Index Full Scan vs Index Fast Full Scan-1103

时间:2023-03-08 17:09:40

[Oracle] Index Full Scan vs Index Fast Full Scan
作者:汪海 (Wanghai)
日期:14-Aug-2005 
出处:http://spaces.msn.com/members/wzwanghai/

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Index Full Scan vs Index Fast Full Scan

index full scan和index fast full scan是指同样的东西吗?
答案是no。
两者虽然从字面上看起来差不多,但是实现的机制完全不同。

我们一起来看看两者的区别在哪里?

首先来看一下IFS,FFS能用在哪里:在一句sql中,如果我们想搜索的列都包含在索引里面的话,那么index full scan 和 index fast full scan 都可以被采用代替full table scan。

比如以下语句:

-- 1.创建测试表
SQL> CREATE TABLE TEST AS SELECT * FROM dba_objects WHERE 0=1;

--2.创建测试索引
SQL> CREATE INDEX ind_test_id ON TEST(object_id);

--3.插入测试数据
SQL> INSERT INTO TEST   SELECT   *       FROM dba_objects      WHERE object_id IS NOT NULL AND object_id > 10000   ORDER BY object_id DESC;

17837 rows created.

--4.分析表 附带索引等等
SQL> analyze table test compute statistics for table for all columns for all indexes;

Table analyzed.

--5.打开执行计划
SQL> set autotrace trace;

--6.FFS示例
SQL> select object_id from test;

17837 rows selected.

Execution Plan
----------------------------------------------------------
   0      SELECT STATEMENT Optimizer=CHOOSE (Cost=68 Card=17837 Bytes=71348)
   1    0   TABLE ACCESS (FULL) OF 'TEST' (Cost=68 Card=17837 Bytes=71348)
这时候 Oracle会选择全表扫描,因为 object_id 列默认是可以为null的,来修改成 not null

--6.1修改字段属性 not null    
SQL>alter table test modify(object_id not null);

--6.2再次验证 FFS
SQL> select object_id from test;

17837 rows selected.

Execution Plan
----------------------------------------------------------
   0      SELECT STATEMENT Optimizer=CHOOSE (Cost=11 Card=17837 Bytes=71348)
   1    0   INDEX (FAST FULL SCAN) OF 'IND_TEST_ID' (NON-UNIQUE) (Cost=11 Card=17837 Bytes=71348)
没有问题

--7. IFS 示例
SQL> select/*+ index(test ind_TEST_ID)*/ object_id from test;

17837 rows selected.

Execution Plan
----------------------------------------------------------
   0      SELECT STATEMENT Optimizer=CHOOSE (Cost=41 Card=17837 Bytes=71348)
   1    0   INDEX (FULL SCAN) OF 'IND_TEST_ID' (NON-UNIQUE) (Cost=101 Card=17837 Bytes=71348)
没有问题

我们看到了两者都可以在这种情况下使用,那么他们有什么区别呢?有个地方可以看出两者的区别, 来看一下两者的输出结果,为了让大家看清楚一点,我们只取10行。

--8结果验证
--8.1FFS(INDEX FAST FULL SCAN)
SQL> select object_id from test where rownum<11;
    
 OBJECT_ID
----------
     66266
     66267
     66268
     66269
     66270
     66271
     66272
     66273
     66274
     66275
10 rows selected.

 
--8.2FS(INDEX FULL SCAN)
SQL> select/*+ index(test ind_TEST_ID)*/ object_id from test  where rownum<11;
    
 OBJECT_ID
----------
     10616
     12177
     12178
     12179
     12301
     13495
     13536
     13539
     13923
     16503
10 rows selected.
 
结论:两者的结果完全不一样,这是为什么呢?
这是因为当进行index full scan的时候 oracle定位到索引的root block,然后到branch block(如果有的话),再定位到第一个leaf block, 然后根据leaf block的双向链表顺序读取。它所读取的块都是有顺序的,也是经过排序的。
        而进行index fast full scan则不同,它是从段头开始,读取包含位图块,root block,所有的branch block, leaf block,读取的顺序完全由物理存储位置决定,并采取多块读,每次读取db_file_multiblock_read_count个块。

--9.原因考证
这就是为什么两者的结果区别如此之大的原因,我们再仔细跟踪一下这两条语句。首先来看一下索引的结构
--9.1 FFS 操作结果
SQL> select object_id from dba_objects where object_name='IND_TEST_ID';

 OBJECT_ID
----------
     70591
索引的object_id为70591,使用tree dump可以看到索引树的结构
--9.2 索引结构探究
SQL> ALTER SESSION SET EVENTS 'immediate trace name TREEDUMP level 70591';

----- begin tree dump
branch: 0x6809b8d 109091725 (0: nrow: 100, level: 1)
   leaf: 0x6809b96 109091734 (-1: nrow: 294 rrow: 0)
   leaf: 0x6c07ec1 113278657 (0: nrow: 262 rrow: 0)
   leaf: 0x6c07ebd 113278653 (1: nrow: 518 rrow: 0)
   leaf: 0x6c07eb1 113278641 (2: nrow: 524 rrow: 0)
   leaf: 0x6c07ead 113278637 (3: nrow: 524 rrow: 0)
   leaf: 0x6c07ea9 113278633 (4: nrow: 524 rrow: 0)
   leaf: 0x6c07ea5 113278629 (5: nrow: 524 rrow: 0)
   leaf: 0x6c07ea1 113278625 (6: nrow: 524 rrow: 0)
   leaf: 0x6c07e9d 113278621 (7: nrow: 524 rrow: 0)
   leaf: 0x6c07e99 113278617 (8: nrow: 524 rrow: 0)
   leaf: 0x6c07e95 113278613 (9: nrow: 532 rrow: 0)
   leaf: 0x6c07e91 113278609 (10: nrow: 524 rrow: 0)
   leaf: 0x6c07e8d 113278605 (11: nrow: 524 rrow: 0)
   leaf: 0x6c07ec8 113278664 (12: nrow: 524 rrow: 0)
   leaf: 0x6c07ec4 113278660 (13: nrow: 524 rrow: 0)
   leaf: 0x6c07ec0 113278656 (14: nrow: 524 rrow: 0)
   leaf: 0x6c07ebc 113278652 (15: nrow: 524 rrow: 0)
   leaf: 0x6809bb2 109091762 (16: nrow: 524 rrow: 0)
   leaf: 0x6c07eb8 113278648 (17: nrow: 524 rrow: 0)
   leaf: 0x6c07eb4 113278644 (18: nrow: 524 rrow: 0)
   leaf: 0x6c07eb0 113278640 (19: nrow: 524 rrow: 0)
   leaf: 0x6c07eac 113278636 (20: nrow: 524 rrow: 0)
   leaf: 0x6809bae 109091758 (21: nrow: 524 rrow: 0)
   leaf: 0x6c07ea8 113278632 (22: nrow: 524 rrow: 0)
   leaf: 0x6c07ea4 113278628 (23: nrow: 524 rrow: 0)
   leaf: 0x6c07ea0 113278624 (24: nrow: 105 rrow: 105)
   leaf: 0x6c07e9c 113278620 (25: nrow: 129 rrow: 129)
   leaf: 0x6c07eb9 113278649 (26: nrow: 123 rrow: 123)
   leaf: 0x6809baa 109091754 (27: nrow: 246 rrow: 246)
   leaf: 0x6c07e98 113278616 (28: nrow: 246 rrow: 246)
   leaf: 0x6c07e94 113278612 (29: nrow: 246 rrow: 246)
   leaf: 0x6809ba6 109091750 (30: nrow: 246 rrow: 246)
   leaf: 0x6809bce 109091790 (31: nrow: 246 rrow: 246)
   leaf: 0x6809bca 109091786 (32: nrow: 246 rrow: 246)
   leaf: 0x6809c05 109091845 (33: nrow: 248 rrow: 248)
   leaf: 0x6809c01 109091841 (34: nrow: 246 rrow: 246)
   leaf: 0x6809bfd 109091837 (35: nrow: 246 rrow: 246)
   leaf: 0x6809bf9 109091833 (36: nrow: 246 rrow: 246)
   leaf: 0x6809bf5 109091829 (37: nrow: 246 rrow: 246)
   leaf: 0x6809bf1 109091825 (38: nrow: 246 rrow: 246)
   leaf: 0x6809bed 109091821 (39: nrow: 246 rrow: 246)
   leaf: 0x6809be9 109091817 (40: nrow: 246 rrow: 246)
   leaf: 0x6809be5 109091813 (41: nrow: 246 rrow: 246)
   leaf: 0x6809be1 109091809 (42: nrow: 246 rrow: 246)
   leaf: 0x6809bdd 109091805 (43: nrow: 246 rrow: 246)
   leaf: 0x6809bd9 109091801 (44: nrow: 246 rrow: 246)
   leaf: 0x6809bd5 109091797 (45: nrow: 246 rrow: 246)
   leaf: 0x6809bd1 109091793 (46: nrow: 248 rrow: 248)
   leaf: 0x6809bcd 109091789 (47: nrow: 246 rrow: 246)
   leaf: 0x6809bc9 109091785 (48: nrow: 246 rrow: 246)
   leaf: 0x6809c08 109091848 (49: nrow: 246 rrow: 246)
   leaf: 0x6809c04 109091844 (50: nrow: 246 rrow: 246)
   leaf: 0x6809c00 109091840 (51: nrow: 246 rrow: 246)
   leaf: 0x6809bfc 109091836 (52: nrow: 246 rrow: 246)
   leaf: 0x6809bf8 109091832 (53: nrow: 246 rrow: 246)
   leaf: 0x6809bf4 109091828 (54: nrow: 246 rrow: 246)
   leaf: 0x6809bf0 109091824 (55: nrow: 246 rrow: 246)
   leaf: 0x6809bec 109091820 (56: nrow: 246 rrow: 246)
   leaf: 0x6809be8 109091816 (57: nrow: 246 rrow: 246)
   leaf: 0x6809be4 109091812 (58: nrow: 246 rrow: 246)
   leaf: 0x6809be0 109091808 (59: nrow: 248 rrow: 248)
   leaf: 0x6809bdc 109091804 (60: nrow: 246 rrow: 246)
   leaf: 0x6809bd8 109091800 (61: nrow: 246 rrow: 246)
   leaf: 0x6809bd4 109091796 (62: nrow: 246 rrow: 246)
   leaf: 0x6809bd0 109091792 (63: nrow: 246 rrow: 246)
   leaf: 0x6809bcc 109091788 (64: nrow: 246 rrow: 246)
   leaf: 0x6809c07 109091847 (65: nrow: 246 rrow: 246)
   leaf: 0x6809c03 109091843 (66: nrow: 246 rrow: 246)
   leaf: 0x6809bff 109091839 (67: nrow: 246 rrow: 246)
   leaf: 0x6809bfb 109091835 (68: nrow: 246 rrow: 246)
   leaf: 0x6809bf7 109091831 (69: nrow: 246 rrow: 246)
   leaf: 0x6809bf3 109091827 (70: nrow: 246 rrow: 246)
   leaf: 0x6809bef 109091823 (71: nrow: 246 rrow: 246)
   leaf: 0x6809beb 109091819 (72: nrow: 248 rrow: 248)
   leaf: 0x6809be7 109091815 (73: nrow: 246 rrow: 246)
   leaf: 0x6809be3 109091811 (74: nrow: 246 rrow: 246)
   leaf: 0x6809bdf 109091807 (75: nrow: 246 rrow: 246)
   leaf: 0x6809bdb 109091803 (76: nrow: 246 rrow: 246)
   leaf: 0x6809bd7 109091799 (77: nrow: 246 rrow: 246)
   leaf: 0x6809bd3 109091795 (78: nrow: 246 rrow: 246)
   leaf: 0x6809bcf 109091791 (79: nrow: 246 rrow: 246)
   leaf: 0x6809bcb 109091787 (80: nrow: 246 rrow: 246)
   leaf: 0x6809c06 109091846 (81: nrow: 246 rrow: 246)
   leaf: 0x6809c02 109091842 (82: nrow: 246 rrow: 246)
   leaf: 0x6809bfe 109091838 (83: nrow: 246 rrow: 246)
   leaf: 0x6809bfa 109091834 (84: nrow: 246 rrow: 246)
   leaf: 0x6809ba2 109091746 (85: nrow: 129 rrow: 129)
   leaf: 0x6c07eb5 113278645 (86: nrow: 123 rrow: 123)
   leaf: 0x6809bf6 109091830 (87: nrow: 246 rrow: 246)
   leaf: 0x6809bf2 109091826 (88: nrow: 246 rrow: 246)
   leaf: 0x6809bee 109091822 (89: nrow: 246 rrow: 246)
   leaf: 0x6809bea 109091818 (90: nrow: 246 rrow: 246)
   leaf: 0x6809b9e 109091742 (91: nrow: 246 rrow: 246)
   leaf: 0x6809be6 109091814 (92: nrow: 246 rrow: 246)
   leaf: 0x6809be2 109091810 (93: nrow: 246 rrow: 246)
   leaf: 0x6809bde 109091806 (94: nrow: 246 rrow: 246)
   leaf: 0x6809bda 109091802 (95: nrow: 246 rrow: 246)
   leaf: 0x6809b9a 109091738 (96: nrow: 246 rrow: 246)
   leaf: 0x6809bd6 109091798 (97: nrow: 246 rrow: 246)
   leaf: 0x6809bd2 109091794 (98: nrow: 246 rrow: 246)
----- end tree dump

index full scan     读取的是 0x6c07ea0 这个块  
读取顺序:首先定位到索引的root block、然后到branch block(如果有的话)、再定位到第一个leaf block, 然后根据leaf block的双向链表顺序读取。
结论:它所读取的块都是有顺序的,也是经过排序的。FS 数据应该是从头开始的

index fast full scan读取的是 0x6809b9a 这个块  
读取顺序: 从段头开始,读取包含位图块、root block、所有的branch block、leaf block,读取的顺序完全有物理存储位置决定,并采取多块读,每次读取db_file_multiblock_read_count个块
结论:也就是包含数据的物理存储位置最前的块。    FFS数据应该不是从头开始的

--9.3 分别看一下这两个块的内容

FS: 0x6c07ea0 =十进制的113278624
FFS:0x6809b9a =十进制的109091738

SQL> select dbms_utility.data_block_address_file(113278624) "file",dbms_utility.data_block_address_block(113278624) "block"  from dual;

      file      block
---------- ----------
        27      32416
FS: 文件号 27 快号  32416

SQL> select dbms_utility.data_block_address_file(109091738) "file",dbms_utility.data_block_address_block(109091738)"block"  from dual;

      file      block
---------- ----------
        26      39834
FFS: 文件号 26 块号 39834

--9.4 dump该数据块
SQL> alter system dump datafile 26 block 39834;
block 39834的前10行
row#0[4591] flag: -----, lock: 2
col 0; len 4; (4):  c3 07 3f 43
col 1; len 6; (6):  02 81 71 f6 00 36
row#1[4605] flag: -----, lock: 2
col 0; len 4; (4):  c3 07 3f 44
col 1; len 6; (6):  02 81 71 f6 00 35
row#2[4619] flag: -----, lock: 2
col 0; len 4; (4):  c3 07 3f 45
col 1; len 6; (6):  02 81 71 f6 00 34
row#3[4633] flag: -----, lock: 2
col 0; len 4; (4):  c3 07 3f 46
col 1; len 6; (6):  02 81 71 f6 00 33
row#4[4647] flag: -----, lock: 2
col 0; len 4; (4):  c3 07 3f 47
col 1; len 6; (6):  02 81 71 f6 00 32
row#5[4661] flag: -----, lock: 2
col 0; len 4; (4):  c3 07 3f 48
col 1; len 6; (6):  02 81 71 f6 00 31
row#6[4675] flag: -----, lock: 2
col 0; len 4; (4):  c3 07 3f 49
col 1; len 6; (6):  02 81 71 f6 00 30
row#7[4689] flag: -----, lock: 2
col 0; len 4; (4):  c3 07 3f 4a
col 1; len 6; (6):  02 81 71 f6 00 2f
row#8[4703] flag: -----, lock: 2
col 0; len 4; (4):  c3 07 3f 4b
col 1; len 6; (6):  02 81 71 f6 00 2e
row#9[4717] flag: -----, lock: 2
col 0; len 4; (4):  c3 07 3f 4c
col 1; len 6; (6):  02 81 71 f6 00 2d

SQL> alter system dump datafile 27 block 32416;
block 32416的前10行  
row#0[6564] flag: -----, lock: 2
col 0; len 4; (4):  c3 02 07 11
col 1; len 6; (6):  07 00 7c 20 00 2b
row#1[6578] flag: -----, lock: 2
col 0; len 4; (4):  c3 02 16 4e
col 1; len 6; (6):  07 00 7c 20 00 2a
row#2[6592] flag: -----, lock: 2
col 0; len 4; (4):  c3 02 16 4f
col 1; len 6; (6):  07 00 7c 20 00 29
row#3[6606] flag: -----, lock: 2
col 0; len 4; (4):  c3 02 16 50
col 1; len 6; (6):  07 00 7c 20 00 28
row#4[6620] flag: -----, lock: 2
col 0; len 4; (4):  c3 02 18 02
col 1; len 6; (6):  07 00 7c 20 00 27
row#5[6634] flag: -----, lock: 2
col 0; len 4; (4):  c3 02 23 60
col 1; len 6; (6):  07 00 7c 20 00 26
row#6[6648] flag: -----, lock: 2
col 0; len 4; (4):  c3 02 24 25
col 1; len 6; (6):  07 00 7c 20 00 25
row#7[6662] flag: -----, lock: 2
col 0; len 4; (4):  c3 02 24 28
col 1; len 6; (6):  07 00 7c 20 00 24
row#8[6676] flag: -----, lock: 2
col 0; len 4; (4):  c3 02 28 18
col 1; len 6; (6):  07 00 7c 20 00 23
row#9[6690] flag: -----, lock: 2
col 0; len 4; (4):  c3 02 42 04
col 1; len 6; (6):  07 00 7c 20 00 22
 
 

--9.5 对照一下前面的结果集

block 32416的第一行为10616,数据内的存储格式应该为
SQL> select dump(10616,16) from dual;

DUMP(10616,16)
----------------------
Typ=2 Len=4: c3,2,7,11
确实等于dump block所看到的
row#0[6564] flag: -----, lock: 2
col 0; len 4; (4):  c3 02 07 11
col 1; len 6; (6):  07 00 7c 20 00 2b

再看block 39834的第1行
SQL> select dump(66266,16) from dual;

DUMP(66266,16)
-----------------------
Typ=2 Len=4: c3,7,3f,43
跟dump 的结果也一样
row#0[4591] flag: -----, lock: 2
col 0; len 4; (4):  c3 07 3f 43
col 1; len 6; (6):  02 81 71 f6 00 36
--9.6 结论:证明了上面所说的index full scan和index fast full scan的不同。

--10.我们也可以用10046事件去跟踪两者走的路径
--10.1.1 清空buffer_cache
SQL> ALTER SESSION SET EVENTS 'immediate trace name flush_cache';
(清空buffer cache,以便观看'db file sequential read','db file scattered read'事件)。

--10.1.2 打开10046事件
SQL> alter session set events'10046 trace name context forever,level 12';

Session altered.
--10.1.3 FFS 结果
SQL> select object_id from test where rownum<11;
    
 OBJECT_ID
----------
     66266
     66267
     66268
     66269
     66270
     66271
     66272
     66273
     66274
     66275
10 rows selected.

--10.1.4 关闭10046事件
SQL>  alter session set events'10046 trace name context off';

Session altered.

--10.1.5 观察该 FFS 的 trc文件
[oracle@csdbc udump]$ grep read cs-dbc_ora_15596.trc

Redo thread mounted by this instance: 1
WAIT #1: nam='db file sequential read' ela= 33 p1=26 p2=39820 p3=1
WAIT #1: nam='db file sequential read' ela= 21 p1=26 p2=39817 p3=1
WAIT #1: nam='db file sequential read' ela= 17 p1=26 p2=39819 p3=1
WAIT #1: nam='db file parallel read' ela= 53 p1=2 p2=2 p3=2
WAIT #1: nam='db file scattered read' ela= 466 p1=26 p2=39821 p3=16
最前面的'db file sequential read'是由于读段头等操作,我们来关注'db file scattered read'事件,因为index fast full scan是采用多块读,从39821开始读取db_file_multiblock_read_count个块(本例里设置为16)。我们关心的39834块正位于其中。

--10.2 再来看index full scan的10046 trace
--10.2.1 清空buffer cache
SQL> ALTER SESSION SET EVENTS 'immediate trace name flush_cache';
(清空buffer cache,以便观看'db file sequential read','db file scattered read'事件)。

--10.2.2 打开10046事件
SQL> alter session set events'10046 trace name context forever,level 12';

Session altered.

--10.2.3 FS结果
SQL> select/*+ index(test ind_TEST_ID)*/ object_id from test  where rownum<11;
 OBJECT_ID
----------
     10616
     12177
     12178
     12179
     12301
     13495
     13536
     13539
     13923
     16503
     
10 rows selected.

--10.2.4 关闭10046事件
SQL>  alter session set events'10046 trace name context off';

Session altered.

--10.2.5 观察该 FS 的 trc文件  
[oracle@csdbc udump]$ grep read cs-dbc_ora_15609.trc
Redo thread mounted by this instance: 1
WAIT #1: nam='db file sequential read' ela= 49 p1=26 p2=39821 p3=1
root block,正是先前索引树dump里面的 0x6809b8d
WAIT #1: nam='db file sequential read' ela= 32 p1=26 p2=39830 p3=1
WAIT #1: nam='db file sequential read' ela= 40 p1=27 p2=32449 p3=1
WAIT #1: nam='db file sequential read' ela= 35 p1=27 p2=32445 p3=1
WAIT #1: nam='db file sequential read' ela= 28 p1=27 p2=32433 p3=1
WAIT #1: nam='db file sequential read' ela= 19 p1=27 p2=32429 p3=1
WAIT #1: nam='db file sequential read' ela= 34 p1=27 p2=32425 p3=1
WAIT #1: nam='db file sequential read' ela= 32 p1=27 p2=32421 p3=1
WAIT #1: nam='db file sequential read' ela= 33 p1=27 p2=32417 p3=1
WAIT #1: nam='db file sequential read' ela= 29 p1=27 p2=32413 p3=1
WAIT #1: nam='db file sequential read' ela= 37 p1=27 p2=32409 p3=1
WAIT #1: nam='db file sequential read' ela= 32 p1=27 p2=32405 p3=1
WAIT #1: nam='db file sequential read' ela= 35 p1=27 p2=32401 p3=1
WAIT #1: nam='db file sequential read' ela= 34 p1=27 p2=32397 p3=1
WAIT #1: nam='db file sequential read' ela= 31 p1=27 p2=32456 p3=1
WAIT #1: nam='db file sequential read' ela= 29 p1=27 p2=32452 p3=1
WAIT #1: nam='db file sequential read' ela= 31 p1=27 p2=32448 p3=1
WAIT #1: nam='db file sequential read' ela= 30 p1=27 p2=32444 p3=1
WAIT #1: nam='db file sequential read' ela= 38 p1=26 p2=39858 p3=1
WAIT #1: nam='db file sequential read' ela= 31 p1=27 p2=32440 p3=1
WAIT #1: nam='db file sequential read' ela= 32 p1=27 p2=32436 p3=1
WAIT #1: nam='db file sequential read' ela= 35 p1=27 p2=32432 p3=1
WAIT #1: nam='db file sequential read' ela= 31 p1=27 p2=32428 p3=1
WAIT #1: nam='db file sequential read' ela= 29 p1=26 p2=39854 p3=1
WAIT #1: nam='db file sequential read' ela= 36 p1=27 p2=32424 p3=1
WAIT #1: nam='db file sequential read' ela= 32 p1=27 p2=32420 p3=1
WAIT #1: nam='db file sequential read' ela= 36 p1=27 p2=32416 p3=1

--10.3 结论
index full scan走的路径正是文章开始所提到的定位到root block,然后根据leaf block链表一路读取块。
看到这里大家应该比较了解index full scan 和index fast full scan的区别了。

--11. 最后补充一下 index full scan 和 index fast full scan 在排序上的不同。

--11.1打开trace跟踪
SQL> set autotrace trace;

--11.2 FS 结果验证
SQL> select object_id from test order by object_id;

17837 rows selected.

Execution Plan
----------------------------------------------------------
   0      SELECT STATEMENT Optimizer=CHOOSE (Cost=41 Card=17837 Bytes=71348)
   1    0   INDEX (FULL SCAN) OF 'IND_TEST_ID' (NON-UNIQUE) (Cost=101 Card=17837 Bytes=71348)
由于有排序所以oracle自动选择了index full scan避免了排序。那么强制用index fast full scan呢?

 --11.3 FFS结果验证
SQL> select/*+ index_ffs(test ind_test_id)*/object_id from test order by object_id;
17837 rows selected.

Execution Plan
----------------------------------------------------------
   0      SELECT STATEMENT Optimizer=CHOOSE (Cost=59 Card=17837 Bytes=71348)
   1    0   SORT (ORDER BY) (Cost=59 Card=17837 Bytes=71348)
   2    1     INDEX (FAST FULL SCAN) OF 'IND_TEST_ID' (NON-UNIQUE) (Cost=11 Card=17837 Bytes=71348)

结论:
index full scan 会自动的执行 sort (order by)
index fast full scan会多一步 sort (order by)

--------------------------------------------------------------------------------
本文原作者
WangHai(要了解他请访问他的Blog). 本文版权归原作者所有。转载请注明作者及出处!

----- begin tree dump
branch: 0x10000f3 16777459 (0: nrow: 255, level: 1)
   leaf: 0x10000f7 16777463 (-1: nrow: 289 rrow: 289)
   leaf: 0x100447f 16794751 (0: nrow: 246 rrow: 246)
   leaf: 0x100447b 16794747 (1: nrow: 246 rrow: 246)
   leaf: 0x1004477 16794743 (2: nrow: 246 rrow: 246)
   leaf: 0x1004473 16794739 (3: nrow: 246 rrow: 246)
   leaf: 0x100446f 16794735 (4: nrow: 246 rrow: 246)
   leaf: 0x100446b 16794731 (5: nrow: 246 rrow: 246)
                       .
                       .
                       .
   leaf: 0x100024c 16777804 (249: nrow: 246 rrow: 246)
   leaf: 0x100024b 16777803 (250: nrow: 251 rrow: 251)
   leaf: 0x10000f6 16777462 (251: nrow: 246 rrow: 246)
   leaf: 0x10000f5 16777461 (252: nrow: 246 rrow: 246)
   leaf: 0x10000f4 16777460 (253: nrow: 246 rrow: 246)
----- end tree dump                       

####################################################################
结构说明:
branch:表示该数据块是 枝节点数据块
leaf: 表示该数据块是 叶节点数据块
0x10000f3: 对应当前数据块的十六进制地址
16777459:对应当前数据块的十进制地址
-1: 表示当前数据块的编号,编号起始是-1。以上图示 该索引共包含 1个枝节点数据块, 253 - (0)- (-1) =255个叶子节点数据块
nrow: 289 :表示该索引数据块中总的行数,包含被删除的行
rrow: 289 :表示该索引数据块中实际存在有效行数
####################################################################
表示共有255个索引块
branch:表示为根节点 1 个
leaf:表示为叶子节点 255 个.

SQL> SELECT NAME, BLOCKS, HEIGHT,LF_ROWS, LF_BLKS, BR_ROWS, BR_BLKS, BTREE_SPACE, USED_SPACE FROM INDEX_STATS WHERE NAME='IND_TEST_ID';

NAME                               BLOCKS     HEIGHT    LF_ROWS    LF_BLKS    BR_ROWS    BR_BLKS BTREE_SPACE USED_SPACE
------------------------------ ---------- ---------- ---------- ---------- ---------- ---------- ----------- ----------
IND_TEST_ID                           384          2      62862        255        254          1     2047008    1008179
--完全符合以上 dump的结果

SQL> select dbms_utility.data_block_address_file(16777459),dbms_utility.data_block_address_block(16777459) from dual;

DBMS_UTILITY.DATA_BLOCK_ADDRESS_FILE(16777459) DBMS_UTILITY.DATA_BLOCK_ADDRESS_BLOCK(16777459)
---------------------------------------------- -----------------------------------------------
                                             4                                             243

243数据块  无从验证

dump 枝节点
Branch block dump
=================
结构说明:

header address 140343647131724=0x7fa44d3bd84c
kdxcolev 1              该节点到叶节点的深度(index level, 0表示是leaf block  1 表示是 branch block)
KDXCOLEV Flags = - - -   is converted=Y 内部操作代码
kdxcolok 1              是否有事务lock了这个branch block,如果有 有多少事务
kdxcoopc 0x81: opcode=1: iot flags=--- is converted=Y
kdxconco 2              索引列数量  ???
kdxcosdc 1              索引结构改变次数
kdxconro 254            索引记录数量BR_ROWS
kdxcofbo 536=0x218      空闲空间开始偏移量
kdxcofeo 5542=0x15a6    空闲空间结束偏移量
kdxcoavs 5006           所提供的空闲空间
kdxbrlmc 16777463=0x10000f7
kdxbrsno 0              最后一次被更改的索引条目
kdxbrbksz 8056          使用的数据块空间
kdxbr2urrc 0
kdxlespl 0              在数据块被cleaned out时,还未进行commit的数量
kdxlende 122            被删除索引记录的数量
kdxlenxt 67120396=0x4002d0c  下一个链接数据块的地址
kdxleprv 0=0x0          上一个链接数据块地址
kdxledsz 0              被删除的空间大小
kdxlebksz 8036          使用的数据块空间

其他注释
kdxcolev: index level (0 represents leaf blocks)
kdxcolok: denotes whether structural block transaction is occurring
kdxcoopc: internal operation code
kdxconco: index column count
kdxcosdc: count of index structural changes involving block
kdxconro: number of index entries (does not include kdxbrlmc pointer)
kdxcofbo: offset to beginning of free space within block
kdxcofeo: offset to the end of free space (ie. first portion of block containing index data)
kdxcoavs: available space in block (effectively area between the two fields above)

http://blog.csdn.net/robinson1988/article/details/7312683?locationNum=1&fps=1