Dec/090
Oracle Performance Tuning Part 1: Using Full Table Scans
It is a common misconception that all SQL queries on all tables in Oracle databases should be index driven. In fact, using full-table scans can improve performance in two scenarios: when querying very small tables and when querying very large tables.
The Effect of Full Table Scans When Querying Small Tables
Let’s suppose your using your Oracle database to run in-house designed and built HR application. Consider a reference table such as a list of department ids and the associated department names. Even a large company is likely to have only a few departments – HR, Sales, Marketing, Finance, IT, so the table is going to be quite small.
Now let’s suppose the table has just 2 columns – department id and department name – with an index on the department id. To find the department name for a given id, we would have to read the index and then read the table, but because the table is so small and because Oracle reads multiple database blocks in one read operation the whole table is scanned in just one read, so however efficient the index, by using it we will be performing unnecessary i/o.
In this case, therefore, a full table scan is faster than an index scan and table lookup. The exception to this of course is when the table has been created as an index-only table (available since Oracle 
which means that the whole table is stored in a B-tree structure (although you may have pointers to overflow areas).
The Effect of Full Table Scans When Querying Very Large Tables
Let’s look at using this technique for querying very large tables in your Oracle database. Surely they should use an index? Otherwise you might have to read thousands of blocks. It is correct to say that a full table scan of a very large table could read many thousands of data blocks, but as we shall see it may be better to do this than to perform an index scan and table lookup.
The situation when the a full table scan is very likely to perform better than an index scan and table lookup is when you are retrieving 10% or more of the data in the table and it may perform better even when you are retrieving as little as 1% of the table data. Of course if you only want to retrieve one row in the table, then you would want to use an index.
Index Scan And Table Lookup Vs. Full Table Scan For Very Large Tables in Oracle Databases
Let’s look at the 2 scenarios then – retrieving 10% of the table data by index scan and table lookup vs. full table scan.
To make the maths easy, assume our table has 10,000,000 rows with 10 data rows per block and 100 index entries per block. Therefore to read 10% of the table via an index scan and table lookup, we would have to read 10,000 (1,000,000/100) index blocks plus 100,000 (1,000,000/10) data blocks. That’s 110,000 blocks in total.
However this assumes that the data is stored in order which means that we only retrieve the blocks of data that we want. If the data is not sorted then the worst case is that we would have to read 1 block for each row of data i.e. 1,000,000 blocks, which would would give us a worst case total of 1,010,000 blocks.
For a full table scan the maths is easy: (10,000,000 rows)/(10 rows per block) = 1,000,000 blocks. This is less than the worst case scenario for an indexed read, but more than the best case scenario for an indexed read. This would seem to suggest that if you sort your data before loading, an indexed read would be faster than a full-table scan.
Whilst it is true that pre-sorting the data of very large table will improve performance , it is not necessarily correct that the read via the index will be better overall. We also need to take into account what happens to the blocks stored in the buffer cache of the Oracle SGA and the impact this will have on other users of the database.
Let’s look at the effect on the buffer cache of reading many data blocks via an index. As we know, data and index blocks are stored in the buffer cache by Oracle for reuse by other queries by being marked as least recently used when we do an indexed read. However, those data blocks read by a full table scan are quickly aged out of the buffer cache, because they are not marked as least recently used.
What this means is that the large number of blocks (1,010,000) of index and table data read via the indexed read of our table will be saved in the SGA flushing practically all other data from it – which will obviously have an effect on other users.
Conversely, when a full table scan is performed only the last blocks read are held in the SGA (the actual number is determined by the multi-block read count) so the impact on other users of the database would be minimal.
Summary
To decide whether or not a full-table scan would be better than an indexed read, for a large table you need to consider what proportion of the table the query will retrieve from your Oracle database and consider the likely effect of that on other users. The denser the data, the more efficient a full table scan is for very large tables, but generally if you’re reading more than 1-10% of a very large table, a full table scan would be more efficient than an index scan and table lookup.
For small tables you will get much better performance from your Oracle database by caching the table in its entirety (so that it is always in memory), or by using an index-organised table then you will by relying on indexes. Having said that, every table should have a primary key index to guarantee uniqueness, but you don’t have to use it.
Dec/090
Oracle Performance Tuning Overview
There isn’t the time or space to provide an exhaustive study – whole books have been written about Oracle performance tuning. Instead we’ll just consider a few of the most important tactics and there’ll be suggestions for further reading, so you can expand your knowledge of this important subject.
One point that needs to be made clear is that performance tuning is not an exact science – you can’t always predict that a certain tactic or technique will improve performance. Every change has to be tested, because whilst it may improve performance in one area, it may also degrade performance in another area. Adding an index is a classic example of this – it may improve query performance but the performance of inserts and deletes become slower because the index entries also have to be updated.
The other thing to remember about performance tuning is that you need to decide on your goals before you start – do you need a 10% decrease in response time for queries ? Is adding new records or updating existing records 20% slower than targets ?
You also need to be aware that improving response time is not the only aim that you might have – you might want to reduce memory usage instead – which might mean having to redesign or rewrite some stored procedures. All these issues need to be considered before you start looking at performance.
Let’s start with a list of the topics that we’ll cover:
Use of full-table scans
How and when to use indexes.
How you can optimise joins.
How to use views to get a high performance database.
Why your database should NOT be normalised.
How to use stored procedures to sky-rocket Oracle performance.
How to use sub queries to boost Oracle performance
Jul/090
What is a Database
Definitions:
A database is a collection of information organized into interrelated tables of data and specifications of data objects.
A table in a relational database is a predefined format of rows and columns that define an entity.
Database tables are composed of individual columns corresponding to the attributes of the object.
In a relational database, a row consists of one set of attributes (or one tuple) corresponding to one instance of the entity that a table schema describes.
Also Known As: Record
A single data item related to a database object. The database schema associates one or more attributes with each database entity.
Also Known As: field, column
A database record consists of one set of tuples for a given relational table. In a relational database, records correspond to rows in each table.
Databases are designed to offer an organized mechanism for storing, managing and retrieving information. They do so through the use of tables. If you’re familiar with spreadsheets like Microsoft Excel, you’re probably already accustomed to storing data in tabular form. It’s not much of a stretch to make the leap from spreadsheets to databases. Let’s take a look.
Database Tables
Just like Excel tables, database tables consist of columns and rows. Each column contains a different type of attribute and each row corresponds to a single record. For example, imagine that we were building a database table that contained names and telephone numbers. We’d probably set up columns named “FirstName”, “LastName” and “TelephoneNumber.” Then we’d simply start adding rows underneath those columns that contained the data we’re planning to store.
If we were building a table of contact information for our business that has 50 employees, we’d wind up with a table that contains 50 rows.
Databases and Spreadsheets
At this point, you’re probably asking yourself an obvious question – if a database is so much like a spreadsheet, why can’t I just use a spreadsheet? Databases are actually much more powerful than spreadsheets in the way you’re able to manipulate data. Here are just a few of the actions that you can perform on a database that would be difficult if not impossible to perform on a spreadsheet:
* Retrieve all records that match certain criteria
* Update records in bulk
* Cross-reference records in different tables
* Perform complex aggregate calculations
Jun/090
A Few Hints And Tips On Optimizing Your SQL
This was intended to be a list of hints and tips that you might find useful when using SQ,L but a mere list of tips would be of little benefit without the knowledge to make use of them, so we’ve expanded the list to include the explanations to increasing its usefulness and to make it a proper tutorial.
One important point to remember is that Oracle caches the compiled form of SQL and is therefore able to re-use queries which are the same as previously executed queries. This saves the time and resources required to parse the statement and determine the execution plan. How can you do this ?
1. Use Views
Views are a good way to ensure the same query is re-used as much as possible.
Remember that even just changing the case and spacing of the words could prevent a query from being reused. A view is merely a pre-defined query, the text of which is stored in the database. Therefore by using views you are using exactly the same queries and eliminating the re-parsing overhead. As the load on the database increases this re-parsing overhead becomes more and more significant. Materialized views take the concept one stage further by actually running the query and storing the results in a table
2. Use Stored Procedures
Another way is to use stored procedures which are program units that contain both SQL and logic statements and are stored in the database. Oracle allows the use of PL/SQL and Java stored procedures. Stored procedures and views also have the advantage that the queries in the views/stored procedures have to be tuned only once, not in every place where they’re used. Like views, stored procedures also eliminate the overhead of sending the queries from the client to the server as the queries are already on the server.
3. Use Bind Variables
The use of bind variables in queries makes them generic and therefore re-usable.
For example, instead of writing a query like :-
SELECT name,addr FROM custs WHERE id = 12345;
Change it to:-
SELECT name,addr FROM custs WHERE id = <cust_id>;
The first query will only be re-used when you request the details for customer number 12345, whereas the second query will be re-used for any other customer.
4. Use Selective Indexes
Ensure that tables are accessed via selective indexes, unless the table is very small or very large, in which case it may be better not to use the indexes.
If the table were very small it could be cached completely, or all the columns could be indexed which means only the index would have to be read to satisfy any query.
Also make sure that you’re not disabling the use of an index by:-
* using an operator on the column (eg. <indexed_col> + 1);
* the use of hints, if you’re running Oracle(only applies if you’re using the cost based optimizer);
* using NULL and not equal checks. (eg. <indexed_col> <> 12345 ; or <indexed_col> IS NULL)
5. Use Full-Table Scans
If the table is very large, depending on how many blocks are read, using an index may remove everything else from the buffer cache and degrade the performance of all other queries. In which case a full-table scan is better – only the last few blocks read are kept in the buffer cache.
6. Optimize Joins
* All other things being equal, the driving table is the one listed LAST in the FROM clause, when using the rule-based optimizer. Changing the order of the columns in the join condition does not change which table is used as the driving table. Choose the driving table carefully to ensure the minimum number of rows are returned.
When using the cost-based optimizer, ensure that all the tables in the join have been analyzed (ask your dba), if they haven’t, this may well cause poor performance. The most usual way to optimize queries when using the cost-based optimizer is to use hints, which instruct the parser as to which indexes should or should not be used, or which tables should be scanned in full. You can also experiment with the order of the tables in the join.
* Indexes – these can still be used even if the where clause contains a “like” condition but not if there is a “not like” condition.
* Outer joins – the correct syntax for outer joins using Oracle syntax is:
tab1.col1(+)= tab2.col1
or tab1.col1 = tab2.col1(+)
The bracketed plus sign follows the column of the table which has/may have the missing row.
An alternative is to use the ANSI standard outer join format which has the advantage that it enables you to perform a full outer join in one statement:
tab1.col1 left outer join tab2.col1 (return all rows from tab1)
tab1.col1 right outer join tab2.col1 (return all rows from tab2)
tab1.col1 full outer join tab2.col1 (return all rows from tab1 and tab2)
The final tip for this short tutorial is:
7. Name The Columns In A Query
There are three good reasons why it is better to name the columns in a query rather than to use “select * from …”.
1. Network traffic is reduced. This can have a significant impact on performance if the table has a large number of columns, or the table has a long or long raw column or have in-line clob or blob columns (all of which can be up to 2 Gigabytes in length). These types of columns will take a long time to transfer over the network and so they should not be fetched from the database unless they are specifically required.
2. The code is easier to understand, which means you need fewer comments!
3. It could save the need for changes in the future. If you are using views, not only might columns be added to or removed from the view, but the order of the columns could well change – in which case using “SELECT *” at best would fetch the wrong data and at worst would fail with an Oracle error which might take a long while to understand.