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 Oracle PLSQL
PL/SQL is Oracle’s SQL++ programming language providing structure and flow control extensions to SQL. The name PLSQL is derived from the term “Procedural Language extensions to SQL”.
On its own, SQL enables you to specify what you want done but not how it is done. However, you often need more control over how data is retrieved and manipulated and this is where PL/SQL comes in.
The procedural capabilities combined with standard SQL in Oracle PLSQL gives developers far more control of how their SQL statements interact with the database and makes using PL/SQL an excellent alternative to developing applications in other languages such as Java or C or VB.
The language itself is modeled on Ada, so Java/C/C++ programmers will find the syntax rather strange and probably won’t like the single”=” being used for comparison, but anyone who’s used Pascal or Ada or Modula2 will fell right at home.
PL/SQL is not a pure object-oriented language like Java or Ada, but it does support some obect-oriented features such as classification, polymorphism and, in the later versions, inheritance.
Jun/090
Short Oracle Tutorial For Beginners
Introduction
This is just a brief Oracle tutorial for beginners, to provide a short history of databases and Oracle’s role in them, explain relational theory and give you an idea on how relational databases work with a few examples. There is also a very brief discussion of object-oriented design as it applies to databases.
Time and space don’t permit an in-depth discussion of all the features available in Oracle, but if you would like to learn more just contact us and ask for our free Oracle tutorial mini-course.
History of Databases – From Trees To Objects
The storage and management of data is probably the biggest headache for all businesses. It has been so for a long while and is likely to continue for a long while too. As companies try to store more and more details about their customers and their buying habits and as regulatory requirements for storing more data for longer, so companies will need to store and manage more and more data. The only way this can be done at a reasonable cost is by the use of computers.
In the late 1960s/early 1970s, specialised data management software appeared – the first database management systems (DBMS). These early DBMS were either hierarchical (tree) or network (CODASYL) databases. These early systems were very complex and inflexible and so it adding new applications or reorganising the data was very difficult and time-consuming.
In 1970 the relational data model was defined by E.F. Codd (see “A Relational Model of Data for Large Shared Data Banks” Comm. ACM. 13 (June 6, 1970), 377-387). This delivered a solution to the problems of tree and network databases due to the concept of normalisation which involves the separation of the logical and physical representation of data.
In 1974 IBM started a project called System/R to prove the theory of relational databases. This led to the development of a query language called SEQUEL (Structured English Query Language) later renamed to Structured Query Language (SQL) for legal reasons and now the query language of all databases.
In 1978 a prototype System/R implementation was evaluated at a number of IBM customer sites. By 1979 the project finished with the conclusion that relational databases were a feasible commercial product.
IBM’s research into relational databases had also come to the attention of a group of engineers in California who were so convinced of the potential that they formed a company called Relational Software, Inc. in 1977 to build such a database. Their product was called Oracle and the first version for VAX/VMS was released in 1979, thereby becoming the first commercial rdbms, beating IBM to market by 2 years.
In the 1980s the company was renamed to Oracle Corporation. Throughout the 1980s, new features were added and performance improved as the price of hardware came down and Oracle became the largest independent rdbms vendors. By 1985 they boasted of having more than 1000 installations.
As relational databases became accepted, companies wanted to expand their use to store images, spreadsheets, etc. which can’t be described in 2-dimensional terms. This led to the Oracle database becoming an object-relational hybrid in version 8.0, i.e. a relational database with object extensions, enabling you to have the best of both worlds.
What is a relational database?
As mentioned before, a relational database is based on the separation and independence of the the logical and physical representations of the data. This provides enormous flexibility and means you can store the data physically in any way without affecting how the data is presented to the end user. The separation of physical and logical layers means that you can change either layer without affecting the other.
A relational database can be regarded as a set of 2-dimensional tables which are known as “relations” in relational database theory. Each table has rows (”tuples”) and columns (”domains”). The relationships between the tables is defined by one table having a column with the same meaning (but not necessarily value) as a column in another table.
For example consider a database with just 2 tables :
emp(id number
,name varchar2(30)
,job_title varchar2(20)
,dept_id number)
holding employee information and
dept(id number
,name varchar2(30))
holding department information.
There is an implied relationship between these tables because emp has a column called dept_id which is the same as the id column in dept. In Oracle this is usually implemented by what’s called a foreign-key relationship which prevents values being stored that are not present in the referenced table.
Relational databases obtain their flexibility from being based on set theory (also known as relational calculus) which enables sets or relations to be combined in various ways, including:
* join/intersection
* union (i.e. the sum of 2 sets);
* exclusive “OR” (i.e. the difference between 2 sets)
* and outer-join which is a combination of intersecting and exclusive or ing.
The intersection or join between 2 sets (in this case, tables) produces only those elements that exist in both sets.
Therefore, if we join Emp and Dept on department id, we will be left with only those employees who work for a department that is in the dept table and only those departments which have employees who are in the emp table.
The union produces the sum of the tables – meaning all records in Emp and all records in Dept. and this may be with or without duplicates.
Let’s use the following data to provide specific examples:
Dept
| Id | Name |
| 1 | HR |
| 2 | IT |
| 3 | Marketing |
| 4 | Sales |
| 5 | Finance |
Emp
| Id | Name | Dept Id |
| 1 | Bill Smith | 3 |
| 2 | Mike Lewis | 2 |
| 3 | Ray Charles | 3 |
| 4 | Andy Mallory | 4 |
| 5 | Mandy Randall | 6 |
| 6 | Allison White | 1 |
The join of Emp and Dept. on the department id would produce the following result:
| Emp.Id | Emp.Name | Dept.Id | Dept.Name |
| 1 | Bill Smith | 3 | Marketing |
| 2 | Mike Lewis | 2 | IT |
| 3 | Ray Charles | 3 | Marketing |
| 4 | Andy Mallory | 4 | Sales |
| 6 | Allison White | 1 | HR |
The union of Emp and Dept. would produce the following results
| Id | Name |
| 1 | Bill Smith |
| 2 | Mike Lewis |
| 3 | Ray Charles |
| 4 | Andy Mallory |
| 5 | Mandy Randall |
| 1 | HR |
| 2 | IT |
| 3 | Marketing |
| 4 | Sales |
| 5 | Finance |
The union operator is only allowed when the number and data types of the columns in the 2 sets are the same. It is not normally be used to combine sub sections from one or more tables rather than entire tables.
There are other operators and variations but there isn’t the space or the time to provide full details in this short Oracle tutorial.
The later versions of Oracle (Oracle 8 onwards) support both relational and object-oriented features. The relational features are more prominent at the moment, but this is beginning to change. In this context an object has both attributes and methods (programs stored with the object that performs a certain action or task) and in a true object-oriented database would belong to a class and would allow multilevel inheritance.