When to Rebuild a B-Tree Index

Posted By Sagar Patil

You have to periodically check your indexes to see if they become skewed and, therefore, good candidates for rebuild.

A skewed index has many records clumped close together on the index tree due to their similar indexed values. When an index is skewed, parts of an index are accessed more frequently than others. As a result, disk contention may occur, creating a bottleneck in performance. It is important to periodically examine your indexes to determine if they have become skewed and might need to be rebuilt.

Here is a sample procedure on how to identify the skewed indexes:

1. Gather statistics on your indexes. For large indexes (over one hundred
thousand records in the underlying table), use ESTIMATE instead of COMPUTE STATISTICS.

For example:   SQL> analyze index A1_PK compute statistics;
Index analyzed.

2. Run the script given below – index_check.sql – to find out how skewed each index is.

This query checks on all indexes that belong to user SCOTT:

SQL> select index_name, blevel,
decode(blevel,0,'OK BLEVEL',1,'OK BLEVEL',
from dba_indexes
where owner='SCOTT';

INDEX_NAME                                BLEVEL  OK
----------------------------------------  ------  ---- 
A1_PK                                     BLEVEL  HIGH
A1_UK                                     BLEVEL  HIGH
BUDVERPORT_BV_FK_I                        2       OK BLEVEL
BUDVERPORT_CHAR_CL_FK_I                   1       OK BLEVEL
BUDVERPORT_DIRCTE_FK_I                    3       OK BLEVEL
BUDVERPORT_FUND_TYPE_FK_I                 1       OK BLEVEL
BUDVERPORT_ORG_FK_I                       0       OK BLEVEL
BUDVERPORT_PL_TITLE_FK_I                  1       OK BLEVEL
BUDVERPORT_RDC_FK_I                       1       OK BLEVEL
S_LONGTEXT_ID_PK                          BLEVEL  HIGH
S_ORD_ID_PK                               BLEVEL  HIGH
S_PRODUCT_ID_PK                           BLEVEL  HIGH
S_PRODUCT_NAME_UK                         BLEVEL  HIGH
S_REGION_ID_PK                            BLEVEL  HIGH
S_REGION_NAME_UK                          BLEVEL  HIGH
S_TITLE_TITLE_PK                          BLEVEL  HIGH
S_WAREHOUSE_ID_PK                         BLEVEL  HIGH

3. The BLEVEL (or branch level) is part of the B-tree index format and relates to the number of times Oracle has to narrow its search on the index while searching for a particular record. In some cases, a separate disk hit is requested for each BLEVEL. Prior to 9i, if the BLEVEL is more than 4, it is recommended to rebuild the index. As database are getting bigger and bigger, BLEVEL may not be a good indicator of time to rebuild the index. BLEVEL > 4 may suggest an evaluation of whether the partitioning option could help you.

Note: If you do not analyze the index, the index_check.sql script will
show “BLEVEL HIGH” for such an index.

4. Gather more index statistics using the VALIDATE STRUCTURE option of the ANALYZE command to populate the INDEX_STATS virtual table. This table does not contain an OWNER column and assumes you are looking for statistics for indexes created by your active session only.

SQL> analyze index SCOTT.ORG_PK validate structure;
Index analyzed.

SQL> select DEL_LF_ROWS*100/decode(LF_ROWS, 0, 1, LF_ROWS) PCT_DELETED,
from index_stats  where NAME='&index_name';

Enter value for index_name: ORG_PK

———– —————
0 0

The PCT_DELETED column shows what percent of leaf entries (index entries) have been deleted and remain unfilled. The more deleted entries exist on an index, the more unbalanced the index becomes. If the PCT_DELETED is 20% or higher, the index is candidate for rebuilding. If you can afford to rebuild indexes more frequently, then do so if the value is higher than 10%. Leaving indexes with high PCT_DELETED without rebuild might cause excessive redo allocation on some systems.
The DISTINCTIVENESS column shows how often a value for the column(s) of the index is repeated on average.

For example, if a table has 10000 records and 9000 distinct SSN values, the formula would result in
(10000-9000) x 100 / 10000 = 10. This shows a good distribution of values.

If, however, the table has 10000 records and only 2 distinct SSN values, the formula would result in (10000-2) x 100 /10000 = 99.98. This shows that there are very few distinct values as a percentage of total records in the column. Such columns are not candidates for a rebuild but good candidates for bitmapped indexes.

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