SAPHANA学习（2）：SQL Functions（A）

3.11SQL Functions

/*11.SQL Functions*/

/*

1.ABAP_ALPHANUM

ABAP_ALPHANUM( <string>, <chars> )

<string>,如果是数字字符串，返回左边补0到<chars>位数的字符串，如果是混合数字字母字符串，返回unchanged

<chars>,返回字符串长度,如果<chars>大于原字符串长度，添加0；

*/

--ABAP_ALPHANUM，找不到？
--SELECT ABAP_ALPHANUM('12', 3) FROM DUMMY;
--SELECT ABAP_ALPHANUM('123', 2) FROM DUMMY;
--SELECT ABAP_ALPHANUM('12x', 13) FROM DUMMY;

/*

2.ABAP_NUMC

ABAP_NUMC( <string>, <chars> )

处理数字字符串，如果<chars>大于原字符串长度，左边补0，如果小于，从左边截取掉超出字符；

数字负号会被省略掉

*/

--ABAP_NUMC,找不到？
--SELECT ABAP_NUMC(12, 3) FROM DUMMY;
--SELECT ABAP_NUMC(1.2e13, 13) FROM DUMMY;
--SELECT ABAP_NUMC(-1234.5, 6) FROM DUMMY;

/*

3.ABAP_LOWER

ABAP_LOWER(<string>)

将字符串转换小写

4.ABAP_UPPER

ABAP_UPPER(<string>)

将字符串转换大写

*/

--ABAP_LOWER
SELECT ABAP_LOWER('ABC') FROM DUMMY;
--ABAP_UPPER
SELECT ABAP_UPPER('abc') FROM DUMMY;

/*

5.ABS Function

ABS(<num>)

绝对值

*/

--ABS
SELECT ABS(-1) FROM DUMMY;

/*

6.ACOS Function

ACOS(<num>)

获取反余弦值,y=arccos x x取值[-1,1],y=cosx的反函数

<num>取值-1~1

7.ASIN Function

ASIN(<number>)

反正弦函数y=arcsinx x=[-1,1]

8.ATAN Function

ATAN(<number>)

反正切函数y=arctanx x属于负无穷到正无穷

9.ATAN2 Function

ATAN2(<number1>, <number2>)

两个数之比的反正切值

*/

--ACOS
SELECT ACOS(-1) FROM DUMMY;
--ASIN
SELECT ASIN (0.5) FROM DUMMY;
--ATAN
SELECT ATAN (1000) FROM DUMMY;
--ATAN2
SELECT ATAN2 (100, 200) FROM DUMMY;

/*

10.ADD_DAYS Function

ADD_DAYS(<date>, <num_days>)

日期加上<num_days>

11.ADD_MONTHS Function

ADD_MONTHS(<date>, <num_months>)

日期加上<num_months>

<date>参数数据类型 DATE，TIMESTAMP，SECONDDATE

返回的日期类型和<date>参数类型保持一致

12.ADD_MONTHS_LAST Function

ADD_MONTHS_LAST(<date>, <num_months>)

日期加上<num_months>，然后返回该月最后一天日期

<date>参数数据类型 DATE，TIMESTAMP，SECONDDATE

返回的日期类型和<date>参数类型保持一致

13.ADD_NANO100 Function

ADD_NANO100( <time>, <num> )

<time>:TimeStamp类型数据

<num>:microsecond,微秒

14.ADD_SECONDS Function

ADD_SECONDS(<time>, <num_seconds>)

<num_seconds>:增加秒数，可以是毫秒，微秒级别小数

15.ADD_WORKDAYS Function

ADD_WORKDAYS(<factory_calendar_id>, <start_date>, <workdays> [, <source_schema>])

<start_date>上加上<workdays>

factory table: TFACS.

<factory_calendar_id> ::= <string_literal>

<start_date> ::= <string_literal> | <date>,可以是日期类型，也可以是日期格式字符串'20200101' or '2020-01-01'

<source_schema> ::= <string_literal> ,schema factory table is located

16.ADD_YEARS Function

ADD_YEARS(<date>, <num_years>)

*/

--ADD_DAYS
SELECT ADD_DAYS (TO_DATE ('2009-12-05', 'YYYY-MM-DD'), 30)  FROM DUMMY;

--ADD_MONTHS
SELECT ADD_MONTHS (TO_DATE ('2009-12-05', 'YYYY-MM-DD'), 1)  FROM DUMMY;
SELECT ADD_MONTHS (TO_DATE ('2009-12-05', 'YYYY-MM-DD'), -1)  FROM DUMMY;

--ADD_MONTHS_LAST,??function不存在
--SELECT ADD_MONTHS_LAST (TO_DATE ('2009-02-28', 'YYYY-MM-DD'), 1) FROM DUMMY;
--ADD_NANO100,??function不存在
--SELECT ADD_NANO100(TO_TIMESTAMP('1990-01-01 10:00:00.0000000'), 864000000000) FROM DUMMY;

--ADD_SECONDS
SELECT ADD_SECONDS (TO_TIMESTAMP ('2012-01-01 23:30:45'), 30) FROM DUMMY;
SELECT ADD_SECONDS (TO_TIMESTAMP ('2012-01-01 23:30:45'), 30.0000001) FROM DUMMY;

--ADD_WORKDAYS,需要schema有相应表
--SELECT ADD_WORKDAYS('01', '2014-01-20', 1, 'FCTEST') "result date" FROM DUMMY;
--ADD_YEARS
SELECT ADD_YEARS(TO_DATE ('2009-12-05', 'YYYY-MM-DD'), 1) FROM DUMMY;

/*

17.ALLOW_PRECISION_LOSS Function

ALLOW_PRECISION_LOSS( <aggregate_expression> )

<aggregate_expression> ::= SUM ( <expression> )

使用聚合表达式聚合十进制值时允许精度损失。

当精度损失可接受时，使用此函数可提高聚合表达式对十进制值的性能，并提高聚合的性能。

*/

--ALLOW_PRECISION_LOSS
CREATE TABLE TEST_DECIMAL (COL1 decimal(10,5), COL2 decimal);
INSERT INTO TEST_DECIMAL VALUES(1.139999, 1.138888888);
INSERT INTO TEST_DECIMAL VALUES(2.119999, 2.118888888);
INSERT INTO TEST_DECIMAL VALUES(2.119999, 2.118888888);
INSERT INTO TEST_DECIMAL VALUES(2.669999, 2.668888888);
-- The following query, which does not allow precision loss, returns 8.01, 8.01                 
SELECT SUM(TO_DECIMAL(COL1,10,2)), SUM(TO_DECIMAL(COL2,10,2)) FROM TEST_DECIMAL;
-- The following query, which uses the ALLOW_PRECISION_LOSS function to allow precision loss, returns 8.04, 8.04
--SELECT ALLOW_PRECISION_LOSS(SUM(TO_DECIMAL(COL1,10,2))), ALLOW_PRECISION_LOSS(SUM(TO_DECIMAL(COL2,10,2))) FROM TEST_DECIMAL;
--没有这个function?

/*

18.ASCII Function

ASCII(<string>)

返回字符对应ASCII整型数据

*/

--ASCII
--A 对应ASCII 65
SELECT ASCII('Ant') FROM DUMMY;
--a 对应ASCII 97
SELECT ASCII('ant') FROM DUMMY;

/*

19.AUTO_CORR Function

AUTO_CORR( <expression>, <maxTimeLag> { <series_order_by_clause> | <order_by_clause> })

计算给定输入表达式的所有自相关系数并返回值数组。

maxTimeLag：必须正整数;

<expression>值可以是任何数字类型;

<series_orderby> ::= SERIES( <series_period> <series_equidistant_definition> )

<series_orderby>只能与等距序列使用

<order_by_clause> ::= ORDER BY <order_by_expression> [, <order_by_expression> [,...] ]

 <order_by_expression> ::=

  <column_name> [ <collate_clause> ] [ ASC | DESC ] [ NULLS FIRST | NULLS LAST ]

  | <column_position> [ <collate_clause> ] [ ASC | DESC ] [ NULLS FIRST | NULLS LAST ]

 <collate_clause> ::= COLLATE <collation_name>

<collate_clause> :指定结果值排序排序规则；

<collate_clause>只能用于定义为NVARCHAR或VARCHAR的列；

<collation_name>是COLLATIONS系统视图中列出的受支持的排序规则名称之一。

*/

实例1：

--密集序列数据返回自相关系数数组
CREATE COLUMN TABLE correlationTable (TS_ID VARCHAR(10), "DATE" DAYDATE, "VALUE" DOUBLE);
INSERT INTO correlationTable VALUES ('A', '2014-10-01', 1);
INSERT INTO correlationTable VALUES ('A', '2014-10-02', 2);
INSERT INTO correlationTable VALUES ('A', '2014-10-03', 3);
INSERT INTO correlationTable VALUES ('A', '2014-10-04', 4);
INSERT INTO correlationTable VALUES ('A', '2014-10-05', 5);
INSERT INTO correlationTable VALUES ('A', '2014-10-06', 1);
INSERT INTO correlationTable VALUES ('A', '2014-10-07', 2);
INSERT INTO correlationTable VALUES ('A', '2014-10-08', 3);
INSERT INTO correlationTable VALUES ('A', '2014-10-09', 4);
INSERT INTO correlationTable VALUES ('A', '2014-10-10', 5);
SELECT TS_ID, AUTO_CORR("VALUE", 8 SERIES (PERIOD FOR SERIES("DATE") EQUIDISTANT INCREMENT BY INTERVAL 1 DAY MISSING ELEMENTS NOT ALLOWED))   
       FROM correlationTable
    GROUP BY TS_ID
    ORDER BY TS_ID;

实例2：

--稀疏序列数据自相关系数，
--不考虑缺失条目，MISSING ELEMENT NOT ALLOWED
CREATE COLUMN TABLE correlationTable1 (TS_ID VARCHAR(20), "DATE" DAYDATE, VAL DOUBLE);
INSERT INTO correlationTable1 VALUES ('A', '2014-10-01', 1);
INSERT INTO correlationTable1 VALUES ('A', '2014-10-02', 2);
INSERT INTO correlationTable1 VALUES ('A', '2014-10-04', 3);
INSERT INTO correlationTable1 VALUES ('A', '2014-10-07', 4);
INSERT INTO correlationTable1 VALUES ('A', '2014-10-11', 5);
INSERT INTO correlationTable1 VALUES ('A', '2014-10-21', 6);
INSERT INTO correlationTable1 VALUES ('A', '2014-10-22', 7);
SELECT ts_id, AUTO_CORR(VAL, 999 SERIES (PERIOD FOR SERIES("DATE") EQUIDISTANT INCREMENT BY INTERVAL 1 DAY MISSING ELEMENTS NOT ALLOWED))   
      FROM correlationTable1
    GROUP BY TS_ID
    ORDER BY TS_ID;

实例3：

--稀疏序列数据自相关系数，
--考虑缺失条目，MISSING ELEMENT ALLOWED
CREATE COLUMN TABLE correlationTable2 (TS_ID VARCHAR(20), "DATE" DAYDATE, VAL DOUBLE);
INSERT INTO correlationTable2 VALUES ('A', '2014-10-01', 1);
INSERT INTO correlationTable2 VALUES ('A', '2014-10-02', 2);
INSERT INTO correlationTable2 VALUES ('A', '2014-10-04', 3);
INSERT INTO correlationTable2 VALUES ('A', '2014-10-07', 4);
INSERT INTO correlationTable2 VALUES ('A', '2014-10-11', 5);
INSERT INTO correlationTable2 VALUES ('A', '2014-10-21', 6);
INSERT INTO correlationTable2 VALUES ('A', '2014-10-22', 7);
SELECT ts_id, AUTO_CORR(VAL, 999 SERIES (PERIOD FOR SERIES("DATE") EQUIDISTANT INCREMENT BY INTERVAL 1 DAY MISSING ELEMENTS ALLOWED))
       FROM correlationTable2
    GROUP BY TS_ID
    ORDER BY TS_ID;

/*

20.AVG Function

Aggregate function:

       AVG( [ ALL | DISTINCT ] <expression> )

Window function:

       AVG( <expression> ) <window_specification>

<window_specification>

Defines a window on the data over which the function operates.

For <window_specification>, see Window Functions and the Window Specification

AVG输出数据类型取决于输入值类型

输入类型：输出类型

TINYINT:DECIMAL(9,6)

SMALLINT:DECIMAL(11,6)

INTEGER:DECIMAL(16,6)

BIGINT:DECIMAL(25,6)

DECIMAL(p ,s):DECIMAL(p,s)

DECIMAL:DECIMAL

REAL:REAL

DOUBLE:DOUBLE

*/

--删除Table
DROP TABLE "MyProducts";
--创建Table
CREATE COLUMN TABLE "MyProducts"( 
       "Product_ID" VARCHAR(10), 
       "Product_Name" VARCHAR(100), 
       "Category" VARCHAR(100), 
       "Quantity" INTEGER, 
       "Price" DECIMAL(10,2),
       PRIMARY KEY ("Product_ID") );               
INSERT INTO "MyProducts" VALUES('P1','Shirts', 'Clothes', 32, 20.99);
INSERT INTO "MyProducts" VALUES('P2','Jackets', 'Clothes', 16, 99.49);
INSERT INTO "MyProducts" VALUES('P3','Trousers', 'Clothes', 30, 32.99);
INSERT INTO "MyProducts" VALUES('P4','Coats', 'Clothes', 5, 129.99);
INSERT INTO "MyProducts" VALUES('P5','Purse', 'Accessories', 3, 89.49);
--AVG
SELECT AVG("Price") FROM "MyProducts";