SAP HANA Predictive Analysis Library (PAL)

Table Column Column Data Type Description Constraint
Models 1st column varchar or nvarchar GMM model.
Each row stores a
Gaussian distribution
model with the weight,
mean, and covariance
matrix as a JSON format.
The number of rows is
dependent on the
number of components
in GMM.
Example
Assume that:
●
●
●
DM_PAL is a schema belonging to USER1; and
USER1 has been assigned the AFLPM_CREATOR_ERASER_EXECUTE role; and
USER1 has been assigned the AFL__SYS_AFL_AFLPAL_EXECUTE or
AFL__SYS_AFL_AFLPAL_EXECUTE_WITH_GRANT_OPTION role.
Example 1
SET SCHEMA DM_PAL;
DROP TYPE PAL_GMM_DATA_T;
CREATE TYPE PAL_GMM_DATA_T AS TABLE (
ID INTEGER,
ATTRIBUTE1 DOUBLE,
ATTRIBUTE2 DOUBLE,
ATTRIBUTE3 varchar(100)
);
DROP TYPE PAL_GMM_INIT_T;
CREATE TYPE PAL_GMM_INIT_T AS TABLE (
ID INTEGER,
CLUSTERNUM INTEGER
);
DROP TYPE PAL_CONTROL_T;
CREATE TYPE PAL_CONTROL_T AS TABLE(
NAME VARCHAR(50),
INTARGS INTEGER,
DOUBLEARGS DOUBLE,
STRINGARGS VARCHAR(100)
);
DROP TYPE PAL_GMM_RESULTS_T;
CREATE TYPE PAL_GMM_RESULTS_T AS TABLE(
ID INTEGER,
RESULT INTEGER,
PROB0 DOUBLE,
PROB1 DOUBLE
);
DROP TYPE PAL_GMM_RESULTSMODEL_T;
CREATE TYPE PAL_GMM_RESULTSMODEL_T AS TABLE(
MIXTURE1 DOUBLE,
MIXTURE2 DOUBLE
);
DROP TABLE PAL_GMM_PDATA_TBL;
CREATE COLUMN TABLE PAL_GMM_PDATA_TBL (
"POSITION" INT,
"SCHEMA_NAME" NVARCHAR(256),
"TYPE_NAME" NVARCHAR(256),
"PARAMETER_TYPE" VARCHAR(7)
);
58 P U B L I C
SAP HANA Predictive Analysis Library (PAL)
PAL Functions