· Never do a calculation on an indexed column (e.g., WHERE salary*5 > :myvalue)
· Whenever possible, use the UNION statement instead of OR conditions
· Avoid the use of NOT IN or HAVING in the WHERE clause. Instead, use the NOT EXISTS clause
· Always specify numeric values in numeric form and character values in character form (e.g., WHERE emp_number = 565, WHERE emp_name = ?Jones?)
· Avoid specifying NULL in an indexed column
· Avoid the LIKE parameter if = will suffice. Using any Oracle function will invalidate the index, causing a full-table scan
· Never mix data types in Oracle queries, as it will invalidate the index. If the column is numeric, remember not to use quotes (e.g., salary = 50000). For char index columns, always use single quotes (e.g., name = ?BURLESON?)
· Remember that Oracle’s rule-based optimizer looks at the order of table names in the FROM clause to determine the driving table. Always make sure that the last table specified in the FROM clause is the table that will return the smallest number of rows. In other words, specify multiple tables with the largest result set table specified first in the FROM clause
· Avoid using sub-queries when a JOIN will do the job
· Use the Oracle decode function to minimize the number of times a table has to be selected
· To turn off an index you do not want to use (only with a cost-based optimizer), concatenate a null string to the index column name (e.g., name||’) or add zero to a numeric column name (e.g., salary+0). With the rule-based optimizer, this allows you to manually choose the most selective index to service your query
· If your query will return more than 20 percent of the rows in the table, use a full-table scan rather than an index scan
· Always use table aliases when referencing columns
· Understand the data. Look around table structures and data. Get a feel for the data model and how to navigate it.
· If a view joins 3 extra tables to retrieve data that you do not need, don’t use the view!
· When joining 2 views that themselves select from other views, check that the 2 views that you are using do not join the same tables!
· Avoid multiple layers of view. For example, look for queries based on views that are themselves views. It may be desirable to encapsulate from a development point of view. But from a performance point of view, you loose control and understanding of exactly how much task loading your query will generate for the system.
· Look for tables/views that add no value to the query. Try to remove table joins by getting the data from another table in the join.
· WHERE EXISTS sub-queries can be better than join if can you reduce drastically the number of records in driver query. Otherwise, join is better.
· WHERE EXISTS can be better than join when driving from parent records and want to make sure that at least on child exists. Optimizer knows to bail out as soon as finds one record. Join would get all records and then distinct them!
· In reports, most of the time fewer queries will work faster. Each query results in a cursor that Reports has to open and fetch. See Reports Ref Manual for exceptions.
· Avoid NOT in or NOT = on indexed columns. They prevent the optimizer from using indexes. Use where amount > 0 instead of where amount != 0.
· Avoid writing where project_category is not null. Nulls can prevent the optimizer from using an index.
· Consider using IN or UNION in place of OR on indexed columns. OR’s on indexed columns causes the optimizer to perform a full table scan.
· Avoid calculations on indexed columns. Write WHERE approved_amt > 26000/3 instead of WHERE approved_amt/3 > 26000.
· Avoid this: SUBSTR(haou.attribute1,1,LENGTH(‘:p_otc’)) = :p_otc). Consider this: WHERE haou.attribute1 like :p_otc||’%’
· Talk to your DBA. If you think that a column used in a WHERE clause should have an index, don’t assume that an index was defined. Check and talk to your DBA if you don’t find any.
· Consider replacing outer joins on indexed columns with UNION. A nested loop outer takes more time than a nested loop un-joined with another table access by index.
· Consider adding small frequently accessed columns (not frequently updated) to an existing index. This will enable some queries to work only with the index, not the table.
· Consider NOT EXISTS instead of NOT IN.
· If a query is going to read most of the records in a table (more than 60%), use a full table scan.
· Try to group multiple sub queries into one.
· If you want to actually understand what you are doing, here are a few things that you need to start playing with:
· Get into EXPLAIN_PLAN. There are multiple way of doing this. The less user friendly is to simply issue this in SQL*Plus: explain plan set statement_id = ‘HDD1’ for ;
· Look at the trace from Oracle Reports. It tells you how much time it spends on each query.
· Use the SQL Trace by issuing an alter session set sql_trace=true; then look at it with TKPROF .trc
· Do not use functions on indexed columns in WHERE clauses Unless specifically using a function based index.
· Beware of implicit datatype conversions occuring on indexed columns (e.g. comparing a character column with a number expression will invoke an implicit
TO_NUMBER operation on the indexed column, preventing use of the index – in this case it would be better to us an explicit TO_CHAR operation around thenumber expression being compared against
· Make sure that you have the correct indexes on the tables:-
· Ensure that the first column of the index is selective ( e.g. more than around 15 distinct values with a near uniform distribution
· Avoid using insufficiently selective indexes (i.e. each index value applies to at least 15% of the rows). In this case, a full table scan will be more efficient.
· Aim to have no more than 4 indexes per table. ( each insert into the table has to also modify data in the indexes )
· To use compound indexes ensure that the WHERE clause includes conditions on the leading column(s) of the index
· NEVER use SELECT * FROM. in application code
· Try to avoid use of the DISTINCT clause as it always requires a sort operation. Excessive use of DISTINCT clause may point to an underlying data model problem (e.g a missing table).