Performance Improvement - Part 1: Parsing

Performance Improvement - Part 1: Parsing

In this article, we see how to improve the performance of the SQL queries. Before that we should know about the parsing and types of that.

Parsing:

This is the first step in the processing of any statement in Oracle. Parsing is the process of breaking the submitted statement down into its component parts. Determining what type of statement it is (whether Query, DML, DDL) and performing various checks on it.
The parsing process performs two main functions:

· Syntax Check
· Semantic Analysis

Syntax Check:

The syntax check performs the below operation.

Is the statement a valid one?
Does it make sense given the SQL grammar documented in the SQL Reference Manual? Does it follow all of the rules for SQL?

Semantic Analysis:
The semantic going beyond the syntax and it is performing the below operation.

Is the statement valid in light of the objects in the database (do the tables and columns referenced exist)?
Do you have access to the objects?
Are the proper privileges in place?
Are there ambiguities in the statement?
Soft parsing and hard parsing:
The next step in the parse operation is to see if the statement we are currently parsing has already in fact been processed by some other session. We may be in luck here If it has, we can skip the next two steps in the process, that is

1 .Optimization
2. Row source generation.

If we can skip these next two steps in the process, we have done what is known as a Soft Parse.


If we cannot, if we must do all of the steps, we are performing what is known as a Hard Parse. Hard parse includes the parse, optimize, generation of the plan for the query.
Example for Hard Parse:
The below scripts demonstrate the hard parsing.
SQL> ALTER SYSTEM FLUSH SHARED_POOL;

System altered.

SQL> create table t
(
id number(2),
Des varchar2(20)
);

Table created.

insert into t values(1,'AA');
insert into t values(2,'BB');
insert into t values(3,'CC');
insert into t values(4,'DD');
insert into t values(5,'EE');
insert into t values(6,'FF');


SQL> select * from t;

ID DES
--- --------
1 AA
2 BB
3 CC
4 DD
5 EE
6 FF

6 rows selected.


SQL> select SQl_TEXT,executions,hash_value,child_latch,child_address from v$sql where sql_text like 'select * from t where id %';

no rows selected

SQL> select * from t where id = 2;

ID DES
--- --------
2 BB

SQL> select * from t where id = 2;

ID DES
--- --------
2 BB

SQL> select * from t where id = 3;

ID DES
--- --------
3 CC

SQL> select SQl_TEXT,executions,hash_value,child_latch,child_address from v$sql where sql_text like 'select * from t where id %';




The above result is showing that, it is creating the different hash value for “where id = 2” and “where id =3 “. That means it is going for the hard parse for the each time when we change the condition.

Example for Soft parse:

The Execution column is showing 2 for the “where id =2 “. First time it has gone for the hard parse and second time it is gone for the soft parse.

How to make soft parse for “where id =2 “and “where id =3 “. We use the bind variable and it solves the issue.


SQL> variable id number
SQL> exec :id := 1;

PL/SQL procedure successfully completed.

SQL> select * from t where id = :id;

ID DES
--- --------
1 AA

SQL> exec :id :=2 ;

PL/SQL procedure successfully completed.

SQL> select * from t where id = :id;

ID DES
--- ------
2 BB

SQL> exec :id :=2 ;

PL/SQL procedure successfully completed.

SQL> select * from t where id = :id;

ID DES
--- -------
2 BB


SQL> select SQl_TEXT,executions,hash_value,child_latch,child_address from v$sql where sql_text like 'select * from t where id %';

It is not creating the different plan for each time when we use the bind variable. The hash value vale has created for the script “where id = :id “ and the value of the variable (:id) is changing each time. Refer the “Execution field, It is showing 3 for the different values.
Hard parsing is very CPU intensive. If our applications we want a very high performance then our queries to be Soft Parsed (to be able to skip the optimize/generate phases)

If we have to Hard Parse a large percentage of our queries, our system will function slowly and in some cases not at all.

Now we have a strong proof for the soft parsing and that improve the performance. But soft parsing is not always good and hard parsing is not always bad. We see that in the next Blog.