The join order is the order in which the tables are joined together in a multi-table SQL statement. Ideally, a plan should start with the join that eliminates the most data to minimize the amount of data carried into the subsequent joins.
How is the Join Order Determined?
The join order is determined based on cost, which is strongly influenced by the cardinality estimates and available access paths. However, the Optimizer will also always adhere to some basic rules:
The Optimizer will always select a join that will produce at most 1 row as the initial join in the plan. For example, a join between two row sources that only have 1 row each. Like a primary key lookup or an index unique scan.
If a SQL statement uses an outer join, then the optimizer must obey the join order specified by the outer join. That is to say; the row preserving table must come after the other table in the predicate to ensure all of the additional rows that don’t satisfy the join condition can be added to the result set correctly. For example, with the Oracle syntax for outer joins, the table with the outer join operator must come after the other table in the predicate. Thus, in this example, the cites table must come before the countries table.
WHERE cities.country_id = countries.id(+);
For SQL statements that reference a database view, the Optimizer will attempt to do view merging, where the definition of the view is inserted into the rest of the SQL statement, and the entire expanded statement is optimized as a whole. However, there are a few cases where view merging isn’t possible. In these cases, the optimizer will join all of the tables in the view together before the resulting data set is joined to the tables outside the view.
When a subquery has been converted into an anti-join (NOT IN subquery) or semi-join (EXISTS subquery), the tables from the subquery must come after those tables in the outer query block to which they were connected or correlated. However, hash anti-joins and semi-joins can override this ordering condition under certain circumstances.
How to determine the Join Order in an execution plan
You can take several approaches to determine the Join Order in a plan, from looking at the indentation of the tables in the operation column to a depth-first search. To clearly explain how to identify the Join Order in an execution plan, I’ve created a short video demonstrating several approaches using real-world examples.
At the end of last year, I began a blog series on reading and interpreting Oracle execution plans. In this week’s post, I will tackle the aspect of execution plans that I get the most questions about, Access Methods.
What are Oracle Access Paths or Methods?
Access Methods or Access Paths are the techniques used by Oracle to access the data needed to answer a query. Access Methods can be divided into two categories; data accessed via a table scan or index access. You can find the individual Access Methods chosen by the Optimizer in the Operations column of an Execution table.
How Many Access Paths are available to the Optimizer?
Oracle supports nine different Access Methods today, as shown in the image below.
When will the Optimizer choose each of these methods, and what can I do to influence that decision?
To clearly explain how each of the Access Methods works and when it will be chosen, I’ve created a short video.
What if I don’t get the Access Method I want?
If the Access Method you see in an execution plan is not what you expect, check the cardinality estimates for that object are correct, and the join order allows the access method you desire. Remember, Optimizer transformations (the rewriting of your query to open up additional access methods) can also greatly impact the Access Method.
Examining the different aspects of an execution plan, from cardinality estimates to parallel execution, and understanding what information you should glean from it can be overwhelming even for the most experienced DBA.
That’s why I’ve put together a series of short videos that will walk you through each aspect of the plan and explain what information you can find there and what to do if the plan isn’t what you were expecting.
What is an Execution Plan?
The series starts at the very beginning with a comprehensive overview of what an execution plan is and what information is displayed in each section. After all, you can’t learn to interpret what is happening in a plan, until you know what a plan actually is.
How to Generate an Execution Plan?
Although multiple different tools will display an Oracle Execution Plan for you, there really are only two ways to generate the plan. You can use the Explain Plan command, or you can view the execution plan of a SQL statement currently in the Cursor Cache using the dictionary view V$SQL_Plan. This session covers both techniques for you and provides insights into what additional information you can get the Optimizer to share with you when you generate a plan. It also explains why you don’t always get the same plan with each approach, as I discussed in an earlier post.
How to use DBMS_XPLAN to FORMAT an Execution Plan
The FORMAT parameter within the DBMS_XPLAN.DISPLAY_CURSOR function is the best tool to show you detailed information about a what’s happened in an execution plan including the bind variable values used, the actual number of rows returned by each step, and how much time was spent on each step. I’ve also covered a lot of the content in this video in a previous post.
From time to time, it may become necessary to influence the plan the Optimizer chooses via Optimizer hints. This session explains how Optimizer hints are interpreted, when and where they should be used.
Part 4 is called “Harnessing the power of optimizer hints”. Although I am not a strong supporter of adding hints to SQL statements for a whole host of reasons, from time to time, it may become necessary to influence the plan the Optimizer chooses. The most powerful way to alter the plan chosen is via Optimizer hints. But knowing when and how to use Optimizer hints correctly is somewhat of a dark art. This session explains how Optimizer hints are interpreted, when and where they should be used, and why they sometimes appear to be ignored.
Examines the different aspects of an execution plan, from cardinality estimates to parallel execution and explains what information you should be gleaming from the plan.
Part 3 of the workshop examines the different aspects of an execution plan, from cardinality estimates to parallel execution and explains what information you should be gleaming from the plan and how it affects the execution. It offers insight into what caused the Optimizer to make the decision it did as well as a set of corrective measures that can be used to improve each aspect of the plan.
The volume of data being stored in databases has grown exponentially in recent years. So too has the need to rapidly generate value or business insights from that data.
Parallel execution is the key to processing large volumes of diverse data quickly, as it subdivides complex tasks into a number of small tasks allowing multiple processes to accomplish a single complex task.
However, the use of parallelism can complicate the execution plan displayed. Oracle not only displays the operations needed to complete the SQL statement in the plan but all of the communication steps between the parallel server processes.
So, how should you go about interpreting a parallel execution plan?
In the video below, I give you a step by step guide on how to read parallel plans and what additional information you can glean from them!