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‎tutorials/api-tools-postman-install/api-tools-postman-install.md‎

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@@ -70,3 +70,5 @@ you are now all set to move to your next tutorial.
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[ACCORDION-END]
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## Next Steps
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- [View all How-Tos](https://www.sap.com/developer/tutorial-navigator.tutorials.html?tag=tutorial:type/how-to)

‎tutorials/cp-hana-aa-movielens-01/cp-hana-aa-movielens-01.md‎

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tags: [ tutorial>beginner, products>sap-hana, products>sap-cloud-platform, topic>machine-learning ]
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---
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## Prerequisites
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## Prerequisites
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- **Proficiency:** Beginner
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## Details
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### You will learn
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### You will learn
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- How to create the relevant CDS artefacts to expose your flat files as CDS entities.
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@@ -284,7 +284,7 @@ By default, the ***Role Editor*** will open by default, but instead we will be u
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Instead, right click on the **`user.hdbrole`** item in the tree, and use the **Open With** > **Text Editor** menu.
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Now, paste the following content:
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Now, paste the following content:
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```JavaScript
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role public.aa.movielens.hdb::user extends catalog role "sap.pa.apl.base.roles::APL_EXECUTE", "AFLPM_CREATOR_ERASER_EXECUTE", "AFL__SYS_AFL_AFLPAL_EXECUTE"

‎tutorials/cp-hana-aa-movielens-02/cp-hana-aa-movielens-02.md‎

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tags: [ tutorial>beginner, products>sap-hana, products>sap-cloud-platform, topic>machine-learning ]
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---
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## Prerequisites
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## Prerequisites
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- **Proficiency:** Beginner
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## Details
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### You will learn
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### You will learn
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- Understand the basics about recommendation engines
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- Which statistics can help you better understand the structure of the dataset
@@ -128,10 +128,10 @@ The result should be:
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table name | row count
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-----------|-----------
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links | 9125
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movies | 9125
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ratings | 100004
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tags | 1296
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links | 9125
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movies | 9125
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ratings | 100004
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tags | 1296
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Here are a few conclusion we can make upfront:
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‎tutorials/cp-hana-aa-movielens-03/cp-hana-aa-movielens-03.md‎

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@@ -13,11 +13,11 @@ If you are using a different version of SAP HANA and the SAP HANA APL library, t
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For more details about the APL function, check the online <a href="https://help.sap.com/viewer/cb31bd99d09747089754a0ba75067ed2/3.1/en-US/9bf31268c57e4c079f0cbabd36f39640.html" target="new">documentation</a>.
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&nbsp;
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## Prerequisites
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## Prerequisites
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- **Proficiency:** Beginner
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## Details
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### You will learn
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### You will learn
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- How to use SAP HANA APL Recommendation algorithm from SAP HANA APL version 3.2
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@@ -63,50 +63,50 @@ However, the ***SAP HANA APL*** installation package includes a script where you
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Here is a quick code example with the direct technique:
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```
66-
-- --------------------------------------------------------------------------
67-
-- Create the table type for the dataset
68-
-- --------------------------------------------------------------------------
69-
drop type TRAINING_DATASET_T;
70-
create type TRAINING_DATASET_T as table ( .... );
71-
72-
-- --------------------------------------------------------------------------
73-
-- Create the AFL wrapper corresponding to the target APL function
74-
-- --------------------------------------------------------------------------
75-
DROP TABLE CREATE_MODEL_SIGNATURE;
76-
create column table CREATE_MODEL_SIGNATURE like PROCEDURE_SIGNATURE_T;
77-
78-
-- the signature is defined in the APL API documentation
79-
INSERT INTO CREATE_MODEL_SIGNATURE values (1, 'MYSCHEMA','FUNCTION_HEADER_T' , 'IN');
80-
INSERT INTO CREATE_MODEL_SIGNATURE values (2, 'MYSCHEMA','OPERATION_CONFIG_T' , 'IN');
81-
INSERT INTO CREATE_MODEL_SIGNATURE values (3, 'MYSCHEMA','TRAINING_DATASET_T' , 'IN');
82-
INSERT INTO CREATE_MODEL_SIGNATURE values (4, 'MYSCHEMA','MODEL_BIN_OID_T' , 'OUT');
83-
INSERT INTO CREATE_MODEL_SIGNATURE values (5, 'MYSCHEMA','VARIABLE_DESC_OID_T', 'OUT');
84-
85-
call SYS.AFLLANG_WRAPPER_PROCEDURE_DROP('MYSCHEMA','APLWRAPPER_CREATE_MODEL');
86-
call SYS.AFLLANG_WRAPPER_PROCEDURE_CREATE('APL_AREA','CREATE_MODEL','MYSCHEMA', 'APLWRAPPER_CREATE_MODEL', CREATE_MODEL_SIGNATURE);
87-
88-
-- --------------------------------------------------------------------------
89-
-- Create the input/output tables used as arguments for the APL function
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-- --------------------------------------------------------------------------
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DROP TABLE FUNCTION_HEADER;
92-
CREATE COLUMN TABLE FUNCTION_HEADER LIKE FUNCTION_HEADER_T;
93-
INSERT INTO FUNCTION_HEADER values ('key', 'value');
94-
95-
DROP TABLE OPERATION_CONFIG;
96-
CREATE COLUMN TABLE OPERATION_CONFIG LIKE OPERATION_CONFIG_T;
97-
INSERT INTO OPERATION_CONFIG values ('key', 'value');
98-
99-
DROP TABLE TRAINED_MODEL;
100-
CREATE COLUMN TABLE TRAINED_MODEL LIKE MODEL_BIN_OID_T;
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DROP TABLE VARIABLE_DESC;
103-
CREATE COLUMN TABLE VARIABLE_DESC LIKE VARIABLE_DESC_OID_T;
104-
105-
-- --------------------------------------------------------------------------
66+
-- --------------------------------------------------------------------------
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-- Create the table type for the dataset
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-- --------------------------------------------------------------------------
69+
drop type TRAINING_DATASET_T;
70+
create type TRAINING_DATASET_T as table ( .... );
71+
72+
-- --------------------------------------------------------------------------
73+
-- Create the AFL wrapper corresponding to the target APL function
74+
-- --------------------------------------------------------------------------
75+
DROP TABLE CREATE_MODEL_SIGNATURE;
76+
create column table CREATE_MODEL_SIGNATURE like PROCEDURE_SIGNATURE_T;
77+
78+
-- the signature is defined in the APL API documentation
79+
INSERT INTO CREATE_MODEL_SIGNATURE values (1, 'MYSCHEMA','FUNCTION_HEADER_T' , 'IN');
80+
INSERT INTO CREATE_MODEL_SIGNATURE values (2, 'MYSCHEMA','OPERATION_CONFIG_T' , 'IN');
81+
INSERT INTO CREATE_MODEL_SIGNATURE values (3, 'MYSCHEMA','TRAINING_DATASET_T' , 'IN');
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INSERT INTO CREATE_MODEL_SIGNATURE values (4, 'MYSCHEMA','MODEL_BIN_OID_T' , 'OUT');
83+
INSERT INTO CREATE_MODEL_SIGNATURE values (5, 'MYSCHEMA','VARIABLE_DESC_OID_T', 'OUT');
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85+
call SYS.AFLLANG_WRAPPER_PROCEDURE_DROP('MYSCHEMA','APLWRAPPER_CREATE_MODEL');
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call SYS.AFLLANG_WRAPPER_PROCEDURE_CREATE('APL_AREA','CREATE_MODEL','MYSCHEMA', 'APLWRAPPER_CREATE_MODEL', CREATE_MODEL_SIGNATURE);
87+
88+
-- --------------------------------------------------------------------------
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-- Create the input/output tables used as arguments for the APL function
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-- --------------------------------------------------------------------------
91+
DROP TABLE FUNCTION_HEADER;
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CREATE COLUMN TABLE FUNCTION_HEADER LIKE FUNCTION_HEADER_T;
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INSERT INTO FUNCTION_HEADER values ('key', 'value');
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DROP TABLE OPERATION_CONFIG;
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CREATE COLUMN TABLE OPERATION_CONFIG LIKE OPERATION_CONFIG_T;
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INSERT INTO OPERATION_CONFIG values ('key', 'value');
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DROP TABLE TRAINED_MODEL;
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CREATE COLUMN TABLE TRAINED_MODEL LIKE MODEL_BIN_OID_T;
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102+
DROP TABLE VARIABLE_DESC;
103+
CREATE COLUMN TABLE VARIABLE_DESC LIKE VARIABLE_DESC_OID_T;
104+
105+
-- --------------------------------------------------------------------------
106106
-- Execute the APL function using its AFL wrapper and the actual input/output tables
107107
-- --------------------------------------------------------------------------
108108
call APLWRAPPER_CREATE_MODEL(FUNCTION_HEADER, OPERATION_CONFIG, MYSCHEMA.TRAINING_DATASET, TRAINED_MODEL, VARIABLE_DESC) with overview;
109-
```
109+
```
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111111
- **The procedure technique**:
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@@ -118,30 +118,30 @@ These APL stored procedures are part of the `HCO_PA_APL` delivery unit which is
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Here is a quick code example with the procedure technique:
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120120
```
121-
SET SESSION 'APL_CACHE_SCHEMA' = 'APL_CACHE';
121+
SET SESSION 'APL_CACHE_SCHEMA' = 'APL_CACHE';
122122
123-
-- --------------------------------------------------------------------------
124-
-- Create the input/output tables used as arguments for the APL function
125-
-- --------------------------------------------------------------------------
126-
DROP TABLE FUNCTION_HEADER;
123+
-- --------------------------------------------------------------------------
124+
-- Create the input/output tables used as arguments for the APL function
125+
-- --------------------------------------------------------------------------
126+
DROP TABLE FUNCTION_HEADER;
127127
CREATE COLUMN TABLE FUNCTION_HEADER LIKE "SAP_PA_APL"."sap.pa.apl.base::BASE.T.FUNCTION_HEADER";
128-
INSERT INTO FUNCTION_HEADER values ('key', 'value');
128+
INSERT INTO FUNCTION_HEADER values ('key', 'value');
129129
130-
DROP TABLE OPERATION_CONFIG;
131-
CREATE COLUMN TABLE OPERATION_CONFIG LIKE "SAP_PA_APL"."sap.pa.apl.base::BASE.T.OPERATION_CONFIG_DETAILED";
132-
INSERT INTO OPERATION_CONFIG values ('key', 'value');
130+
DROP TABLE OPERATION_CONFIG;
131+
CREATE COLUMN TABLE OPERATION_CONFIG LIKE "SAP_PA_APL"."sap.pa.apl.base::BASE.T.OPERATION_CONFIG_DETAILED";
132+
INSERT INTO OPERATION_CONFIG values ('key', 'value');
133133
134-
DROP TABLE TRAINED_MODEL;
135-
CREATE COLUMN TABLE TRAINED_MODEL LIKE "SAP_PA_APL"."sap.pa.apl.base::BASE.T.MODEL_BIN_OID";
134+
DROP TABLE TRAINED_MODEL;
135+
CREATE COLUMN TABLE TRAINED_MODEL LIKE "SAP_PA_APL"."sap.pa.apl.base::BASE.T.MODEL_BIN_OID";
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DROP TABLE VARIABLE_DESC;
138-
CREATE COLUMN TABLE VARIABLE_DESC LIKE "SAP_PA_APL"."sap.pa.apl.base::BASE.T.VARIABLE_DESC_OID";
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DROP TABLE VARIABLE_DESC;
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CREATE COLUMN TABLE VARIABLE_DESC LIKE "SAP_PA_APL"."sap.pa.apl.base::BASE.T.VARIABLE_DESC_OID";
139139
140-
-- --------------------------------------------------------------------------
140+
-- --------------------------------------------------------------------------
141141
-- Execute the APL function using its AFL wrapper and the actual input/output tables
142142
-- --------------------------------------------------------------------------
143-
call "SAP_PA_APL"."sap.pa.apl.base::CREATE_MODEL"(FUNCTION_HEADER, OPERATION_CONFIG, 'MYSCHEMA','TRAINING_DATASET', TRAINED_MODEL, VARIABLE_DESC) with overview;
144-
```
143+
call "SAP_PA_APL"."sap.pa.apl.base::CREATE_MODEL"(FUNCTION_HEADER, OPERATION_CONFIG, 'MYSCHEMA','TRAINING_DATASET', TRAINED_MODEL, VARIABLE_DESC) with overview;
144+
```
145145

146146
We will use the procedure technique in this tutorial.
147147

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396396
, "MOVIES"."TITLE"
397397
, "MOVIES"."GENRES"
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, "LINKS"."IMDBID"
399-
, "LINKS"."TMDBID"
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, "LINKS"."TMDBID"
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FROM (
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SELECT
402402
"T1"."USERID"
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544544
, "MOVIES"."TITLE"
545545
, "MOVIES"."GENRES"
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, "LINKS"."IMDBID"
547-
, "LINKS"."TMDBID"
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, "LINKS"."TMDBID"
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FROM (
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SELECT
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"T1"."MOVIEID"
@@ -610,7 +610,7 @@ Let's verify how many distinct movies will actually get recommended to a user (p
610610
```SQL
611611
SELECT
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COUNT(1) AS "MOVIE_COUNT"
613-
, COUNT(1) *100 / (SELECT COUNT(1) AS "COUNT" FROM "MOVIELENS"."public.aa.movielens.hdb::data.MOVIES" ) AS "MOVIE_RATIO"
613+
, COUNT(1) *100 / (SELECT COUNT(1) AS "COUNT" FROM "MOVIELENS"."public.aa.movielens.hdb::data.MOVIES" ) AS "MOVIE_RATIO"
614614
FROM (
615615
SELECT "MOVIEID"
616616
FROM "MOVIELENS"."APL_RECO_MODEL_ITEMS_RESULTS"

‎tutorials/cp-hana-aa-movielens-04/cp-hana-aa-movielens-04.md‎

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tags: [ tutorial>beginner, products>sap-hana, products>sap-cloud-platform, topic>machine-learning ]
77
---
88

9-
## Prerequisites
9+
## Prerequisites
1010
- **Proficiency:** Beginner
1111

1212
## Details
13-
### You will learn
13+
### You will learn
1414

1515
- How to use SAP HANA PAL APRIORI algorithm from SAP HANA 1.0 SPS12
1616

@@ -73,16 +73,16 @@ Once the AFL wrapper is generated, it can be invoked through a call statement.
7373
Here is a quick code example:
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7575
```
76-
-- --------------------------------------------------------------------------
77-
-- Create the table type for the dataset
78-
-- --------------------------------------------------------------------------
76+
-- --------------------------------------------------------------------------
77+
-- Create the table type for the dataset
78+
-- --------------------------------------------------------------------------
7979
DROP TYPE TRAINING_DATASET_T;
8080
-- the training dataset definition
81-
CREATE TYPE TRAINING_DATASET_T AS TABLE( .... );
81+
CREATE TYPE TRAINING_DATASET_T AS TABLE( .... );
8282
83-
-- --------------------------------------------------------------------------
84-
-- Create the AFL wrapper corresponding to the target APL function
85-
-- --------------------------------------------------------------------------
83+
-- --------------------------------------------------------------------------
84+
-- Create the AFL wrapper corresponding to the target APL function
85+
-- --------------------------------------------------------------------------
8686
DROP TYPE PROCEDURE_SIGNATURE_T;
8787
CREATE TYPE PROCEDURE_SIGNATURE_T AS TABLE(
8888
"NAME" VARCHAR (50),
@@ -95,7 +95,7 @@ DROP TYPE TRAINED_MODEL_T;
9595
CREATE TYPE TRAINED_MODEL_T AS TABLE(
9696
"NAME" VARCHAR (50),
9797
"VALUE" VARCHAR (5000)
98-
);
98+
);
9999
DROP TABLE OPERATION_CONFIG;
100100
101101
DROP TYPE OPERATION_CONFIG_T;
@@ -104,22 +104,22 @@ CREATE TYPE OPERATION_CONFIG_T AS TABLE(
104104
"VALUE" VARCHAR (5000)
105105
);
106106
107-
-- --------------------------------------------------------------------------
108-
-- Create the AFL wrapper corresponding to the target PAL function
109-
-- --------------------------------------------------------------------------
110-
DROP TABLE CREATE_MODEL_SIGNATURE;
111-
CREATE COLUMN TABLE CREATE_MODEL_SIGNATURE like PROCEDURE_SIGNATURE_T;
112-
-- the signature is defined in the PAL API documentation
107+
-- --------------------------------------------------------------------------
108+
-- Create the AFL wrapper corresponding to the target PAL function
109+
-- --------------------------------------------------------------------------
110+
DROP TABLE CREATE_MODEL_SIGNATURE;
111+
CREATE COLUMN TABLE CREATE_MODEL_SIGNATURE like PROCEDURE_SIGNATURE_T;
112+
-- the signature is defined in the PAL API documentation
113113
INSERT INTO CREATE_MODEL_SIGNATURE VALUES (1,'MYSCHEMA', 'TRAINING_DATASET_T' ,'IN');
114114
INSERT INTO CREATE_MODEL_SIGNATURE VALUES (2,'MYSCHEMA', 'OPERATION_CONFIG_T' ,'IN');
115-
INSERT INTO CREATE_MODEL_SIGNATURE VALUES (3,'MYSCHEMA', 'TRAINED_MODEL_T' ,'OUT');
115+
INSERT INTO CREATE_MODEL_SIGNATURE VALUES (3,'MYSCHEMA', 'TRAINED_MODEL_T' ,'OUT');
116116
117-
call SYS.AFLLANG_WRAPPER_PROCEDURE_DROP('MYSCHEMA','APLWRAPPER_CREATE_MODEL');
117+
call SYS.AFLLANG_WRAPPER_PROCEDURE_DROP('MYSCHEMA','APLWRAPPER_CREATE_MODEL');
118118
call SYS.AFLLANG_WRAPPER_PROCEDURE_CREATE('AFLPAL','ARIMATRAIN','MYSCHEMA', 'APLWRAPPER_CREATE_MODEL', "CREATE_MODEL_SIGNATURE");
119119
120-
DROP TABLE OPERATION_CONFIG;
120+
DROP TABLE OPERATION_CONFIG;
121121
CREATE COLUMN TABLE OPERATION_CONFIG like OPERATION_CONFIG_T;
122-
-- the function configuration is defined in the PAL API documentation
122+
-- the function configuration is defined in the PAL API documentation
123123
INSERT INTO OPERATION_CONFIG VALUES ('P', 1,null,null);
124124
INSERT INTO OPERATION_CONFIG VALUES ('Q', 1,null,null);
125125
INSERT INTO OPERATION_CONFIG VALUES ('D', 0,null,null);
@@ -130,7 +130,7 @@ DROP TABLE TRAINED_MODEL;
130130
CREATE COLUMN TABLE TRAINED_MODEL LIKE TRAINED_MODEL_T;
131131
132132
CALL APLWRAPPER_CREATE_MODEL("TRAINING_DATASET", "OPERATION_CONFIG");
133-
```
133+
```
134134

135135
For more information please refer to the online <a href="https://help.sap.com/viewer/2cfbc5cf2bc14f028cfbe2a2bba60a50/1.0.12/en-US" target="new">documentation</a>..
136136

@@ -368,7 +368,7 @@ Let's verify how many distinct movies will actually get recommended to a user (p
368368
```SQL
369369
SELECT
370370
COUNT(1) AS "MOVIE_COUNT"
371-
, COUNT(1) *100 / (SELECT COUNT(1) AS "COUNT" FROM "MOVIELENS"."public.aa.movielens.hdb::data.MOVIES" ) AS "MOVIE_RATIO"
371+
, COUNT(1) *100 / (SELECT COUNT(1) AS "COUNT" FROM "MOVIELENS"."public.aa.movielens.hdb::data.MOVIES" ) AS "MOVIE_RATIO"
372372
FROM (
373373
SELECT "MOVIEID"
374374
FROM "MOVIELENS"."PAL_APRIORI_MODEL_USERS_RESULTS"
@@ -381,7 +381,7 @@ Let's verify how many distinct movies will potentially get recommended to a user
381381
```SQL
382382
SELECT
383383
COUNT(1) AS "MOVIE_COUNT"
384-
, COUNT(1) *100 / (SELECT COUNT(1) AS "COUNT" FROM "MOVIELENS"."public.aa.movielens.hdb::data.MOVIES" ) AS "MOVIE_RATIO"
384+
, COUNT(1) *100 / (SELECT COUNT(1) AS "COUNT" FROM "MOVIELENS"."public.aa.movielens.hdb::data.MOVIES" ) AS "MOVIE_RATIO"
385385
FROM (
386386
SELECT "PRERULE" AS "MOVIEID"
387387
FROM "MOVIELENS"."PAL_APRIORI_RESULT"
@@ -425,7 +425,7 @@ FROM (
425425
, "MOVIES"."TITLE"
426426
, "MOVIES"."GENRES"
427427
, "LINKS"."IMDBID"
428-
, "LINKS"."TMDBID"
428+
, "LINKS"."TMDBID"
429429
FROM (
430430
SELECT "MOVIEID", "RULES"."POSTRULE" AS "CONSEQUENT", "RULES"."CONFIDENCE" AS "SCORE"
431431
FROM "MOVIELENS"."public.aa.movielens.hdb::data.MOVIES" AS INPUT_DATA
@@ -463,7 +463,7 @@ Let's verify how many distinct movies will actually get recommended to a user (p
463463
```SQL
464464
SELECT
465465
COUNT(1) AS "MOVIE_COUNT"
466-
, COUNT(1) *100 / (SELECT COUNT(1) AS "COUNT" FROM "MOVIELENS"."public.aa.movielens.hdb::data.MOVIES" ) AS "MOVIE_RATIO"
466+
, COUNT(1) *100 / (SELECT COUNT(1) AS "COUNT" FROM "MOVIELENS"."public.aa.movielens.hdb::data.MOVIES" ) AS "MOVIE_RATIO"
467467
FROM (
468468
SELECT "MOVIEID"
469469
FROM "MOVIELENS"."PAL_APRIORI_MODEL_ITEMS_RESULTS"

‎tutorials/cp-hana-aa-movielens-05/cp-hana-aa-movielens-05.md‎

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tags: [ tutorial>beginner, products>sap-hana, products>sap-cloud-platform, topic>machine-learning ]
77
---
88

9-
## Prerequisites
9+
## Prerequisites
1010
- **Proficiency:** Beginner
1111

1212
## Details
13-
### You will learn
13+
### You will learn
1414

1515
- How to setup your SAP HANA XS OData service to be used in your SAPUI5 application
1616

@@ -68,7 +68,7 @@ SELECT DISTINCT
6868
, "T2". "TITLE"
6969
, "T2". "GENRES"
7070
, "T3". "IMDBID"
71-
, "T3". "TMDBID"
71+
, "T3". "TMDBID"
7272
, COUNT(1) over( PARTITION BY "T1"."MOVIEID" ) AS "RATING_COUNT"
7373
, AVG("RATING") over( PARTITION BY "T1"."MOVIEID" ) AS "RATING_AVG"
7474
, NTH_VALUE("TIMESTAMP",1) over( PARTITION BY "T1"."MOVIEID" ORDER BY "T1"."TIMESTAMP" DESC, "T1"."MOVIEID") AS "LAST_RATING_DATE"
@@ -91,8 +91,8 @@ SELECT
9191
, "T2"."TITLE"
9292
, "T2"."GENRES"
9393
, "T3"."IMDBID"
94-
, "T3"."TMDBID"
95-
, "T1"."RATING"
94+
, "T3"."TMDBID"
95+
, "T1"."RATING"
9696
, "T1"."TIMESTAMP"
9797
FROM "MOVIELENS"."public.aa.movielens.hdb::data.RATINGS" "T1"
9898
LEFT OUTER JOIN "MOVIELENS"."public.aa.movielens.hdb::data.MOVIES" "T2" on ("T1".MOVIEID = "T2".MOVIEID)

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