access plan

Ideally, the optimizer would identify the most efficient access plan possible, but this goal is often impractical.

Section actuals permit you to see what the real cardinalities are vs. estimated cardinalities in an access plan.

The query itself and its access plan are cached once by DB2 and are then ready to be used every time the query is executed.

The inserts themselves could be very fast, but there may be an access plan problem for the SELECT which slows down the whole statement.

You can use the REWRITE function without the ANSI argument to help understand how the optimizer generated the access plan for a given query.

You may have noticed that the query access plan itself did not change with the increase in cardinality estimate.

The above access plan is for an insert into the child table of a foreign key relationship.

The optimizer depends on accurate cardinality estimates to properly compute the cost of each query access plan considered.

You can use the Design Advisor to see if indexes would result in an access plan with fewer table scans.

Before beginning this tutorial, you should be familiar with the concept of a SQL access plan.

Note that the nickname divisional_sales is shown as one of the objects used in the access plan.

Generate the access plan and see what the optimizer estimates the total cardinality (Number of rows) returned by the query will be.

When examining an access plan, you may find that the estimated cardinality is not as accurate as it should be.

However, the access plan for all the statements was likely the same, so it was a waste of resources to repeatedly calculate it.

CPU Cost -- Estimated cumulative total cost (in timerons) of executing the chosen access plan up to and including this plan operator.

This feature identifies which side is the master entity (driver) and which entity is the child and enhances the data access plan.

Runtime statistics can also be gathered for access plan operators during the execution of a section.

Bind is the process that saves the access plan associated with a SQL statement into a DB2 SQL package.

The optimizer takes account of these changes and selects the optimal access plan when the job is executed.

In the query access plan shown in Listing 9, notice a join between the table EMPLOYEE and a table function, GENROW.

If there are no growing cost SQL queries in the snapshot, analyze the access plan to see which can be amended based on the accumulated data.

The best access plan for the SQL statement does not depend on explicit values in the statement's filter conditions.

With few exceptions, the Adaptive Server Anywhere optimizer devises a suitable access plan based only on the semantics of each statement.

Normally, the optimizer selects an access plan for a query every time the query is executed.

Understanding the access plan is important for understanding and influencing performance, as well as for stabilizing performance.

The SQL explain facility provides detailed information about the access plan that the query optimizer chooses for an SQL statement.

For queries that do not match any guideline, the regular cost-based access plan is chosen.

The next objective is to further reduce the SQL cost by optimizing the access plan.

The true solution to this problem is to improve the access plan for problematic SQL statements by adding the correct indexes.

As you've seen in the steps above, the optimizer selects the optimal access plan based on available statistics.

The access plan assumes that the sort operations to generate the data streams ordered on prod_id are pushed down to the two data sources.

The optimizer expresses its chosen method in the form of an access plan.

As a simple example, the following graph (produced by db2exfmt) shows the access plan for an "Insert into Test1 values (? , ? , . . . )" .

It is important for a DBA to understand how to look at EXPLAIN output to detect and locate problems in the access plan.

In this example, access plan overall costs do not include the actual fetch time.

However, you would still like the optimizer to find the best access plan based on the values that users have passed into the query.

When this attribute is not specified, the optimizer makes a cost-based decision to select an access plan for the given table.

To enable access plan reuse, rewrite the SQL statement using a parameter marker, as shown in Listing 3.

Starting with the V9. 7 Fix Pack 1, runtime statistics can be gathered for access plan operators during the execution of a section.

Then we analyzed the access plan and decided to do runstats and rebind the database during a long-running test.

As the previous section described, parameter marker usage in SQL statements fosters access plan reuse.

The cardinality represents the estimated number of rows returned from the access plan operator.

The access plan is basically the roadmap of how DB2 is going to access the data required to satisfy the query.

If you use the Statement interface, you parse each statement you send to the database, generate an access plan, and execute the statement.

Direct execution Adaptive Server Anywhere parses the SQL statement, prepares an access plan, and executes the statement.

Learn to use access plan information to understand how to optimize your SQL statements.

The DB2 optimizer uses these statistics to determine the most efficient access plan for any given query, which improves query performance.

So if an access plan is reused, a database server requires less CPU resources to execute the corresponding SQL statement repeatedly.

The access plan can be modeled as a Merge Join (MGJN) of the two sales tables.

Access plan describes the access path that the DB2 optimizer has chosen for accessing data for an SQL statement.

The identified problematic SQL statements should be explained to show the access plan for any needed, specific tuning.

Remember that DB2 can only reuse an access plan if SQL statement texts completely match.

The access plan operator is either an action that must be performed on data, or the output from a table or an index.

When a procedure is executed for the first time, it is compiled to determine an optimal access plan to retrieve the data.

With this feature, the query optimizer can immediately consider the index when determining an access plan.

The following are additional methods that may be used in an access plan.

When the DB2 optimizer forms a query access plan for a query, it divides the work among the database partitions which work in parallel.

After you collect those statistics, you get the new access plan graph shown in Figure 10.

Dynamic SQL needs to be prepared execution by the UDB optimizer in order to create an access plan for the statement.

The example below introduces the access plan basics by analyzing the bad SQL statement we captured in the previous section.

The access plan for a given SQL statement is generated at bind time.

An access plan defines the order for accessing tables, which indexes are used, and by what kind of join methods data is correlated.

By the way, when you see "GENROW" in an access plan, it is a "generate row" step.

A good access plan is key for the fast execution of an SQL statement.

Parsing and access plan preparation are called preparing the statement.

Always use literals if the optimal access plan for the SQL statement varies according to the literals in the filter conditions.

When the index name is not specified, optimizer picks the cheapest single XML index access plan.

This visualization is called the access plan graph.

Briefly, an access plan is the set of steps that DB2 uses to execute an SQL statement and access data.

Access plan and other very detailed information can be found in this file for our example query.

Figure 12 confirms that the new index on the STAFF table is being used in the query access plan.

At each operator in the access plan, the optimizer estimates the cardinality output from the operator.

Briefly, an access plan is the set of steps that DB2 uses to execute a SQL statement and access data.

Under-estimating the cardinality could lead the optimizer to choose a sub-optimal access plan.

UltraLite Interactive SQL has a window that displays the access plan of a query.

In this case, the optimizer creates a different access plan, which may not be optimal if the user input is 0.

Collect distribution statistics and then generate the access plan again.

Either way you provide the query and the access plan is generated and shown to you.

If current statistics are not available, the optimizer may choose an inefficient access plan based on inaccurate default statistics.

The query access plan produced after collecting these statistics is the same as the final plan in Example 3.

Figure 3 depicts the access plan for the very query that we used before extensively in this article.

This now populates the explain tables with the access plan chosen by the optimizer based on real and virtual indexes.

You get a different access plan in test than production.

This brings little overhead for compiling, but gives an optimal access plan.

Naoto Kan said it was considering "access" plan, but the specific date has been set.

Another advantage of access plan reuse is a reduced CPU load.

Depending on the value provided for T1. PENDING column, the above access plan may or may not be optimal.

How do I recreate the same query access plan on my test environment that I am getting on my production environment?

After creating the three new indexes, you get the new access plan graph shown in Figure 13.

Nevertheless, another access plan is generated when parameter markers are used.

Access plan creation in the prepare phase requires CPU resources.

If not, analyze the access plan (for example, using DB2 Explain utilities) to see which can be amended.

This is quite useful when you match the access plan back to the event monitor outputs.

The access plan previously used may not be the best one if the value is changed from 0 to 1.

This covers all the operators in this access plan.

SQL Server uses the optimal access plan, but query optimization is limited by what is possible.

Introducing asynchrony into an access plan leads to increased use of resources on both the WFS and the backend system(s).

When the statement is compiled, its access plan is stored in the package cache.

Listing 12 shows the basic component of an access plan.

Ideally, the database will choose the most optimal access plan -- that is, the plan that returns the data the most efficiently and quickly.

You've learned how to capture the access plan of a given query using the SQL explain utility (db2exfmt) in the DB2 UDB monitoring section.

Listing 11 shows the access plan for the SELECT statement.

The attribute TYPE can have the value 'XMLINDEX' to select an index anding access plan that includes one or more XML indexes.

Figure 2 shows an example access plan graph for a given query.

From the access plan, IXSCAN(3) shows one row is expected to be returned from T1.

And the access plan generated by the.

To check if a spatial grid index is actually exploited during query time, you should have a look at the access plan.

You can generate the access plan using DB2's explain facility.

With this method, we can collect real cardinality for access plan operators.

The goal of the optimizer is to find a good access plan.

In the above access plan, IXSCAN(4) scans the entire primary key for one million rows.

Visual Explain, which is available through the DB2 Control Center, is the simplest way to view an access plan.

There are three methods of viewing an access plan.

After the DB2 optimizer selects an access plan, DB2 generates the executable code for running the query, based on the QGM result.

With REOPT ALWAYS, the query will be re-compiled and the access plan will be re-generated based on run-time value.

Listing 13 shows the new access plan.

Now, look at the access plan.

The hash join in the access plan estimates that 1 row will be returned when in fact it is 4 rows.

By adding the index on the ACCT_ID_INX column, the new access plan shows a significant cost reduction from 3420. 41 to 38. 6219 timerons.

With the new index created, and statistics collected on it, the optimizer corrects the cardinality estimate of the query access plan

This provides the optimizer with the most accurate information with which to determine the best access plan. For example

Better UNION handling in the compile and optimization phase of the access plan

Database and database manager configuration from the access plan

Proposed concourse level Pedestrian access plan

Proposed street level pedestrian access plan

To evaluate the new access plan after the index creation on the ACCOUNT table issue

A query access plan similar to the following is chosen by the optimizer

Access plan for query accessing an inverted text index

Access plan for query without inverted text index

The file exfmt_example2. out should contain a query access plan similar to the following, with an estimated cardinality of 7

The file exfmt_example1. out contains a query access plan similar to the following, with an estimated cardinality of 1

From the access plan graph in Figure 6, you can do some initial performance analysis

You may execute the following steps in order to generate the access plan for the above SELECT statement

Generate the access plan using db2exfmt as follows

Listing 1. How access plan components appear in db2exfmt output

Generate the access plan using db2exfmt. You will see the following access plan

Examine the contents of test_dummydb_exfmt. txt and look at the access plan

You should see the following access plan generated

From this new access plan graph, you can see the following

From the access plan graph in Figure 6, you can see the following

The access plan here is