES (2,-3.471103742302148);
DROP TABLE PAL_FER_FITTED_TBL;
CREATE COLUMN TABLE PAL_FER_FITTED_TBL ("ID" INT,"Fitted" DOUBLE);
CALL DM_PAL.PAL_FORECAST_EXPR_PROC(PAL_FER_PREDICTDATA_TBL,
PAL_FER_COEEFICIENT_TBL, "#PAL_CONTROL_TBL", PAL_FER_FITTED_TBL) with overview;
SELECT * FROM PAL_FER_FITTED_TBL;
Expected Result
PAL_FER_FITTED_TBL:
3.3.4 Multiple Linear Regression
Linear regression is an approach to modeling the linear relationship between a variable , usually referred
to as dependent variable, and one or more variables, usually referred to as independent variables, denoted as
predictor vector . In linear regression, data are modeled using linear functions, and unknown model
parameters are estimated from the data. Such models are called linear models.
264 P U B L I C
SAP HANA Predictive Analysis Library (PAL)
PAL Functions