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Tuning Aggregation Queries with Temporary Tables
Oracle Tips by Burleson
 

In addition to data dictionary queries, temporary table can dramatically improve the performance of certain SQL self-join queries that summarize data values.

For example, consider a query that examines the stats$tab_stats STATSPACK extension table. Rows for the stats$tab_stats table are collected weekly, and one row in this table exists for each table in the schema. This STATSPACK extension table is loaded by collecting the table_name and the bytes consumed by the table (from the dba_segments view), and we want to use this table-level detail data to summarize our overall size change per week.

Here is the description for this STATSPACK extension table. For details on using this table, refer to Oracle High-Performance Tuning with STATSPACK, by Don Burleson (McGraw-Hill Professional Publishing, 2001).

SQL> desc stats$tab_stats;
 Name                                      Null?    Type
 ----------------------------------------- -------- -----------------
 SNAP_TIME                                          DATE
 SERVER_NAME                                        VARCHAR2(20)
 DB_NAME                                            VARCHAR2(9)
 TABLESPACE_NAME                                    VARCHAR2(40)
 OWNER                                              VARCHAR2(40)
 TABLE_NAME                                         VARCHAR2(40)
 NUM_ROWS                                           NUMBER
 AVG_ROW_LEN                                        NUMBER
 NEXT_EXTENT                                        NUMBER
 EXTENTS                                            NUMBER
 BYTES                                              NUMBER

Since each row of this table contains a date (snap_time), a table name (table_name), and the number of bytes, we need a query that sums up the total size for all tables for one week, and then compares that value to the overall size for the following week (Figure 18-1).

Figure 1: Using temporary tables to preaggregate values from a time-based table

Essentially, we could formulate this comparison of summaries as a single query that summarizes each range or rows.

select distinct
   to_char(old_size.snap_time,'yyyy-mm-dd'), -- The old snapshot date
   sum(old_size.bytes),
   sum(new_size.bytes),
   sum(new_size.bytes) - sum(old_size.bytes)
from
   stats$tab_stats old_size,
   stats$tab_stats new_size
where
   -- This is the highest date in the table
   new_size.snap_time = (select max(snap_time) from stats$tab_stats)
and
   -- This is the prior weeks snapshot
   old_size.snap_time = (select min(snap_time)-7 from stats$tab_stats)
group by
   to_char(old_size.snap_time,'yyyy-mm-dd')
;

Here is the execution plan for this query. Because we are summing and comparing ranges of values within the same table, we see the dreaded MERGE JOIN CARTESIAN access method. As you know, a Cartesian merge join can run for hours because the Cartesian products of the tables must be derived.

OPERATION
----------------------------------------------------------------------
OPTIONS                        OBJECT_NAME                    POSITION
------------------------------ ---------------------------- ----------
SELECT STATEMENT
                                                                     5
  SORT
GROUP BY                                                             1
    MERGE JOIN
CARTESIAN                                                            1
      TABLE ACCESS
BY INDEX ROWID                 STATS$TAB_STATS                       1
        INDEX
RANGE SCAN                     TAB_STAT_DATE_IDX                     1
          SORT
AGGREGATE                                                            1
            INDEX
FULL SCAN (MIN/MAX)            TAB_STAT_DATE_IDX                     1
      SORT
JOIN                                                                 2
        TABLE ACCESS
BY INDEX ROWID                 STATS$TAB_STATS                       1
          INDEX
RANGE SCAN                     TAB_STAT_DATE_IDX                     1
            SORT
AGGREGATE                                                            1
              INDEX

FULL SCAN (MIN/MAX)            TAB_STAT_DATE_IDX                     1

Take a close look at the execution plan for this query, and carefully review the steps:

1.      We begin with an index range scan to get the maximum date in the stats$tab_stats table.

2.      Next, we perform an index range scan to get the sysdate–7 value.

3.      Once we have the target data values, we must perform a Cartesian merge join to access the rows and resolve the query.

This query gets tricky where we must compare a range of common date with another range of common dates. As you can see, these range comparison queries are hard to formulate and hard for Oracle to optimize.

To see an alternative query, let’s look at an equivalent query that utilizes temporary tables. This report uses the STATSPACK extension tables for objects to prepare weekly growth reports. The rpt_object_stats.sql script is a very useful STATSPACK report that approximates the overall growth of the database over the past week. The DBA can quickly compare table and index counts, and see the total growth for table and indexes over the past week. This report is often e-mailed to MIS managers.

Let’s take a closer look at each section of the report and then see how to formulate the query.


This is an excerpt from "Oracle High-Performance SQL Tuning" by Donald K. Burleson, published by Oracle Press.

  
 

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