Index Range Scan成本 Histogram 和 10053
原貼發表在ITPUB
http://www.itpub.net/581612.html
試驗環境:
Linux AS4 + 10.2.0.1.0 - 64bit Production
為了模擬資料庫物件佔用多個block,故設定較高pctfree.
SQL> create table irs pctfree 80 tablespace users as
2 select rownum id,a.* from all_objects a;
Table created.
SQL> alter table irs add constraint irs_id_pk primary key(id);
Table altered.
SQL> create index irs_owner_idx on irs(owner) tablespace indx pctfree 80;
Index created.
SQL> show parameter optimizer_index
NAME TYPE VALUE
------------------------------------ ----------- ------------------------------
optimizer_index_caching integer 0
optimizer_index_cost_adj integer 100
獲取表和索引的統計資訊
SQL> analyze table irs compute statistics for table for all indexes;
Table analyzed.
獲取列的histogram資訊
SQL> analyze table irs compute statistics for all indexed columns;
Table analyzed.
[@more@]SQL> select owner,count(*) from irs
2 group by owner;
OWNER COUNT(*)
------------------------------ ----------
MDSYS 859
DMSYS 189
TSMSYS 2
CTXSYS 338
OLAPSYS 718
OUTLN 7
PUBLIC 20079
EXFSYS 279
SCOTT 6
SYSTEM 425
DBSNMP 46
OWNER COUNT(*)
------------------------------ ----------
LIYONG 2
ORDPLUGINS 10
ORDSYS 1669
SYSMAN 1291
XDB 346
CWT 310
PERFSTAT 139
SI_INFORMTN_SCHEMA 8
SYS 23134
WMSYS 232
21 rows selected.
SQL> select NUM_ROWS,BLOCKS,EMPTY_BLOCKS from dba_tables
2 where table_name='IRS';
NUM_ROWS BLOCKS EMPTY_BLOCKS
---------- ---------- ------------
50089 3423 33
SQL> select BLEVEL,LEAF_BLOCKS,DISTINCT_KEYS,CLUSTERING_FACTOR from dba_indexes
2 where INDEX_NAME='IRS_OWNER_IDX';
BLEVEL LEAF_BLOCKS DISTINCT_KEYS CLUSTERING_FACTOR
---------- ----------- ------------- -----------------
2 570 21 5890
SQL> select DENSITY,NUM_DISTINCT,HISTOGRAM from dba_tab_columns
2 where OWNER='LIYONG'
3 and TABLE_NAME='IRS'
4 and COLUMN_NAME='OWNER';
DENSITY NUM_DISTINCT HISTOGRAM
---------- ------------ ---------------
9.9822E-06 21 FREQUENCY
SQL> alter session set events '10053 trace name context forever ,level 2';
Session altered.
SQL> select * from irs where owner='SYSMAN';
1291 rows selected.
SQL> alter session set events '10053 trace name context off';
10053內容擷取
***************************************
BASE STATISTICAL INFORMATION
***********************
Table Stats::
Table: IRS Alias: IRS
#Rows: 50089 #Blks: 3423 AvgRowLen: 102.00
Index Stats::
Index: IRS_ID_PK Col#: 1
LVLS: 1 #LB: 104 #DK: 50089 LB/K: 1.00 DB/K: 1.00 CLUF: 3361.00
Index: IRS_OWNER_IDX Col#: 2
LVLS: 2 #LB: 570 #DK: 21 LB/K: 27.00 DB/K: 280.00 CLUF: 5890.00
***************************************
SINGLE TABLE ACCESS PATH
Column (#2): OWNER(VARCHAR2)
AvgLen: 5.00 NDV: 21 Nulls: 0 Density: 9.9822e-06
這裡看到OWNER列的Density: 9.9822e-06
Histogram: Freq #Bkts: 21 UncompBkts: 50089 EndPtVals: 21
Table: IRS Alias: IRS
Card: Original: 50089 Rounded: 1291 Computed: 1291.00 Non Adjusted: 1291.00 --這裡可以看到CBO根據列的histogram資訊統計出Card集的相關資訊,
SQL> select 1291/50089 from dual;
1291/50089
----------
.025774122
這樣可以準確算出effective index selectivity為0.025774122
Access Path: TableScan --全表掃描的代價為750
Cost: 754.17 Resp: 754.17 Degree: 0
Cost_io: 750.00 Cost_cpu: 35706109
Resp_io: 750.00 Resp_cpu: 35706109
Access Path: index (AllEqRange)
Index: IRS_OWNER_IDX
resc_io: 169.00 resc_cpu: 1991033
ix_sel: 0.025774 ix_sel_with_filters: 0.025774
Cost: 169.23 Resp: 169.23 Degree: 1
Best:: AccessPath: IndexRange Index: IRS_OWNER_IDX
Cost: 169.23 Degree: 1 Resp: 169.23 Card: 1291.00 Bytes: 0
根據索引掃描成本計算公式
cost = (cost(INDEX RANGE SCAN)+cost(TABLE ACCESS BY INDEX ROWID)) * optimizer_index_cost_adj%
= blevel +ceiling(leaf_blocks * effective index selectivity) + -- cost(INDEX RANGE SCAN)
ceiling(clustering_factor * effective table selectivity) --cost(TABLE ACCESS BY INDEX ROWID)
= 2 + ceil(570*0.025774) + ceil(5890*0.025774)
= 2 + 15 (17) -- cost(INDEX RANGE SCAN)
+ 152 --cost(TABLE ACCESS BY INDEX ROWID)
= 169
----------------------------------------------------+-----------------------------------+
| Id | Operation | Name | Rows | Bytes | Cost | Time |
----------------------------------------------------+-----------------------------------+
| 0 | SELECT STATEMENT | | | | 169 | |
| 1 | TABLE ACCESS BY INDEX ROWID | IRS | 1291 | 129K | 169 | 00:00:03 |
| 2 | INDEX RANGE SCAN | IRS_OWNER_IDX| 1291 | | 17 | 00:00:01 |
----------------------------------------------------+-----------------------------------+
解釋一下整個sql執行過程:
1 首先根據謂詞 table_name='IRS'做INDEX RANGE SCAN,找到1291個Index Entrys,整個這個過程的代價為17.
2 Oracle根據Index Entrys中Rowid掃描原表中的blocks,獲取到1291條記錄. 整個TABLE ACCESS BY INDEX ROWID的代價為169-17=152.
3 TABLE ACCESS BY INDEX ROWID過程中,表的blocks被Server process讀入到SGA的DB Cache中,讀入的資料量近似的等於129K.(Oracle讀取一行記錄會讀整個block;命中率等因素)
SQL> select AVG_ROW_LEN,BLOCKS from dba_tables
2 where table_name='IRS';
AVG_ROW_LEN BLOCKS
----------- ----------
102 3423
SQL> select 102*1291/1024 from dual;
102*1291/1024
-------------
128.595703
關於索引的索引聚簇因子CLUF演算法下次再作探討.
索引掃描成本還和另一個引數有很大關係.先前eygle老大已經發表過專門的帖子.
我這裡拿來主義.
SQL> alter session set optimizer_index_cost_adj=40;
Session altered.
SQL> set autotrace traceonly
SQL> set linesize 150
SQL> select * from irs where owner='SYSMAN';
1291 rows selected.
Execution Plan
----------------------------------------------------------
Plan hash value: 4071038474
---------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
---------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1291 | 128K| 68 (0)| 00:00:01 |
| 1 | TABLE ACCESS BY INDEX ROWID| IRS | 1291 | 128K| 68 (0)| 00:00:01 |
|* 2 | INDEX RANGE SCAN | IRS_OWNER_IDX | 1291 | | 7 (0)| 00:00:01 |
---------------------------------------------------------------------------------------------
可以看到 Cost=68=ceil(169*0.4)
附:
在沒有列的histogram情況下的成本計算,我們看到偏差很大.CBO無法準確獲取到Card集的資訊,所以Oracle只能估算.
10053內容擷取
***************************************
BASE STATISTICAL INFORMATION
***********************
Table Stats::
Table: IRS Alias: IRS
#Rows: 50089 #Blks: 3423 AvgRowLen: 102.00
Index Stats::
Index: IRS_ID_PK Col#: 1
LVLS: 1 #LB: 104 #DK: 50089 LB/K: 1.00 DB/K: 1.00 CLUF: 3361.00
Index: IRS_OWNER_IDX Col#: 2
LVLS: 2 #LB: 570 (索引LEAF_BLOCKS個數) #DK: 21 (索引distinct key個數) LB/K: 27.00 DB/K: 280.00 CLUF: 5890.00 (索引聚簇因子,稍後會有詳細介紹)
***************************************
SINGLE TABLE ACCESS PATH
Column (#2): OWNER(VARCHAR2) NO STATISTICS (using defaults)
AvgLen: 30.00 NDV: 1565 Nulls: 0 Density: 6.3886e-04
Table: IRS Alias: IRS
Card: Original: 50089 Rounded: 501 Computed: 500.89 Non Adjusted: 500.89
Access Path: TableScan
Cost: 754.15 Resp: 754.15 Degree: 0
Cost_io: 750.00 Cost_cpu: 35516509
Resp_io: 750.00 Resp_cpu: 35516509
Access Path: index (AllEqGuess) -- 我們注意這裡索引的訪問路徑為index (AllEqGuess),我猜想是由於沒有OWNER列的Histogram,Oracle無法計算OWNER列的selectivity造成的
Index: IRS_OWNER_IDX
resc_io: 53.00 resc_cpu: 500046
ix_sel: 0.004 ix_sel_with_filters: 0.004
Cost: 53.06 Resp: 53.06 Degree: 1
Best:: AccessPath: IndexRange Index: IRS_OWNER_IDX
Cost: 53.06 Degree: 1 Resp: 53.06 Card: 500.89 Bytes: 0
根據10053 Oracle評估出:
cost(TableScan)=750
cost(index)=53.06
所以選擇索引掃描為執行計劃.
----------------------------------------------------+-----------------------------------+
| Id | Operation | Name | Rows | Bytes | Cost | Time |
----------------------------------------------------+-----------------------------------+
| 0 | SELECT STATEMENT | | | | 53 | |
| 1 | TABLE ACCESS BY INDEX ROWID | IRS | 501 | 50K | 53 | 00:00:01 |
| 2 | INDEX RANGE SCAN | IRS_OWNER_IDX| 200 | | 29 | 00:00:01 |
----------------------------------------------------+-----------------------------------+
根據索引掃描成本計算公式
cost = (cost(INDEX RANGE SCAN)+cost(TABLE ACCESS BY INDEX ROWID)) * optimizer_index_cost_adj%
= blevel +ceiling(leaf_blocks * effective index selectivity) + -- cost(INDEX RANGE SCAN)
ceiling(clustering_factor * effective table selectivity) --cost(TABLE ACCESS BY INDEX ROWID)
= 2 + ceil(570*0.004) + ceil(5890*0.004)
= 2 + 3 + 24
= 29
來自 “ ITPUB部落格 ” ,連結:http://blog.itpub.net/76065/viewspace-846417/,如需轉載,請註明出處,否則將追究法律責任。
相關文章
- histogram與10053(zt)Histogram
- [20230908]Oracle Index Range Scan with LIKE Condition on Wildcard '_'.txtOracleIndex
- PostgreSQL DBA(119) - pgAdmin(LIMIT:Index Scan vs Bitmap Index Scan)SQLMITIndex
- C# 使用 Index 和 Range 簡化集合操作C#Index
- [20180725]index skip-scan operation.txtIndex
- 20180316不使用INDEX FULL SCAN (MIN/MAX)Index
- Oracle vs PostgreSQL Develop(31) - Index Only ScanOracleSQLdevIndex
- 簡單談談MySQL的loose index scanMySqlIndex
- 說說C# 8.0 新增功能Index和Range的^0是什麼?C#Index
- python爬蟲 -IndexError: list index out of range報錯Python爬蟲IndexError
- [20181201]奇怪的INDEX SKIP SCAN執行計劃.txtIndex
- 【最佳化】INDEX FULL SCAN (MIN/MAX)訪問路徑Index
- 【TUNE_ORACLE】列出走了INDEX FULL SCAN的SQL參考OracleIndexSQL
- 【TUNE_ORACLE】列出走了INDEX SKIP SCAN的SQL參考OracleIndexSQL
- 隨筆:MySQL:eq_range_index_dive_limit 索引下探介面MySqlIndexMIT索引
- 關於Pyinstaller在打包Streamlit程式時遇到的IndexError:tuple index out of rangeIndexError
- 【效能】解讀10053檔案
- skim、scan和browse的區別
- django中出現 錯誤 Errno 10053Django
- java.sql.SQLException: Parameter index out of range (3 > number of parameters, which is 2)的解決方法JavaSQLExceptionIndex
- SCAN
- JavaScript 中的 Range 和 Selection 物件JavaScript物件
- elasticsearch 之 histogram 直方圖聚合ElasticsearchHistogram直方圖
- elasticsearch 聚合之 date_histogram 聚合ElasticsearchHistogram
- 基於 range 的 for 迴圈和 auto
- INDEX REBUILD和INDEX REORGANIZE和UPDATE STATISTICS是否涉及Sch-M的案例分析IndexRebuild
- Redis中KEYS和SCAN命令的區別和建議Redis
- [20190703]12c Hybrid histogram.txtHistogram
- Python:range、np.arange和np.linspacePython
- 新增SCAN IP
- RAC 增加SCAN IP
- HTML input rangeHTML
- Range Sparse Net
- Range Minimum Sum
- python-rangePython
- for range 作用域
- Python學習系列之 xrange和range的區別!Python
- 阿里雲內容安全介面 敏感詞 green scan、圖片 image scan阿里
- http斷點續傳原理:http頭 Range、Content-RangeHTTP斷點