SAP HANA Predictive Analysis Library (PAL)

Name Data Type Default Value Description Dependency
SD Integer 1 Specifies the standard
deviation method.
Only valid when BIN­
NING_METHOD is 3.
Examples: 1 S.D.; 2
S.D.; 3 S.D.
Output Table
Table 312:
Table Column Column Data Type Description Constraint
Result 1st column Integer, bigint, varchar,
or nvarchar
ID
This must be the first
column.
2nd column Integer Bin index assigned
The value is from 1 to
BIN_NUMBER.
3rd column Integer or double Smoothed value
Binning Model (optional)
1st column Integer Binning model ID This must be the first
column.
2nd column
CLOB, varchar, or
Binning model saved
The table must be a
nvarchar
as JSON string
column table. The minimum
length of each
unit (row) is 5000.
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.
SET SCHEMA DM_PAL;
DROP TYPE PAL_BINNING_DATA_T ;
CREATE TYPE PAL_BINNING_DATA_T AS TABLE("ID" INT, "TEMPERATURE" DOUBLE) ;
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_BINNING_RESULT_T ;
CREATE TYPE PAL_BINNING_RESULT_T AS TABLE("ID" INT, "BIN_NUMBER" INT,
"PRE_RESULT" DOUBLE);
DROP TYPE PAL_BINNING_MODEL_T ;
CREATE TYPE PAL_BINNING_MODEL_T AS TABLE("ID" INT, "MODEL" VARCHAR (5000));
DROP TABLE PAL_BINNING_PDATA_TBL;
CREATE COLUMN TABLE PAL_BINNING_PDATA_TBL("POSITION" INT, "SCHEMA_NAME"
NVARCHAR(256), "TYPE_NAME" NVARCHAR(256), "PARAMETER_TYPE" VARCHAR(7));
INSERT INTO PAL_BINNING_PDATA_TBL VALUES (1,'DM_PAL', 'PAL_BINNING_DATA_T','IN');
INSERT INTO PAL_BINNING_PDATA_TBL VALUES (2,'DM_PAL', 'PAL_CONTROL_T','IN');
SAP HANA Predictive Analysis Library (PAL)
PAL Functions P U B L I C 435