SAP HANA Predictive Analysis Library (PAL)

"STRINGARGS" VARCHAR(100)
);
--create procedure
DROP TABLE PAL_CDT_PDATA_TBL;
CREATE COLUMN TABLE PAL_CDT_PDATA_TBL(
"POSITION" INT,
"SCHEMA_NAME" NVARCHAR(256),
"TYPE_NAME" NVARCHAR(256),
"PARAMETER_TYPE" VARCHAR(7)
);
INSERT INTO PAL_CDT_PDATA_TBL VALUES (1, 'DM_PAL', 'PAL_CDT_DATA_T', 'IN');
INSERT INTO PAL_CDT_PDATA_TBL VALUES (2, 'DM_PAL', 'PAL_CONTROL_T', 'IN');
INSERT INTO PAL_CDT_PDATA_TBL VALUES (3, 'DM_PAL', 'PAL_CDT_JSONMODEL_T', 'OUT');
INSERT INTO PAL_CDT_PDATA_TBL VALUES (4, 'DM_PAL', 'PAL_CDT_PMMLMODEL_T', 'OUT');
CALL SYS.AFLLANG_WRAPPER_PROCEDURE_DROP('DM_PAL', 'PAL_CREATEDT_PROC');
CALL SYS.AFLLANG_WRAPPER_PROCEDURE_CREATE('AFLPAL', 'CREATEDT', 'DM_PAL',
'PAL_CREATEDT_PROC', PAL_CDT_PDATA_TBL);
DROP TABLE PAL_CDT_TRAINING_TBL;
CREATE COLUMN TABLE PAL_CDT_TRAINING_TBL(
"REGION" VARCHAR(50),
"SALESPERIOD" VARCHAR(50),
"REVENUE" Double,
"CLASSLABEL" VARCHAR(50)
);
DROP TABLE #PAL_CONTROL_TBL;
CREATE LOCAL TEMPORARY COLUMN TABLE #PAL_CONTROL_TBL(
"NAME" VARCHAR(100),
"INTARGS" INTEGER,
"DOUBLEARGS" DOUBLE,
"STRINGARGS" VARCHAR(100)
);
INSERT INTO #PAL_CONTROL_TBL VALUES ('PERCENTAGE', NULL, 1.0, NULL);
INSERT INTO #PAL_CONTROL_TBL VALUES ('THREAD_NUMBER', 2, NULL, NULL);
INSERT INTO #PAL_CONTROL_TBL VALUES ('IS_SPLIT_MODEL', 1, NULL, NULL);
INSERT INTO #PAL_CONTROL_TBL VALUES ('PMML_EXPORT', 2, NULL, NULL);
DROP TABLE PAL_CDT_JSONMODEL_TBL;
CREATE COLUMN TABLE PAL_CDT_JSONMODEL_TBL LIKE PAL_CDT_JSONMODEL_T;
DROP TABLE PAL_CDT_PMMLMODEL_TBL;
CREATE COLUMN TABLE PAL_CDT_PMMLMODEL_TBL LIKE PAL_CDT_PMMLMODEL_T;
CALL DM_PAL.PAL_CREATEDT_PROC(PAL_KMEANS_RESULT_TBL, "#PAL_CONTROL_TBL",
PAL_CDT_JSONMODEL_TBL, PAL_CDT_PMMLMODEL_TBL) WITH OVERVIEW;
SELECT * FROM PAL_CDT_JSONMODEL_TBL;
SELECT * FROM PAL_CDT_PMMLMODEL_TBL;
Step 3
Use the above tree model to map each new customer to the corresponding level he or she belongs to.
SET SCHEMA DM_PAL;
DROP TYPE PAL_PCDT_DATA_T;
CREATE TYPE PAL_PCDT_DATA_T AS TABLE(
"ID" INT,
"AGE" DOUBLE,
"INCOME" DOUBLE
);
DROP TYPE PAL_PCDT_JSONMODEL_T;
CREATE TYPE PAL_PCDT_JSONMODEL_T AS TABLE(
"ID" INT,
"JSONMODEL" VARCHAR(5000)
);
DROP TYPE PAL_CONTROL_T;
CREATE TYPE PAL_CONTROL_T AS TABLE(
"NAME" VARCHAR (100),
"INTARGS" INTEGER,
"DOUBLEARGS" DOUBLE,
"STRINGARGS" VARCHAR (100)
);
SAP HANA Predictive Analysis Library (PAL)
End-to-End Scenarios P U B L I C 555