SAP HANA Predictive Analysis Library (PAL)

INSERT INTO PAL_DISTRPROB_DATA_TBL VALUES (42);
DROP TABLE PAL_DISTRPROB_DISTRPARAM_TBL;
CREATE COLUMN TABLE PAL_DISTRPROB_DISTRPARAM_TBL LIKE PAL_DISTRPROB_DISTRPARAM_T;
INSERT INTO PAL_DISTRPROB_DISTRPARAM_TBL VALUES ('DistributionName', 'Weibull');
INSERT INTO PAL_DISTRPROB_DISTRPARAM_TBL VALUES ('Shape', '1.40528');
INSERT INTO PAL_DISTRPROB_DISTRPARAM_TBL VALUES ('Scale', '36.3069');
DROP TABLE #PAL_CONTROL_TBL;
CREATE LOCAL TEMPORARY COLUMN TABLE #PAL_CONTROL_TBL(
"NAME" VARCHAR (50),
"INTARGS" INTEGER,
"DOUBLEARGS" DOUBLE,
"STRINGARGS" VARCHAR (100)
);
INSERT INTO #PAL_CONTROL_TBL VALUES ('LOWER_UPPER',0,null,null);
DROP TABLE PAL_DISTRPROB_RESULT_TBL;
CREATE COLUMN TABLE PAL_DISTRPROB_RESULT_TBL LIKE PAL_DISTRPROB_RESULT_T;
CALL DM_PAL.PAL_DISTRPROB_PROC(PAL_DISTRPROB_DATA_TBL,
PAL_DISTRPROB_DISTRPARAM_TBL, #PAL_CONTROL_TBL, PAL_DISTRPROB_RESULT_TBL) WITH
OVERVIEW;
SELECT * FROM PAL_DISTRPROB_RESULT_TBL;
The expected result is as follows:
Step 4
Get the CDF (cumulative distribution function) of Weibull distribution for the control treatment data:
SET SCHEMA DM_PAL;
DROP TYPE PAL_DISTRPROB_DATA_T;
CREATE TYPE PAL_DISTRPROB_DATA_T AS TABLE("DATACOL" DOUBLE);
DROP TYPE PAL_DISTRPROB_DISTRPARAM_T;
CREATE TYPE PAL_DISTRPROB_DISTRPARAM_T AS TABLE(
"NAME" VARCHAR(50),
"VALUE" VARCHAR(50)
);
DROP TYPE PAL_DISTRPROB_RESULT_T;
CREATE TYPE PAL_DISTRPROB_RESULT_T AS TABLE(
"INPUTDATA" DOUBLE,
"PROBABILITY" DOUBLE
);
DROP TYPE PAL_CONTROL_T;
CREATE TYPE PAL_CONTROL_T AS TABLE(
"NAME" VARCHAR (50),
"INTARGS" INTEGER,
"DOUBLEARGS" DOUBLE,
"STRINGARGS" VARCHAR (100)
);
DROP TABLE PAL_DISTRPROB_PDATA_TBL;
CREATE COLUMN TABLE PAL_DISTRPROB_PDATA_TBL(
"POSITION" INT,
"SCHEMA_NAME" NVARCHAR(256),
"TYPE_NAME" NVARCHAR(256),
"PARAMETER_TYPE" VARCHAR(7)
574 P U B L I C
SAP HANA Predictive Analysis Library (PAL)
End-to-End Scenarios