SAP HANA Predictive Analysis Library (PAL)

INSERT INTO PAL_DISTRRANDOM_PDATA_TBL VALUES
(3,'DM_PAL','PAL_DISTRRANDOM_RESULT_T', 'OUT');
call SYS.AFLLANG_WRAPPER_PROCEDURE_DROP('DM_PAL','PAL_DISTRRANDOM_PROC');
call SYS.AFLLANG_WRAPPER_PROCEDURE_CREATE('AFLPAL','DISTRRANDOM',
'DM_PAL','PAL_DISTRRANDOM_PROC', PAL_DISTRRANDOM_PDATA_TBL);
DROP TABLE PAL_DISTRRANDOM_DISTRPARAM_TBL;
CREATE COLUMN TABLE PAL_DISTRRANDOM_DISTRPARAM_TBL LIKE
PAL_DISTRRANDOM_DISTRPARAM_T;
INSERT INTO PAL_DISTRRANDOM_DISTRPARAM_TBL VALUES ('DistributionName',
'UNIFORM');
INSERT INTO PAL_DISTRRANDOM_DISTRPARAM_TBL VALUES ('MIN', '2');
INSERT INTO PAL_DISTRRANDOM_DISTRPARAM_TBL VALUES ('MAX', '2.1');
DROP TABLE #PAL_CONTROL_TBL;
CREATE LOCAL TEMPORARY TABLE #PAL_CONTROL_TBL LIKE PAL_CONTROL_T;
INSERT INTO #PAL_CONTROL_TBL VALUES ('THREAD_NUMBER', 2, null, null);
INSERT INTO #PAL_CONTROL_TBL VALUES ('NUM_RANDOM', 10000, null, null);
INSERT INTO #PAL_CONTROL_TBL VALUES ('SEED', 0, null, null);
DROP TABLE PAL_DISTRRANDOM_RESULT_TBL;
CREATE COLUMN TABLE PAL_DISTRRANDOM_RESULT_TBL LIKE PAL_DISTRRANDOM_RESULT_T;
CALL DM_PAL.PAL_DISTRRANDOM_PROC(PAL_DISTRRANDOM_DISTRPARAM_TBL,
#PAL_CONTROL_TBL, PAL_DISTRRANDOM_RESULT_TBL) with overview;
SELECT * FROM PAL_DISTRRANDOM_RESULT_TBL;
Expected Result
3.6.9 Sampling
In business scenarios the number of records in the database is usually quite large, and it is common to use a
small portion of the records as representatives, so that a rough impression of the dataset can be given by
analyzing sampling.
This release of PAL provides eight sampling methods, including:
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First_N
Middle_N
Last_N
Every_N th
SimpleRandom_WithReplacement
SimpleRandom_WithoutReplacement
Systematic
Stratified
SAP HANA Predictive Analysis Library (PAL)
PAL Functions P U B L I C 469