It is not an exaggeration to say that a few badly written queries can have a devastating effect on the overall performance of the database. This is not just limited to queries that retrieve data inefficiently but also applies to SQL statements that are repeatedly parsed unnecessarily. When an SQL statement is submitted to Oracle, it will do one of three things; a hard parse, a soft parse or no parse at all. Hard Parse. The first time an SQL statement is executed, Oracle must do a hard parse.
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This note lists customer bugs fixed in the 11.2.0.4 Patch Set which are not already fixed in an earlier 11.2 Patch Set.
It must perform all of the following steps. Parse the statement. Determine the optimal execution plan.
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Execute the statement. The main distinction between a hard and a soft parse is that a hard parse must do step two – query optimization. During optimization, the cost based optimizer (CBO) attempts to determine the best way to access the data. The CBO uses complex algorithms based on system and table statistics to generate many (possibly thousands) of execution plans, each of which is assigned a numeric cost. The plan with the lowest cost is selected for use. It is important to understand that optimization is a very expensive operation.
It is a resource hungry, CPU intensive process that can take longer to run than it does to retrieve the data. We can see an example of this with a TKPROF report on a simple SQL command. But there is another issue.
During optimization, Oracle will lock areas of memory using a device called a latch. Latches protect shared memory from being updated by multiple sessions at the same time. The longer the latches are held, the longer other sessions are queued, waiting for their turn to access the memory segment.
Fortunately, once the difficult task of producing the execution plan has been done, Oracle will automatically cache it in a memory area called the shared pool. Next time an identical query is executed, Oracle will retrieve the execution plan produced by the original query and re- use it. This is known as a soft parse. Now Oracle only needs to do the following. Parse the statement.
2.1.1.2.2 Create the Physical Design. The physical design is the implementation of the logical design on the physical database. Because the logical design integrates. The RPAD function can be used to display a text graph in Oracle. Suppose we wish to display the number of sessions that have been opened by each client machine.
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Execute the statement. If we execute the same SQL statement that we ran previously, the TKPROF output looks like this. We re- used the execution plan which was produced the first time we ran the query and no measurable time was spent parsing. So Oracle takes care of caching the execution plan automatically for us.
However, care must be taken to ensure that the appropriate SQL statement can be found in the cache. Consider the following Java method which returns an account name from an account id.
String get. Account. Name(Connection con, int acc. Id) throws SQLException . The problem here is that the SQL produced by this method is unlikely to be identical from one invocation to the next. For example, if we enquire on accounts 1. SQL. SELECT acc. We need Oracle to perform a single hard parse for the first statement and soft parses for subsequent executions.
Bind Variables. The solution is to use bind variables with a Prepared. Statement. public String get. Account. Name(Connection con, int acc. Id) throws SQLException . However, subsequent executions will read the cached execution plan from the shared pool, substitute the bind variable values and execute the query.
The SQL is soft parsed and the query optimization stage is avoided. If you wish to produce a well- behaved, high performance, scalable application then the importance of bind variables cannot be understated. It is simply one of the most important concepts a Java programmer must understand when working with Oracle.
Later we will see the dramatic difference in performance between hard and soft parsing. A word about CURSOR. The original literal values are then substituted, just as if bind variables had been used in the client program. All this happens transparently in the database itself. For example. SELECT acc. It is no substitute for carefully written and well tested SQL that uses Prepared.
Statements and bind variables from the outset. Statement Parsing. So soft parsing improves performance and scalability. But what does a soft parse actually involve? Broadly speaking, the parsing stage consists of syntax checking, semantic analysis and a lookup in the shared pool. Let's look at each of these in turn. Syntax Checking. Is it valid SQL as defined by the Oracle SQL reference documentation?
SELECT acc. An existing statement may refer to different objects, in different schemas, or the environment in which it was executed may be incompatible, making the execution plan inappropriate for our query. Oracle must resolve these issues which takes time. The point I am trying to make here is that, while a soft parse is far more efficient than a hard parse, it is not without cost. So what is even more efficient than doing a soft parse?
Doing no parse at all. No Parse. The problem with the get. Account. Name method shown earlier is that, each time this method is called, the SQL statement is compiled (when prepare. Statement is executed) and each time the statement is compiled, a soft parse is performed. If, however, the Prepared. Statement was created outside of the method and then passed in as a parameter, the statement could be parsed once and executed many times.
Get. Account. Name(Connection con) throws SQLException . The statement parsing and the shared pool lookup process performed by the soft parse is no longer necessary. All Oracle needs to do is bind the new values to the existing structure and execute the query. Statement Caching. Parsing an SQL statement once and executing it many times should be our goal, but passing around a Prepared. Statement is not always convenient or even possible.
Code can become cluttered if every method in the call stack is forced to include the Prepared. Statement object. One solution is to use implicit statement caching. Implicit statement caching improves performance by caching frequently used executable statements in the JDBC driver. This allows us to keep our original get. Account. Name implementation which creates and closes the Prepared.
Statement within the method. By setting the following properties on the data source, we allow up to 2. Connection get. Connection() throws SQLException . If the same SQL statement is executed again, it will be retrieved from the cache and the statement can be executed without any parsing at all.
A Word About PL/SQLPL/SQL makes use of bind variables and statement caching automatically. Let's rewrite the get. Account. Name method we saw earlier as a PL/SQL function.
CREATE OR REPLACE FUNCTION get. We can see this by running the function one thousand times then looking at the statement in the V$SQL view.
DECLARE l. To do so we would need to re- code the function to use the EXECUTE IMMEDIATE statement as follows. CREATE OR REPLACE FUNCTION get. The slight differences in the Java code will demonstrate the effects of hard parsing, soft parsing and no parsing in the database. We will monitor the results using Oracle Enterprise Manager. Hard Parse. First, we execute the method we saw earlier, which uses a JDBC Statement rather than a Prepared. Statement. This will trigger a hard parse each time the SQL is submitted.
String get. Account. Name(Connection con, int acc. Id) throws SQLException . Oracle recommends that we set the CURSOR. Later, we will follow the second recommendation and change our application logic to use a Prepared.
Statement rather than a Statement. Also, if we navigate to the Duplicate SQL page, a feature designed to help us recognise hard parse issues such as this, then we see the following. Further evidence that we have a significant performance problem can be seen on the graphs in the Performance section of Enterprise Manager. Clearly, we are having some concurrency issues. If we click on the Concurrency link we see that library latching is to blame.
This is a classic symptom of excessive hard parsing. Soft Parse. So let's rewrite the method to use bind variables and a Prepared. Statement to run the same query. String get. Account. Name(Connection con, int acc.
Id) throws SQLException ? Lets take a look at the Average Active Sessions on the Performance page. Note the difference in scale of the Active Sessions on the left compared to the hard parse version. We are using less CPU, waiting less time for resources and we have reduced the library latch contention considerably.
The benefits of soft parsing are clear. However, if we take a look at the SQL Details page for our query we see evidence of another potential performance bottleneck. The value that catches the eye is Total Parses in the Shared Cursor Statistics region. It is about the same as the number of executions.
The fact that we did only two hard parses is good but the fact we did a million soft parses suggests we could do better. No Parse. Let's enable implicit statement caching when we retrieve our database connection and re- run the previous test. Connection get. Connection() throws SQLException . We must endeavour to keep, not only hard parsing to a minimum but soft parsing also. In Java, the use of Prepared.
Statements and bind variables is essential to avoid unnecessary hard parses. This is one of the most valuable lessons, regarding Oracle database performance, that a Java developer can learn. However, it is also important to avoid unnecessary soft parses. Effective re- use of a Prepared.
Statement and implicit statement caching are both useful techniques to avoid excessive soft parses. Fortunately, PL/SQL avoids these problems by using bind variables and statement caching automatically.