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使用LAG和LEAD函数可以在一次查询中取出同一字段的前N行的数据和后N行的值

Lag和Lead函数可以在一次查询中取出同一字段的前N行的数据和后N行的值。这种操作可以使用对相同表的表连接来实现，不过使用LAG和LEAD有更高的效率。以下是LAG和LEAD的例子： SQL> select  year,region,profit ,lag (profit,1) over  (order by year)     2       as last_year_exp from test;   YEAR REGION      PROFIT LAST_YEAR_EXP ---- ------- ---------- ------------- 2003 West            88 2003 West            88            88 2003 Central        101            88 2003 Central        100           101 2003 East           102           100 2004 West            77           102 2004 East           103            77 2004 West            89           103   SQL> select  year,region,profit ,lead (profit,1) over  (order by year)     2       as next_year_exp from test;   YEAR REGION      PROFIT NEXT_YEAR_EXP ---- ------- ---------- ------------- 2003 West            88            88 2003 West            88           101 2003 Central        101           100 2003 Central        100           102 2003 East           102            77 2004 West            77           103 2004 East           103            89 2004 West            89 Lag函数为Lag(exp,N,defval)，defval是当该函数无值可用的情况下返回的值。Lead函数的用法类似。 Lead和Lag函数也可以使用分组，以下是使用region分组的例子： SQL> select  year,region,profit ,   2  lag (profit,1,0) over  (PARTITION BY region order by year)     3       as last_year_exp from test;   YEAR REGION      PROFIT LAST_YEAR_EXP ---- ------- ---------- ------------- 2003 Central        101             0 2003 Central        100           101 2003 East           102             0 2004 East           103           102 2003 West            88             0 2003 West            88            88 2004 West            77            88 2004 West            89            77 该函数也可以用于纵向表转横向表、解释示例：      SQL> select * from test_value;                       MONS JJR               CJL       CJJE         ---------- ---------- ---------- ----------             200801 LZF               250       1999             200802 LZF               200       2000             200803 LZF               300       1000             200804 LZF                23        189             200805 LZF               356        456             200806 LZF               100        200             200807 LZF               600        700             200808 LZF                23        123             200809 LZF               400        500                 9 rows selected                 SQL>         SQL> select rownum 序号,Mons,cjl cjl_01,           2  lead(cjl,1) over (order by mons desc) cjl_02,           3  lead(cjl,2) over (order by mons desc) cjl_03,           4  lead(cjl,3) over (order by mons desc) cjl_04,           5  lead(cjl,4) over (order by mons desc) cjl_05,           6  lead(cjl,5) over (order by mons desc) cjl_06,           7  lead(cjl,6) over (order by mons desc) cjl_07,           8  lead(cjl,7) over (order by mons desc) cjl_08,           9  lead(cjl,8) over (order by mons desc) cjl_09          10   from test_value               序号       MONS     CJL_01     CJL_02     CJL_03     CJL_04     CJL_05     CJL_06     CJL_07     CJL_08     CJL_09         ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ----------                  9     200809        400         23        600        100        356         23        300        200        250                  8     200808         23        600        100        356         23        300        200        250                  7     200807        600        100        356         23        300        200        250                             6     200806        100        356         23        300        200        250                                        5     200805        356         23        300        200        250                                                   4     200804         23        300        200        250                                                              3     200803        300        200        250                                                                         2     200802        200        250                                                                                    1     200801        250