Index compression–working out the compression number

Richard Foote did a series of informative posts on Index Compression which concludes that there is whole lot of positives about index compression, and very little negatives.  But obviously one critical thing is choosing the right number of leading columns to compress. Is it just “take a guess?” .  Luckily, Oracle has taken the guesswork out of it.

The ANALYZE command on an index can let you find the optimial compression count.  When you do an ANALYZE INDEX command, two critical columns are populated:

SQL> desc index_stats
 Name                          Null?    Type
 ----------------------------- -------- --------------------
 HEIGHT                                 NUMBER
 BLOCKS                                 NUMBER
 NAME                                   VARCHAR2(128)
 PARTITION_NAME                         VARCHAR2(128)
 LF_ROWS                                NUMBER
 LF_BLKS                                NUMBER
 LF_ROWS_LEN                            NUMBER
 LF_BLK_LEN                             NUMBER
 BR_ROWS                                NUMBER
 BR_BLKS                                NUMBER
 BR_ROWS_LEN                            NUMBER
 BR_BLK_LEN                             NUMBER
 DEL_LF_ROWS                            NUMBER
 DEL_LF_ROWS_LEN                        NUMBER
 DISTINCT_KEYS                          NUMBER
 MOST_REPEATED_KEY                      NUMBER
 BTREE_SPACE                            NUMBER
 USED_SPACE                             NUMBER
 PCT_USED                               NUMBER
 ROWS_PER_KEY                           NUMBER
 BLKS_GETS_PER_ACCESS                   NUMBER
 PRE_ROWS                               NUMBER
 PRE_ROWS_LEN                           NUMBER
 OPT_CMPR_COUNT                         NUMBER
 OPT_CMPR_PCTSAVE                       NUMBER

Lets look at an example – we’ll create a table with 10 columns with all sorts of interesting distributions

SQL> drop table T purge;

Table dropped.

SQL> create table T as
 2   select
 3     rownum r01,
 4     mod(rownum,10) r02,
 5     mod(rownum,100) r03,
 6     mod(rownum,1000) r04,
 7     trunc(rownum/10) r05,
 8     trunc(rownum/100) r06,
 9     trunc(dbms_random.value(1,100)) r07,
10     trunc(dbms_random.value(1,1000)) r08  ,
11     trunc(mod(rownum,100)/10) r09,
12     mod(trunc(rownum/10),100) r10
13  from
14    ( select 1 from dual connect by level <= 1000 ),
15    ( select 1 from dual connect by level <= 1000 )
16  /

Table created.

We’ve used a technique described here to generate 1,000,000 rows.

Now with some SQL trickery, we can generate every possible combination of 3 column indexes for this table.

SQL> with inds as ( select rownum r from dual connect by level <= 10 )
  2  select  '(r'||i1.r||',r'||i2.r||',r'||i3.r||')' ix_cols
  3  from inds i1, inds i2, inds i3
  4  where i1.r != i2.r
  5  and   i2.r != i3.r
  6  and   i1.r != i3.r
  7  /


So, now we’ll create a table called IND_STATS to hold the results of our ANALYZE command, because every time you issue ANALYZE INDEX the INDEX_STATS view is cleared.

SQL> create table IND_STATS as select name, OPT_CMPR_COUNT,  OPT_CMPR_PCTSAVE from index_stats where 1=0;

Table created.

And now we’ll just loop around all 720 potential indexes and work out the optimal compression.

SQL> begin
  2  for i in (
  3    with inds as ( select rownum r from dual connect by level <= 10 )
  4    select 'IX_'||i1.r||'_'||i2.r||'_'||i3.r ix_name,
  5           '(r'||to_char(i1.r,'fm00')||',r'||to_char(i2.r,'fm00')||',r'||to_char(i3.r,'fm00')||')' ix_cols
  6    from inds i1, inds i2, inds i3
  7    where i1.r != i2.r
  8    and   i2.r != i3.r
  9    and   i1.r != i3.r
 10  )
 11  loop
 12    dbms_application_info.set_client_info(i.ix_name);
 13    begin
 14      execute immediate 'drop index IX';
 15    exception
 16      when others then null;
 17    end;
 18    execute immediate 'create index IX on t '||i.ix_cols;
 19    execute immediate 'analyze index IX validate structure';
 20    insert into IND_STATS select i.ix_cols, OPT_CMPR_COUNT,  OPT_CMPR_PCTSAVE from index_stats;
 21    commit;
 22  end loop;
 23  end;
 24  /

PL/SQL procedure successfully completed.

So now we can take a look at the compression recommendations for all of our potential 3 column indexes. (Note: I’m not suggesting you would actually index all 720 combinations ! Smile)

SQL> select * from ind_stats;

NAME                                     OPT_CMPR_COUNT OPT_CMPR_PCTSAVE
---------------------------------------- -------------- ----------------
(r01,r02,r03)                                         0                0
(r01,r02,r04)                                         0                0
(r01,r02,r05)                                         0                0
(r01,r02,r06)                                         0                0
(r01,r02,r07)                                         0                0
(r01,r02,r08)                                         0                0
(r01,r02,r09)                                         0                0


(r02,r06,r05)                                         2               24
(r02,r06,r07)                                         2               26
(r02,r06,r08)                                         2               25
(r02,r06,r09)                                         2               26
(r02,r06,r10)                                         2               26
(r02,r07,r01)                                         2               26
(r02,r07,r03)                                         3               43
(r02,r07,r04)                                         3               39
(r02,r07,r05)                                         2               26
(r02,r07,r06)                                         2               28
(r02,r07,r08)                                         2               28
(r02,r07,r09)                                         3               43
(r02,r07,r10)                                         3               37
(r02,r08,r01)                                         2               29
(r02,r08,r03)                                         3               39

You can see that some indexes probably wont benefit at all from compression, whereas for others, ALL columns become candidates for compression and might save nearly half the size of index.

So you dont need to guess at the compression for your indexes – you can work it out using ANALYZE.


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