SAPHANA学习（19）：SQL Function(S)

/*

121. SCORE

SCORE()

Returns the relevance of a record that has been found.

*/

SELECT SCORE(),"Content" FROM SEARCH_TEXT WHERE CONTAINS("Content", 'cap', LINGUISTIC);
SELECT SCORE(), "Content" FROM SEARCH_TEXT WHERE CONTAINS("Content", 'ca',Fuzzy(0.8));

/*

122. SECOND

SECOND(<time>)

返回时间的second

SECONDS_BETWEEN(<date_1>, <date_2>)

返回两个日期之间秒数

*/

SELECT SECOND ('12:34:56') FROM DUMMY;
SELECT SECOND ('2014-03-25 12:34:56.789') FROM DUMMY;
SELECT SECONDS_BETWEEN ('2009-12-05', '2010-01-05') FROM DUMMY;

/*

123. SERIES_DISAGGREGATE

SERIES_DISAGGREGATE(

     {SERIES TABLE <source_series_table> | <source_increment_by>},

     {SERIES TABLE <generate_series_table> | <target_increment_by>}

     [, <min_value> [, <max_value>]] )

     | { SERIES_DISAGGREGATE_TINYINT   

       | SERIES_DISAGGREGATE_SMALLINT   

       | SERIES_DISAGGREGATE_INTEGER   

       | SERIES_DISAGGREGATE_BIGINT   

       | SERIES_DISAGGREGATE_SMALLDECIMAL   

       | SERIES_DISAGGREGATE_DECIMAL   

       | SERIES_DISAGGREGATE_TIME   

       | SERIES_DISAGGREGATE_DATE   

       | SERIES_DISAGGREGATE_SECONDDATE   

       | SERIES_DISAGGREGATE_TIMESTAMP }

     (source_increment_by, target_increment_by, min_value, max_value)

<source_series_table>等距序列table

<source_series_table> ::= <identifier>

<source_increment_by> ::= <real_const> | <datetime_const>

<generate_series_table> ::= <identifier>

<target_increment_by> ::= <real_const> | <datetime_const>

<min_value> ::= <real_const> | <datetime_const>

<max_value> ::= <real_const> | <datetime_const>

*/

CREATE COLUMN TABLE TEST_SOURCE_SERIES(id INT, ts TIMESTAMP, val DECIMAL(8,2))
    SERIES(SERIES KEY(id ) EQUIDISTANT INCREMENT BY INTERVAL 1 YEAR 
     MINVALUE '1999-01-01'   MAXVALUE '2003-01-01'   PERIOD FOR SERIES (ts));
                      
CREATE COLUMN TABLE TEST_TARGET_SERIES(id INT, ts TIMESTAMP, val DECIMAL(8,2))  
       SERIES(SERIES KEY(id ) EQUIDISTANT INCREMENT BY INTERVAL 3 MONTH  
       MINVALUE '1999-01-01'   MAXVALUE '2001-01-01'   PERIOD FOR SERIES (ts));

INSERT INTO TEST_TARGET_SERIES(id , ts, val) 
       SELECT
              id,
              GENERATED_PERIOD_START AS ts,
              val * FRACTION_OF_SOURCE_PERIOD AS val  
      FROM SERIES_DISAGGREGATE(SERIES TABLE TEST_SOURCE_SERIES, SERIES TABLE TEST_TARGET_SERIES)
    SD JOIN TEST_SOURCE_SERIES S ON source_period_start = ts ORDER BY id, ts;
SELECT * FROM SERIES_DISAGGREGATE_DATE('INTERVAL 1 year', 'INTERVAL 3 MONTH', '1999-01-01', '2001-01-04' );
SELECT * from SERIES_DISAGGREGATE( SERIES TABLE TEST_SOURCE_SERIES, SERIES TABLE TEST_TARGET_SERIES);

/*

124. SERIES_ELEMENT_TO_PERIOD

SERIES_ELEMENT_TO_PERIOD( <element_number>, { <increment_by>, <min_value>, <max_value> | SERIES TABLE <series_table> } )

<element_number> ::= INTEGER

<increment_by> ::= <real_const> | <interval_const>

<min_value> ::= <real_const> | <datetime_const>

<max_value> ::= <real_const> | <datetime_const>

<element_number>生成序列中数字个数；

<increment_by>步长；

*/

--对应序列[0，2，4，6，8]，返回8
SELECT SERIES_ELEMENT_TO_PERIOD(5, 2, 0, 10)  FROM DUMMY;

--[1，2.25，3.50，4.75，6.00，7.25]，返回7.25
SELECT SERIES_ELEMENT_TO_PERIOD(6, 1.25, 1, 10) FROM DUMMY;

--返回2014/01/07
SELECT SERIES_ELEMENT_TO_PERIOD(7, 'INTERVAL 1 DAY', '2014-01-01', '2014-12-31') FROM DUMMY;

--返回1，1999-01-07和1999-01-01,间来年1
SELECT SERIES_PERIOD_TO_ELEMENT('1999-01-07',SERIES TABLE TEST_SOURCE_SERIES) FROM DUMMY;

--SECOND间隔
SELECT SERIES_ELEMENT_TO_PERIOD(500000, 'INTERVAL 1.5 SECOND',
     '2014-01-01 00:00:00.000', '2014-12-31') FROM DUMMY;

/*

125. SERIES_FILTER

SERIES_FILTER(<filter_parameter> => <expression> [, <filter_parameter> => <expression> ... ])

  OVER (

    [ <series_definition> | <series_reference> ]

    [ <window_partition_by_clause> ]

    [ ORDER BY <window_order_by_expression> ]

    [ <window_frame_clause> ]

       )

<filter_parameter> ::= VALUE | METHOD_NAME | ALPHA | BETA

VALUE:是必须参数，指定应用筛选器列，列必须是数字类型，不能为null值

METHOD_NAME:必须参数，指定filter method,SINGLESMOOTH or DOUBLESMOOTH

ALPHA:可选，默认0.1，0-1,the level of the series ;

BETA:可选，默认0.1,0-1,the trend of the series;

<window_partition_by_clause> ::= PARTITION BY <expression> [ { , <expression> } ... ]

<window_frame_clause> ::= <window_frame_unit> <window_frame_extent>

 <window_frame_unit> ::= ROWS

 <window_frame_extent> ::= <window_frame_start> | <window_frame_between>

 <window_frame_start> ::= UNBOUNDED PRECEDING | <window_frame_preceding> | CURRENT ROW

 <window_frame_preceding> ::= <unsigned_integer> PRECEDING

 <window_frame_between> ::= BETWEEN <lower_window_frame_bound> AND <upper_window_frame_bound>

 <lower_window_frame_bound> ::= <window_frame_bound>

 <upper_window_frame_bound> ::= <window_frame_bound>

 <window_frame_bound> := <window_frame_start> | UNBOUNDED FOLLOWING | <window_frame_following>

 <window_frame_following> ::= <unsigned_integer> FOLLOWING

*/

CREATE COLUMN TABLE TEST_FILTER_SERIES (ts DATE, temperature FLOAT);
INSERT INTO TEST_FILTER_SERIES VALUES('2014-01-01', 0);
INSERT INTO TEST_FILTER_SERIES VALUES('2014-01-02', 3);
INSERT INTO TEST_FILTER_SERIES VALUES('2014-01-03', 4.5);
INSERT INTO TEST_FILTER_SERIES VALUES('2014-01-04', 6);
INSERT INTO TEST_FILTER_SERIES VALUES('2014-01-05', 6.3);
INSERT INTO TEST_FILTER_SERIES VALUES('2014-01-06', 6.9);
INSERT INTO TEST_FILTER_SERIES VALUES('2014-01-07', NULL);
INSERT INTO TEST_FILTER_SERIES VALUES('2014-01-08', NULL);

SELECT
       ts,
       temperature,
       SERIES_FILTER(
              VALUE => temperature,
              METHOD_NAME => 'SINGLESMOOTH',
              ALPHA => 0.2)
              OVER (ORDER BY ts) AS SES,      
       SERIES_FILTER(
              VALUE => temperature,
              METHOD_NAME => 'DOUBLESMOOTH',
              ALPHA => 0.2,
              BETA => 0.3)
              OVER (ORDER BY ts) AS DES
 FROM TEST_FILTER_SERIES;

/*

126. SERIES_GENERATE

 SERIES_GENERATE( SERIES TABLE <table_name> [, <min_value> [, <max_value> ]] )

 | SERIES_GENERATE_<generation_spec>

Generates a complete series table based on the specified series definition.

<generation_spec> ::= <data_type> <generate_parameters>

<data_type> ::=  TINYINT | SMALLINT  | INTEGER  | BIGINT  | SMALLDECIMAL  | DECIMAL  | TIME  | DATE  | SECONDDATE | TIMESTAMP

<generate_parameters> ::=

 ( <increment_by>, <min_value>, <max_value> )

<increment_by> ::= { <numeric_literal> | INTERVAL <date_literal> }

<table_name> ::= <identifier>

<min_value> ::= <numeric_literal> | <date_literal>

<max_value> ::= <numeric_literal> | <date_literal>

*/

--生成range改变表[0->2.5->5->7.5->10]，0~10，间隔2.5
SELECT * FROM SERIES_GENERATE_DECIMAL(2.5, 0, 10);

--生成range改变表[1->3->5]，1~5,间隔2
SELECT * FROM SERIES_GENERATE_INTEGER(2, 1, 5);

--生成range改变表，1999-01-01~1999-01-02,间隔30秒
SELECT * FROM SERIES_GENERATE_TIMESTAMP('INTERVAL 30 SECOND', '1999-01-01', '1999-01-02');

--创建等距SERIES表
CREATE COLUMN TABLE TEST_SERIES_GENERATE (
     profile_id INT,   
     ts TIMESTAMP,   
     consumption DECIMAL(4,3))   
     SERIES(       
          SERIES KEY(profile_id)       
          PERIOD FOR SERIES(ts)       
          EQUIDISTANT INCREMENT BY INTERVAL 1 HOUR MISSING ELEMENTS ALLOWED       
          MINVALUE '2010-01-01'       
          MAXVALUE '2015-01-01');

--2010-01-01~2015-01-01，间隔1hour
SELECT * FROM SERIES_GENERATE_TIMESTAMP(SERIES TABLE TEST_SERIES_GENERATE);

--创建等距SERIES表
CREATE COLUMN TABLE TEST_SERIES_GENERATE1(id  INTEGER, pos INTEGER)
    SERIES(
           SERIES KEY(id) 
           PERIOD FOR SERIES(pos)
           EQUIDISTANT INCREMENT BY 1
           MINVALUE 1
           MAXVALUE 5
           );
 --[1->2->3->4->5], 1~5,间隔1
SELECT * FROM SERIES_GENERATE(SERIES TABLE TEST_SERIES_GENERATE1);

/*

127. SERIES_PERIOD_TO_ELEMENT

SERIES_PERIOD_TO_ELEMENT(

  <value>, {<increment_by>, <min_value>, <max_value> [, <rounding_mode>]

  | SERIES TABLE <series_table> [, <rounding_mode>]}

  )

Returns the one-based series element number with which the given period value is associated,

where period = min_value + ( element - 1 ) * interval.

<value> ::= INTEGER | DOUBLE | TIMESTAMP

<increment_by> ::= <identifier>

<min_value> ::= <integer>

<max_value> ::= <integer>

<rounding_mode> ::= ROUND_HALF_UP| ROUND_HALF_DOWN | ROUND_HALF_EVEN | ROUND_UP | ROUND_DOWN | ROUND_CEILING| ROUND_FLOOR

*/

--0->2->4->6->8,返回中间值4
SELECT SERIES_PERIOD_TO_ELEMENT(5, 2, 0, 10, ROUND_HALF_UP) FROM DUMMY;
--0->2->4->6->8,返回3？
SELECT SERIES_PERIOD_TO_ELEMENT(5, 2, 0, 10, ROUND_HALF_DOWN) FROM DUMMY;
--返回3？
SELECT SERIES_PERIOD_TO_ELEMENT(5, 2, 0, 10, ROUND_HALF_EVEN) FROM DUMMY;
--返回4
SELECT SERIES_PERIOD_TO_ELEMENT(5, 2, 0, 10, ROUND_UP) FROM DUMMY;
--返回3
SELECT SERIES_PERIOD_TO_ELEMENT(5, 2, 0, 10, ROUND_DOWN) FROM DUMMY;
--返回4，2014-01到2014-04，间隔月份，
SELECT SERIES_PERIOD_TO_ELEMENT(
     '2014-04-01 12:00:00','INTERVAL 1 MONTH','2014-01-01','2014-12-31',
     ROUND_HALF_DOWN) FROM DUMMY;

/*

128. SERIES_ROUND

SERIES_ROUND( <value>, { <increment_by> | SERIES TABLE <series_table> } [, <rounding_mode> [, <alignment_expression> ] ] )

Rounds a specified value to the series value using the specified rounding settings.

<value> ::= { <real_const> | <datetime_const> }

<increment_by>::= <interval_const>

<series_table> ::= <identifier>

<rounding_mode> ::= ROUND_HALF_UP| ROUND_HALF_DOWN | ROUND_HALF_EVEN | ROUND_UP | ROUND_DOWN | ROUND_CEILING | ROUND_FLOOR

<alignment_expression> ::= { <real_const> | <datetime_const> }

<increment_by>和SERIES TABLE <series_table>选一

*/

SELECT SERIES_ROUND(4.5, 3, ROUND_HALF_UP) FROM DUMMY;
SELECT SERIES_ROUND(4.5, 3, ROUND_HALF_DOWN) FROM DUMMY;
SELECT SERIES_ROUND('2013-05-24', 'INTERVAL 1 YEAR', ROUND_DOWN) FROM DUMMY;

CREATE COLUMN TABLE TEST_SERIES_ROUND(id INTEGER, pos INTEGER)
     SERIES(
          SERIES KEY(id)
          EQUIDISTANT INCREMENT BY 3
          PERIOD FOR SERIES(pos));
SELECT SERIES_ROUND(4.5, SERIES TABLE TEST_SERIES_ROUND, ROUND_HALF_DOWN) FROM DUMMY;

/*

129. SESSION_CONTEXT

SESSION_CONTEXT(<session_variable>)

Returns the value of the specified session variable assigned to the current user.

<session_variable> 可以预定义，用户自定义

SET [SESSION] <variable_name> = <value>

UNSET [SESSION] <variable_name>

SESSION_USER

Returns the user name of the current session.

*/

SELECT SESSION_CONTEXT('APPLICATION') FROM DUMMY;
SELECT SESSION_USER FROM DUMMY;

/*

130. SIGN

SIGN(<number>)

Returns the sign (positive or negative) of the specified numeric argument.

正数返回1，负数返回-1，0返回0，null返回null

*/

SELECT SIGN (-15) FROM DUMMY;
SELECT SIGN (1) FROM DUMMY;
SELECT SIGN (0) FROM DUMMY;
SELECT SIGN (null) FROM DUMMY;

/*

131.SIN

SIN(<number>)

返回sin x三角函数值

SINH(<number>)

返回以弧度表示的角度的双曲正弦值

*/

--sin (pi/2) = 1
SELECT SIN ( 3.141592653589793/2) FROM DUMMY;

--sin1,弧度,pi约等于3.14,
SELECT SIN (1) FROM DUMMY;

--近似于弧度1，sin1,sin(pi/3)
SELECT SIN (3.1415926/3) FROM DUMMY;

--双曲正弦值
SELECT SINH (0.0) FROM DUMMY;

/*

132.SOUNDEX

SOUNDEX(<string>)

Converts alphabet characters into a sound code that represents their sound.

*/

--不存在？
--SELECT SOUNDEX ('Smith'), SOUNDEX ('Smythe') FROM DUMMY; 

/*

133.SQRT

SQRT(<number>)

返回平方根

*/

SELECT SQRT(2) FROM DUMMY;

/*

134. STDDEV

Aggregate function:

STDDEV( [ ALL | DISTINCT ] <expression> )

Window function:

STDDEV( <expression> ) <window_specification>

Returns the standard deviation of the given expression as the square root of the VAR function.

STDDEV_POP(<expression>)

Returns the standard deviation of the given expression as the square root of the VAR_POP function.

STDDEV_SAMP(<expression>)

Returns the standard deviation of the given expression as the square root of VAR_SAMP function.

SELECT STDDEV("Price") FROM "MyProducts";
SELECT STDDEV_POP("Price") FROM "MyProducts";
SELECT STDDEV_SAMP("Price") FROM "MyProducts";

*/

/*

135. STRING_AGG

STRING_AGG( <expression>[, <delimiter> ] [ <order_by_clause> ] )

字符串连接

<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>

*/

CREATE ROW TABLE TEST_STRING(ID INT, STR VARCHAR(20), GRP INT);
 INSERT INTO TEST_STRING VALUES (3,'str2',0);
 INSERT INTO TEST_STRING VALUES (0,'str1',0);
 INSERT INTO TEST_STRING VALUES (NULL,'NULL',0);
 INSERT INTO TEST_STRING VALUES (5,'str3',0);
 INSERT INTO TEST_STRING VALUES (3,'val3',1);
 INSERT INTO TEST_STRING VALUES (6,'val6',1);
 INSERT INTO TEST_STRING VALUES (NULL,'NULL',1);
 INSERT INTO TEST_STRING VALUES (1,'val1',1);
SELECT GRP,STRING_AGG(STR,'&') AS STR_AGG FROM TEST_STRING GROUP BY "GRP";

/*

136. STRTOBIN

STRTOBIN(<string>, <codepage>)

字符串转换为二进制

*/

SELECT STRTOBIN ('Ant', 'UTF-16BE') FROM DUMMY;
SELECT STRTOBIN ('Ant', 'UTF-8') FROM DUMMY;
SELECT STRTOBIN ('Ant', 'GBK') FROM DUMMY;

/*

137. SUBARRAY

SUBARRAY(<array_value_expression>, <start_position> , <length>)

获取指定长度array

*/

SELECT SUBARRAY(VAL, 1, 2) FROM ARRAY_TEST;

/*

138. SUBSTR_AFTER

SUBSTR_AFTER(<string>, <pattern>)

返回字符串<string>匹配<pattern>之后字符串

SUBSTR_BEFORE(<string>, <pattern>)

返回字符串<string>匹配<pattern>之前字符串

SUBSTR[ING]_REGEXPR( <pattern> [ FLAG <flag> ] IN <regex_subject_string>

  [ FROM <start_position> ]

  [ OCCURRENCE <regex_occurrence> ]

  [ GROUP <regex_capture_group> ] )

正则表达式匹配

<pattern>正则表达式

<flag>：模式，i:大小写不敏感；m:多行模式；s:<.>可以匹配任意字符；x：regex表达式支持空格

<flag> ::= 'i' | 'm' | 's' | 'x'

<regex_subject_string> ::= <string>

被匹配的字符串

<start_position> ::= <numeric_literal>

开始位置

<regex_occurrence> ::= <numeric_literal >

匹配次数

<regex_capture_group> ::= <integer>

返回第几分组数

SUBSTRING(<string>, <start_position> [, <string_length>])

字符串切割

*/

--返回Friend
SELECT SUBSTR_AFTER ('Hello My Friend','My') FROM DUMMY;

--返回null
SELECT SUBSTR_AFTER ('Hello My Friend',null) FROM DUMMY;

--返回Hello
SELECT SUBSTR_BEFORE ('Hello My Friend','My') FROM DUMMY;

--返回01
SELECT SUBSTR_REGEXPR('([[:digit:]]{4})([[:digit:]]{2})([[:digit:]]{2})' IN '20140401' GROUP 3) FROM DUMMY;

--切割字符串
SELECT SUBSTRING(x'ABCDEF',1,2) FROM DUMMY;
SELECT SUBSTRING ('1234567890',4,2) "substring" FROM DUMMY;

/*

139.SUM

Aggregate function:

SUM( [ ALL | DISTINCT ] <expression> )

Window function:

SUM( <expression> ) <window_specification>

求和

*/

SELECT SUM("Quantity") FROM "MyProducts" WHERE "Product_Name" IN ('Jackets', 'Coats');

/*

140.SYSUUID

Returns a new universally unique identifier that is generated by the connected SAP HANA instance.

*/

SELECT SYSUUID FROM DUMMY;