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      SQL Server 2012/2016/2017 新增函數(shù)

      1. /**************************************************************
      2. SQL Server 2012 新增的函數(shù)
      3. ***************************************************************/
      4.  
      5. -- CONCAT ( string_value1, string_value2 [, string_valueN ] ) #字符串相連
      6. SELECT CONCAT('A','BB','CCC','DDDD')
      7. --結(jié)果:ABBCCCDDDD
      8.  
      9. -- PARSE ( string_value AS data_type [ USING culture ] ) #轉(zhuǎn)換為所請求的數(shù)據(jù)類型的表達式的結(jié)果
      10. SELECT PARSE('Monday, 13 December 2010' AS datetime2 USING 'en-US') AS Result;
      11. SELECT PARSE('€345,98' AS money USING 'de-DE') AS Result;
      12.  
      13. SET LANGUAGE 'English';
      14. SELECT PARSE('12/16/2010' AS datetime2) AS Result;
      15.  
      16. /*結(jié)果:
      17. 2010-12-13 00:00:00.0000000
      18. 345.98
      19. 2010-12-16 00:00:00.0000000
      20. */
      21.  
      22. -- TRY_CAST TRY_CONVERTTRY_PARSE (TRY_PARSE 僅用于從字符串轉(zhuǎn)換為日期/時間和數(shù)字類型)
      23. SELECT TRY_CAST('test' AS float),TRY_CAST(5 AS VARCHAR)
      24. SELECT TRY_CONVERT(float,'test'),TRY_CONVERT(VARCHAR,5)
      25. SELECT TRY_PARSE('test' AS float),TRY_PARSE('01/01/2011' AS datetime2)
      26. /*結(jié)果:
      27. NULL 5
      28. NULL 5
      29. NULL 2011-01-01 00:00:00.0000000
      30. */
      31.  
      32. -- CHOOSE ( index, val_1, val_2 [, val_n ] ) #返回指定索引處的項 (即返回第幾個值)
      33. SELECT CHOOSE ( 3, 'Manager', 'Director', 'Developer', 'Tester' ) AS Result;
      34. --結(jié)果:Developer
      35.  
      36. -- IIF ( boolean_expression, true_value, false_value )
      37. SELECT IIF ( 10 > 5, 'TRUE', 'FALSE' ) AS Result;
      38. SELECT (CASE WHEN 10 > 5 THEN 'TRUE' ELSE 'FALSE' END) AS Result;
      39. --結(jié)果:TRUE
      40.  
      41. -- 排名函數(shù)!
      42. SELECT *
      43. ,ROW_NUMBER ( ) OVER (PARTITION BY MyName ORDER BY Num) AS 'ROW_NUMBER' --按順序排名
      44. ,DENSE_RANK ( ) OVER (PARTITION BY MyName ORDER BY Num) AS 'DENSE_RANK' --同排名的后面排名連續(xù)
      45. ,RANK ( ) OVER (PARTITION BY MyName ORDER BY Num) AS 'RANK' --同排名的后面排名不連續(xù)
      46. ,NTILE (2) OVER (PARTITION BY MyName ORDER BY Num) AS 'NTILE' --按總數(shù)分兩組,順序排名
      47. FROM (VALUES('AA',55),('AA',30.5),('BB',55),('BB',99),('BB',0),('BB',55))AS T(MyName,Num)
      48. ORDER BY MyName,Num
      49. /*
      50. MyName Num ROW_NUMBER DENSE_RANK RANK NTILE
      51. ------ ----- ---------- ---------- ------ -----
      52. AA 30.5 1 1 1 1
      53. AA 55.0 2 2 2 2
      54. BB 0.0 1 1 1 1
      55. BB 55.0 2 2 2 1
      56. BB 55.0 3 2 2 2
      57. BB 99.0 4 3 4 2
      58. */
      59.  
      60. -- 分析函數(shù)!
      61. SELECT *
      62. ,CUME_DIST( )OVER (PARTITION BY MyName ORDER BY Num) AS 'CUME_DIST' --相對(最大值)位置
      63. ,PERCENT_RANK( )OVER (PARTITION BY MyName ORDER BY Num) AS 'PERCENT_RANK' --相對排名,排名分數(shù)參考 CUME_DIST
      64. ,FIRST_VALUE (MyName)OVER ( ORDER BY Num ASC) AS 'FIRST_VALUE' --Num 最低的是哪個MyName
      65. ,LAST_VALUE (MyName)OVER ( ORDER BY Num ASC) AS 'LAST_VALUE' --Num 排序選底部的那個MyName
      66. ,LAG (Num,1,0)OVER (ORDER BY Num ASC) AS 'LAG' --上/下一行(或多行)的值移到下/上一行(或多行),方便對比
      67. ,LEAD (Num,1,0)OVER (ORDER BY Num ASC) AS 'LEAD' --與LAG一樣,排序相反
      68. ,PERCENTILE_CONT(0.5)WITHIN GROUP (ORDER BY Num) OVER (PARTITION BY MyName) AS 'PERCENTILE_CONT' --連續(xù)分布計算百分位數(shù)
      69. ,PERCENTILE_DISC(0.5)WITHIN GROUP (ORDER BY Num) OVER (PARTITION BY MyName) AS 'PERCENTILE_DISC' --離散分布計算百分位數(shù)
      70. FROM (VALUES('AA',55),('AA',30.5),('BB',55),('BB',99),('BB',0),('BB',55))AS T(MyName,Num)
      71. ORDER BY Num ASC
      72.  
      73. /*
      74. MyName Num CUME_DIST PERCENT_RANK FIRST_VALUE LAST_VALUE LAG LEAD PERCENTILE_CONT PERCENTILE_DISC
      75. ------ ----- --------- ------------ ----------- ---------- ----- ----- --------------- ---------------
      76. BB 0.0 0.25 0 BB BB 0.0 30.5 55 55.0
      77. AA 30.5 0.5 0 BB AA 0.0 55.0 42.75 30.5
      78. AA 55.0 1 1 BB BB 30.5 55.0 42.75 30.5
      79. BB 55.0 0.75 0.33333 BB BB 55.0 55.0 55 55.0
      80. BB 55.0 0.75 0.33333 BB BB 55.0 99.0 55 55.0
      81. BB 99.0 1 1 BB BB 55.0 0.0 55 55.0
      82. */
      83.  
      84. /**************************************************************
      85. SQL Server 2014 新增的函數(shù)
      86. ***************************************************************/
      87.  
      88. --貌似沒有什么
      89.  
      90. /**************************************************************
      91. SQL Server 2016 新增的函數(shù)
      92. ***************************************************************/
      93.  
      94. -- STRING_SPLIT ( string , separator ) #字符分割
      95. SELECT value FROM STRING_SPLIT('A,B,C',',')
      96. /*結(jié)果:
      97. value
      98. -----
      99. A
      100. B
      101. C
      102. */
      103.  
      104. -- STRING_ESCAPE( text , type ) #特殊字符轉(zhuǎn)成帶有轉(zhuǎn)義字符的文本(type只支持json)
      105. SELECT STRING_ESCAPE('\ / \\ " ', 'json') AS escapedText;
      106. --結(jié)果:\\ \/ \\\\ \"
      107.  
      108. -- DATEDIFF_BIG ( datepart , startdate , enddate ) #日期之間的計數(shù)
      109. SELECT DATEDIFF(day, '2005-12-12', '2017-10-10'); --以前版本
      110. SELECT DATEDIFF_BIG(day, '2005-12-12', '2017-10-10');
      111. SELECT DATEDIFF_BIG(millisecond, '2005-12-31 23:59:59.9999999', '2006-01-01 00:00:00.0000000');
      112. /*結(jié)果:
      113. 4320
      114. 4320
      115. 1
      116. */
      117.  
      118. -- inputdate AT TIME ZONE timezone #時區(qū)時間
      119. SELECT * FROM sys.time_zone_info -- 時區(qū)及名稱參考
      120. SELECT CONVERT(DATETIME,'2017-10-10') AT TIME ZONE 'Pacific Standard Time'
      121. SELECT CONVERT(DATETIME,'2017-10-10') AT TIME ZONE 'China Standard Time'
      122. SELECT CONVERT(datetime2(0), '2017-10-10T01:01:00', 126) AT TIME ZONE 'Pacific Standard Time';
      123. SELECT CONVERT(datetime2(0), '2017-10-10T01:01:00', 126) AT TIME ZONE 'China Standard Time';
      124. /*結(jié)果:
      125. 2017-10-10 00:00:00.000 -07:00
      126. 2017-10-10 00:00:00.000 +08:00
      127. 2017-10-10 01:01:00 -07:00
      128. 2017-10-10 01:01:00 +08:00
      129. */
      130.  
      131. -- COMPRESS ( expression ) # GZIP算法壓縮為varbinary(max)
      132. DECLARE @COM varbinary(max)
      133. SELECT @COM = COMPRESS(N'{"sport":"Tennis","age": 28,"rank":1,"points":15258, turn":17}')
      134. SELECT @COM
      135. --結(jié)果:0x1F8B08000000000004002DCC410A80300C44D17F94D2B51B85A2780E2FE042A414AAD4BA12EFEE……(略)
      136.  
      137. -- DECOMPRESS ( expression )#解壓縮
      138. SELECT CAST(DECOMPRESS(@COM) AS NVARCHAR(MAX))
      139. --結(jié)果:{"sport":"Tennis","age": 28,"rank":1,"points":15258, turn":17}
      140.  
      141. -- SESSION_CONTEXT(N'key') #獲取指定的鍵的值
      142. EXEC sp_set_session_context 'user_id', 4; --設(shè)置鍵值
      143. SELECT SESSION_CONTEXT(N'user_id');
      144. --結(jié)果:4
      145.  
      146. -- ISJSON ( expression ) #測試字符串是否包含有效JSON
      147. DECLARE @param1 NVARCHAR(MAX)
      148. DECLARE @param2 NVARCHAR(MAX)
      149. SET @param1 = N' "id" : 2,"info": { "name": "John", "surname": "Smith" }, "age": 25 '
      150. SET @param2 = N'[{ "id" : 2,"info": { "name": "John", "surname": "Smith" }, "age": 25 }]'
      151. SELECT ISJSON(@param1) as P1, ISJSON(@param2) as P2
      152. GO
      153. /*結(jié)果:
      154. P1 P2
      155. -- --
      156. 0 1
      157. */
      158.  
      159. -- JSON_VALUE ( expression , path ) #從 JSON 字符串中提取值
      160. DECLARE @param NVARCHAR(MAX)
      161. SET @param = N'{ "id" : 2,"info": { "name": "John", "surname": "Smith" }, "age": 25 }'
      162. SELECT JSON_VALUE(@param,'$.id') as P1,JSON_VALUE(@param,'$.info.name')as P2
      163. GO
      164. /*結(jié)果:
      165. P1 P2
      166. -- ----
      167. 2 John
      168. */
      169.  
      170. -- JSON_QUERY ( expression [ , path ] ) #從 JSON 字符串中提取對象或數(shù)組
      171. DECLARE @param NVARCHAR(MAX)
      172. SET @param = N'{ "id" : 2,"info": { "name": "John", "surname": "Smith" }, "age": 25 }'
      173. SELECT JSON_QUERY(@param,'$.info')
      174. GO
      175. --結(jié)果:{ "name": "John", "surname": "Smith" }
      176.  
      177. -- JSON_MODIFY ( expression , path , newValue ) #更新的 JSON 字符串中屬性的值并返回更新的 JSON 字符串
      178. DECLARE @param NVARCHAR(MAX)
      179. SET @param = N'{ "id" : 2,"info": { "name": "John", "surname": "Smith" }, "age": 25 }'
      180. SELECT JSON_MODIFY(@param,'$.info.surname','newValue')
      181. GO
      182. --結(jié)果:{ "id" : 2,"info": { "name": "John", "surname": "newValue" }, "age": 25 }
      183.  
      184. /**************************************************************
      185. SQL Server 2017 新增的函數(shù)
      186. ***************************************************************/
      187.  
      188. -- CONCAT_WS ( separator, argument1, argument1 [, argumentN]… ) #按第一個分隔符連接后面的字符
      189. SELECT CONCAT_WS( ' - ', 1, 'kk', '12dd')
      190. --結(jié)果:1 - kk - 12dd
      191.  
      192. -- TRANSLATE ( inputString, characters, translations) #整體對應(yīng)替換
      193. SELECT TRANSLATE('2*[3+4]/{7-2}', '[]{}', '()()');
      194. SELECT REPLACE(REPLACE(REPLACE(REPLACE('2*[3+4]/{7-2}','[','('), ']', ')'), '{', '('), '}', ')');
      195. SELECT TRANSLATE('2*[3+4]/[7-2]', '[2', '');
      196. /*結(jié)果:
      197. 2*(3+4)/(7-2)
      198. 2*(3+4)/(7-2)
      199. 1*63+4]/67-1]
      200. */
      201.  
      202. -- TRIM ( [ characters FROM ] string ) #刪除字符串左右空格字符
      203. SELECT TRIM( ' test ') AS Result,LTRIM(RTRIM(' test '))
      204.  
      205. -- STRING_AGG ( expression, separator ) #同列字符相連成一行
      206. SELECT STRING_AGG (MyName, CHAR(13)) FROM (VALUES('AAAA'),('BBBBB'),('CCCCCC') )AS T(MyName)
      207. SELECT STRING_AGG (MyName,',') FROM (VALUES('AAAA'),('BBBBB'),('CCCCCC') )AS T(MyName)
      208. SELECT STRING_AGG (MyName,',') WITHIN GROUP(ORDER BY id DESC ) FROM (VALUES(1,'AAAA'),(1,'BBBBB'),(2,'CCCCCC'))AS T(id,MyName)
      209. /*結(jié)果:
      210. AAAA BBBBB CCCCCC
      211. AAAA,BBBBB,CCCCCC
      212. CCCCCC,BBBBB,AAAA
      213. */
      posted @ 2023-01-02 14:38  熊大熊二  閱讀(164)  評論(0)    收藏  舉報
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