通过AMDP调用HANA的PAL函数
SAP预测分析库（SAP Predictive Analysis Library，PAL）是SAP HANA中的一项功能，它允许我们在SAP HANA SQLScript过程中执行分析算法。
基于ABAP的SAP应用可以调用PAL提供的功能，包含分类，回归，聚类，关联规则，社交网络分析，推荐系统等。通常使用AMDP来实现调用。
AMDP(ABAP-Managed Database Procedures)是一种在SAP HANA中进行ABAP开发时可以使用的代码优化模式，简而言之，它可以让开发者在ABAP中写HANA数据库存储过程。
本文链接：https://www.cnblogs.com/hhelibeb/p/12610644.html
英文原文：An example to call PAL Apriori via AMDP
示例
接下来用一个例子来展示如何使用PAL。这里用到的PAL函数是Apriori。
步骤一（可选） 熟悉使用SQLScript调用PAL函数
如果你已经熟悉PAL的HANA存储过程接口和它的调用，可以跳过这步。
通过HANA Studio连接HANA数据库，运行下面的脚本：
SET SCHEMA ZHAOJE; DROP TABLE PAL_APRIORI_PARAMETER_TBL; CREATE COLUMN TABLE PAL_APRIORI_PARAMETER_TBL ( “PARAM_NAME ” VARCHAR(100), “INT_VALUE” INTEGER, “DOUBLE_VALUE” DOUBLE, “STRING_VALUE” VARCHAR (100) ); INSERT INTO PAL_APRIORI_PARAMETER_TBL VALUES (‘MIN_SUPPORT’, null, 0.1, null); INSERT INTO PAL_APRIORI_PARAMETER_TBL VALUES (‘MIN_CONFIDENCE’, null, 0.3, null); INSERT INTO PAL_APRIORI_PARAMETER_TBL VALUES (‘MIN_LIFT’, null, 1.1, null); INSERT INTO PAL_APRIORI_PARAMETER_TBL VALUES (‘MAX_CONSEQUENT’, 1, null, null); INSERT INTO PAL_APRIORI_PARAMETER_TBL VALUES (‘PMML_EXPORT’, 1, null, null); DROP TABLE PAL_APRIORI_TRANS_TBL; CREATE COLUMN TABLE PAL_APRIORI_TRANS_TBL ( “CUSTOMER” INTEGER, “ITEM” VARCHAR(20) ); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (2, ‘item2’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (2, ‘item3’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (3, ‘item1’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (3, ‘item2’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (3, ‘item4’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (4, ‘item1’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (4, ‘item3’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (5, ‘item2’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (5, ‘item3’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (6, ‘item1’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (6, ‘item3’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (0, ‘item1’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (0, ‘item2’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (0, ‘item5’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (1, ‘item2’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (1, ‘item4’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (7, ‘item1’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (7, ‘item2’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (7, ‘item3’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (7, ‘item5’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (8, ‘item1’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (8, ‘item2’); INSERT INTO PAL_APRIORI_TRANS_TBL VALUES (8, ‘item3’); CALL _SYS_AFL.PAL_APRIORI(PAL_APRIORI_TRANS_TBL, PAL_APRIORI_PARAMETER_TBL, ?, ?);
你会看到下面的挖掘结果，
步骤二 写AMDP代码，调用PAL过程
下面是一个AMDP类例子，它调用了PAL Apriori过程。你可以在Eclipse里编辑自己的AMDP代码。
CLASS zcl_amdp_pal DEFINITION PUBLIC FINAL CREATE PUBLIC .PUBLIC SECTION. INTERFACES if_amdp_marker_hdb. TYPES: BEGIN OF ty_apdata, customer TYPE i, item TYPE c LENGTH 10, END OF ty_apdata, tt_apdata TYPE STANDARD TABLE OF ty_apdata, BEGIN OF ty_apparams, name TYPE c LENGTH 60, intargs TYPE i, doubleargs TYPE float, stringargs TYPE c LENGTH 100, END OF ty_apparams, tt_apparams TYPE STANDARD TABLE OF ty_apparams, ty_metric TYPE p LENGTH 5 DECIMALS 4, BEGIN OF ty_aprules, antecedent TYPE c LENGTH 20, consequent TYPE c LENGTH 10, support TYPE ty_metric, confidence TYPE ty_metric, lift TYPE ty_metric, END OF ty_aprules, tt_aprules TYPE STANDARD TABLE OF ty_aprules, BEGIN OF ty_appmml, row_index TYPE i, model_content TYPE c LENGTH 500, END OF ty_appmml, tt_appmml TYPE STANDARD TABLE OF ty_appmml. METHODS apriori_proc_call IMPORTING VALUE(it_vapdata) TYPE tt_apdata VALUE(it_apparams) TYPE tt_apparams EXPORTING VALUE(et_ap_rules) TYPE tt_aprules VALUE(et_ap_pmml) TYPE tt_appmml. PROTECTED SECTION. PRIVATE SECTION. ENDCLASS. CLASS zcl_amdp_pal IMPLEMENTATION. METHOD apriori_proc_call BY DATABASE PROCEDURE FOR HDB LANGUAGE SQLSCRIPT. CALL _SYS_AFL.PAL_APRIORI(:it_vapdata, :it_apparams, et_ap_rules, et_ap_pmml); ENDMETHOD. ENDCLASS.
步骤三 在ABAP程序中调用AMDP方法
示例报表代码如下，
REPORT zz_apriori_test. DATA: lt_data TYPE zcl_amdp_pal=>tt_apdata, ls_data LIKE LINE OF lt_data, lt_param TYPE zcl_amdp_pal=>tt_apparams, ls_param LIKE LINE OF lt_param, lt_rules TYPE zcl_amdp_pal=>tt_aprules, lt_pmml TYPE zcl_amdp_pal=>tt_appmml, lr_wrapper TYPE REF TO zcl_amdp_pal. ls_data-customer = 2. ls_data-item = 'item2'. APPEND ls_data TO lt_data. ls_data-customer = 2. ls_data-item = 'item3'. APPEND ls_data TO lt_data. ls_data-customer = 3. ls_data-item = 'item1'. APPEND ls_data TO lt_data. ls_data-customer = 3. ls_data-item = 'item2'. APPEND ls_data TO lt_data. ls_data-customer = 3. ls_data-item = 'item4'. APPEND ls_data TO lt_data. ls_data-customer = 4. ls_data-item = 'item1'. APPEND ls_data TO lt_data. ls_data-customer = 4. ls_data-item = 'item3'. APPEND ls_data TO lt_data. ls_data-customer = 5. ls_data-item = 'item2'. APPEND ls_data TO lt_data. ls_data-customer = 5. ls_data-item = 'item3'. APPEND ls_data TO lt_data. ls_data-customer = 6. ls_data-item = 'item1'. APPEND ls_data TO lt_data. ls_data-customer = 6. ls_data-item = 'item3'. APPEND ls_data TO lt_data. ls_data-customer = 0. ls_data-item = 'item1'. APPEND ls_data TO lt_data. ls_data-customer = 0. ls_data-item = 'item2'. APPEND ls_data TO lt_data. ls_data-customer = 0. ls_data-item = 'item5'. APPEND ls_data TO lt_data. ls_data-customer = 1. ls_data-item = 'item2'. APPEND ls_data TO lt_data. ls_data-customer = 1. ls_data-item = 'item4'. APPEND ls_data TO lt_data. ls_data-customer = 7. ls_data-item = 'item1'. APPEND ls_data TO lt_data. ls_data-customer = 7. ls_data-item = 'item2'. APPEND ls_data TO lt_data. ls_data-customer = 7. ls_data-item = 'item3'. APPEND ls_data TO lt_data. ls_data-customer = 7. ls_data-item = 'item5'. APPEND ls_data TO lt_data. ls_data-customer = 8. ls_data-item = 'item1'. APPEND ls_data TO lt_data. ls_data-customer = 8. ls_data-item = 'item2'. APPEND ls_data TO lt_data. ls_data-customer = 8. ls_data-item = 'item3'. APPEND ls_data TO lt_data. CLEAR ls_param. ls_param-name = 'THREAD_NUMBER'. ls_param-intargs = 2. APPEND ls_param TO lt_param. CLEAR ls_param. ls_param-name = 'MIN_SUPPORT'. ls_param-doubleargs = '0.1'. APPEND ls_param TO lt_param. CLEAR ls_param. ls_param-name = 'MIN_CONFIDENCE'. ls_param-doubleargs = '0.3'. APPEND ls_param TO lt_param. CLEAR ls_param. ls_param-name = 'MIN_LIFT'. ls_param-doubleargs = '1.1'. APPEND ls_param TO lt_param. CLEAR ls_param. ls_param-name = 'MAX_CONSEQUENT'. ls_param-intargs = 1. APPEND ls_param TO lt_param. CREATE OBJECT lr_wrapper. CALL METHOD lr_wrapper->apriori_proc_call EXPORTING it_vapdata = lt_data it_apparams = lt_param IMPORTING et_ap_rules = lt_rules et_ap_pmml = lt_pmml. TRY. cl_salv_table=>factory( IMPORTING r_salv_table = DATA(lr_table) CHANGING t_table = lt_rules ). DATA(lr_functions) = lr_table->get_functions( ). lr_functions->set_default( abap_true ). DATA(lr_columns) = lr_table->get_columns( ). DATA(lr_column_1) = lr_columns->get_column('ANTECEDENT'). lr_column_1->set_long_text('ANTECEDENT'). lr_column_1->set_medium_text('ANTECEDENT'). lr_column_1->set_short_text('ANTECEDENT'). DATA(lr_column_2) = lr_columns->get_column('CONSEQUENT'). lr_column_2->set_long_text('CONSEQUENT'). lr_column_2->set_medium_text('CONSEQUENT'). lr_column_2->set_short_text('CONSEQUENT'). DATA(lr_column_3) = lr_columns->get_column('SUPPORT'). lr_column_3->set_long_text('SUPPORT' ). lr_column_3->set_medium_text('SUPPORT'). lr_column_3->set_short_text('SUPPORT'). DATA(lr_column_4) = lr_columns->get_column('CONFIDENCE'). lr_column_4->set_long_text('CONFIDENCE'). lr_column_4->set_medium_text('CONFIDENCE'). lr_column_4->set_short_text('CONFIDENCE'). DATA(lr_column_5) = lr_columns->get_column('LIFT'). lr_column_5->set_long_text('LIFT'). lr_column_5->set_medium_text('LIFT'). lr_column_5->set_short_text('LIFT'). lr_table->display( ). CATCH cx_salv_msg. "#EC NO_HANDLER CATCH cx_salv_not_found. "#EC NO_HANDLER ENDTRY.
成功执行后，可以看到如下的执行结果：
可以在相关的应用中使用这些结果。
