Spatial space

One thing you (ought to) learn very early on in an Oracle career is that there are always cases you haven’t previously considered. It’s a feature that is frequently the downfall of “I found it on the internet” SQL.  Here’s one (heavily paraphrased) example that appeared on the OTN database forum a few days ago:

select table_name,round((blocks*8),2)||’kb’ “size” from user_tables where table_name = ‘MYTABLE’;

select table_name,round((num_rows*avg_row_len/1024),2)||’kb’ “size” from user_tables where table_name = ‘MYTABLE’;

The result from the first query is 704 kb,  the result from the second is 25.4 kb … fragmentation, rebuild, CTAS etc. etc.

The two queries are perfectly reasonable approximations (for an 8KB block size, with pctfree of zero) for the allocated space and actual data size for a basic heap table – and since the two values here don’t come close to matching it’s perfectly reasonable to consider doing something like a rebuild or shrink space to reclaim space and (perhaps) to improve performance.

In this case it doesn’t look as if the space reclaimed is likely to be huge (less than 1MB), on the other hand it’s probably not going to take much time to rebuild such a tiny table; it doesn’t seem likely that the rebuild could make a significant difference to performance (though apparently it did), but the act of rebuilding might cause execution plans to change for the better because new statistics might appear as the rebuild took place. The figures came from a test system, though, so maybe the table on the production system was much larger and the impact would be greater.

Being cautious about wasting time and introducing risk, I made a few comments about the question –  and learned that one of the columns was of type SDO_GEOMETRY. This makes a big difference about what to do next, because dbms_stats.gather_table_stats() doesn’t process such columns correctly, which results in a massive under-estimate for the avg_row_len (which is basically the sum of avg_col_len for the table). Here’s an example (run on 12c, based on some code taken from the 10gR2 manuals):

drop table cola_markets purge;

CREATE TABLE cola_markets (
  mkt_id NUMBER,
  name VARCHAR2(32),
  shape SDO_GEOMETRY);

INSERT INTO cola_markets VALUES(
  1,
  'cola_a',
  SDO_GEOMETRY(
    2003,  -- two-dimensional polygon
    NULL,
    NULL,
    SDO_ELEM_INFO_ARRAY(1,1003,3), -- one rectangle (1003 = exterior)
    SDO_ORDINATE_ARRAY(1,1, 5,7) -- only 2 points needed to
          -- define rectangle (lower left and upper right) with
          -- Cartesian-coordinate data
  )
);

insert into cola_markets select * from cola_markets;
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execute dbms_stats.gather_table_stats(user,'cola_markets')
select
	avg_row_len, num_rows, blocks,
	round(avg_row_len * num_rows / 7200,0) expected_blocks
from user_tables where table_name = 'COLA_MARKETS';

analyze table cola_markets compute statistics;
select
	avg_row_len, num_rows, blocks,
	round(avg_row_len * num_rows / 7200,0) expected_blocks
from user_tables where table_name = 'COLA_MARKETS';

If you care to count the number of times I execute the “insert as select” it’s 10, so the table ends up with 2^10 = 1024 rows. The 7,200 in the calculated column converts bytes to approximate blocks on the assumption of 8KB blocks and pctfree = 10. Here are the results following the two different methods for generating object statistics:

PL/SQL procedure successfully completed.

AVG_ROW_LEN   NUM_ROWS     BLOCKS EXPECTED_BLOCKS
----------- ---------- ---------- ---------------
         14       1024        124               2

Table analyzed.

AVG_ROW_LEN   NUM_ROWS     BLOCKS EXPECTED_BLOCKS
----------- ---------- ---------- ---------------
        109       1024        124              16

Where does the difference in Expected_blocks come from ? (The Blocks figures is 124 because I’ve used 1MB uniform extents – 128 block – under ASSM (which means 4 space management blocks at the start of the first extent.)

Here are the column lengths after the call to dbms_stats: as you can see the avg_row_len is the sum of avg_col_len.

select column_name, data_type, avg_col_len
from   user_tab_cols
where  table_name = 'COLA_MARKETS'
order by
        column_id
;

COLUMN_NAME          DATA_TYPE                AVG_COL_LEN
-------------------- ------------------------ -----------
MKT_ID               NUMBER                             3
NAME                 VARCHAR2                           7
SYS_NC00010$         SDO_ORDINATE_ARRAY
SHAPE                SDO_GEOMETRY
SYS_NC00008$         NUMBER                             0
SYS_NC00004$         NUMBER                             4
SYS_NC00005$         NUMBER                             0
SYS_NC00006$         NUMBER                             0
SYS_NC00007$         NUMBER                             0
SYS_NC00009$         SDO_ELEM_INFO_ARRAY

The figures from the analyze command are only slightly different, but fortunately the analyze command uses the row directory pointers to calculate the actual row allocation, so picks up information about the impact of inline varrays, LOBs, etc. that the dbms_stats call might not be able to handle.

COLUMN_NAME          DATA_TYPE                AVG_COL_LEN
-------------------- ------------------------ -----------
MKT_ID               NUMBER                             2
NAME                 VARCHAR2                           6
SYS_NC00010$         SDO_ORDINATE_ARRAY
SHAPE                SDO_GEOMETRY
SYS_NC00008$         NUMBER                             1
SYS_NC00004$         NUMBER                             3
SYS_NC00005$         NUMBER                             1
SYS_NC00006$         NUMBER                             1
SYS_NC00007$         NUMBER                             1
SYS_NC00009$         SDO_ELEM_INFO_ARRAY

As a basic reminder – whenever you do anything slightly non-trivial (e.g. something you couldn’t have done in v5, say) then remember that all those dinky little script things you find on the Internet might not actually cover your particular case.