SQL Server Query Execution Plan Analysis

When it comes time to analyze the performance of a specific query, one of the best methods is to view the query execution plan. A query execution plan outlines how the SQL Server query optimizer actually ran (or will run) a specific query. This information if very valuable when it comes time to find out why a specific query is running slow.
If you want to see an execution plan, but you don't want to run the query, you can choose the option "Display Estimated Execution Plan" (located on the Query drop-down menu). When you select this option, immediately an execution plan (in graphical format) will appear. The difference between these two (if any) is accountable to the fact that when a query is really run (not simulated, as in this option), current operations of the server are also considered. In most cases, plans created by either method will produce similar results.
If you see any of the following in an execution plan, you should consider them warning signs and investigate them for potential performance problems. Each of them are less than ideal from a performance perspective.
Index or table scans: May indicate a need for better or additional indexes.
Bookmark Lookups: Consider changing the current clustered index, consider using a covering index, limit the number of columns in the SELECT statement.
Filter: Remove any functions in the WHERE clause, don't include wiews in your Transact-SQL code, may need additional indexes.
Sort: Does the data really need to be sorted? Can an index be used to avoid sorting? Can sorting be done at the client more efficiently?
It is not always possible to avoid these, but the more you can avoid them, the faster query performance will be.
If you have a stored procedure, or other batch Transact-SQL code that uses temp tables, you cannot use the "Display Estimated Execution Plan" option in the Query Analyzer or Management Studio to evaluate it. Instead, you must actually run the stored procedure or batch code. This is because when a query is run using the "Display Estimated Execution Plan" option, it is not really run, and temp tables are not created. Since they are not created, any references to them in the code will fail, which prevents an estimated execution plan from being created.
On the other hand, if you use a table variable instead of a temp table, you can use the "Display Estimated Execution Plan" option
If you have a very complex query you are analyzing in Query Analyzer or Management Studio as a graphical query execution plan, the resulting plan can be very difficult to view and analyze. You may find it easier to break down the query into its logical components, analyzing each component separately.

Keep the following in mind when viewing a graphical execution plan:
In very complex query plans, the plan is divided into many parts, with each part listed one on top of the other on the screen. Each part represents a separate process or step that the query optimizer has to perform in order to get to the final results.
Each of the execution plan steps is often broken down into smaller sub-steps. Unfortunately, they are displayed on the screen from right to left. This means you must scroll to the far right of the graphical query plan to see where each step starts.
Each of the sub-steps and steps is connected by an arrow, showing the path (order) taken of the query when it was executed.
Eventually, all of the parts come together at the top left side of the screen.
If you move your cursor above any of the steps or sub-steps, a pop-up windows is displayed, providing more detailed information about this particular step or sub-step.
If you move your cursor over any of the arrows connecting the steps and sub-steps, you see a pop-up window showing how many records are being moved from one step or sub-step to another step or sub-step.
The arrows that connect one icon to another in a graphical query plan have different thicknesses. The thickness of the arrow indicates the relative cost in the number of rows and row size of the data moving between each icon. The thicker the arrow, the more the relative cost is.
You can use this indicator as a quick gauge as to what is happening within the query plan of your query. You will want to pay extra attention to thick arrows in order to see how it affects the performance of your query. For example, thick lines should be at the right of the graphical execution plan, not the left. If you see them on the left, this could indicate that too many rows are being returned, and that the query execution plan is less than optimal.
In an execution plan, each part of it is assigned a percentage cost. This represents how much this part costs in resource use, relative to the rest of the execution plan. When you analyze an execution plan, you should focus your efforts on those parts that have the largest percentage cost. This way, you focus your limited time on those areas that have the greatest potential for a return on your time investment.

When you place the cursor over a table name (and its icon) in a graphical execution plan and display the pop-up window, you will see one of several messages. These messages tell you if and how an index was used to retrieve data from a table. They include:
Table Scan: If you see this message, it means there was no clustered index on the table and that no index was used to look up the results. Literally, each row in the table had to be examined. If a table is relatively small, table scans can be very fast, sometimes faster than using an index. So the first thing you want to do, when you see that a table scan has been performed, is to see how many rows there are in the table. If there are not many, then a table scan may offer the best overall performance. But if this table is large, then a table scan will most likely take a long time to complete, and performance will suffer. In this case, you need to look into adding an appropriate index(s) to the table that the query can use. Let's say that you have identified a query that uses a table scan, but you also discover that there is an appropriate nonclustered index, but it is not being used. What does that mean, and why isn't the index being used? If the amount of data to be retrieved is large, relative to the size of the table, or if the data is not selective (which means that there are many rows with the same values in the same column), a table scan is often performed instead of an index seek because it is faster. For example, if a table has 10,000 rows, and the query returns 1,000 of them, then a table scan of a table with no clustered index will be faster than trying to use a non-clustered index. Or, if the table had 10,000 rows, and 1,000 of the rows have the same value in the same column (the column being used in the WHERE clause), a table scan is also faster than using a non-clustered index. When you view the pop-up window when you move the cursor over a table in a graphical query plan, notice the "Estimated Row Count" number. This number is the query optimizer's best guess on how many rows will be retrieved. If a table scan was done, and this number is very high, this tells you that the table scan was done because a high number of records were returned, and that the query optimizer believed that it was faster to perform a table scan than use the available non-clustered index.
Index Seek: When you see this, it means that the query optimizer used a non-clustered index on the table to look up the results. Performance is generally very quick, especially when few rows are returned.
Clustered Index Seek: If you see this, this means that the query optimizer was able to use a clustered index on the table to look up the results, and performance is very quick. In fact, this is the fastest type of index lookup SQL Server can do.
Clustered Index Scan: A clustered index scan is like a table scan, except that it is done on a table that has a clustered index. Like a regular table scan, a clustered index scan may indicate a performance problem. Generally, they occur for two different reasons. First, there may be too many rows to retrieve, relative to the total number of rows in the table. See the "Estimated Row Count" to verify this. Second, it may be due to the column queried in the WHERE clause may not be selective enough. In any event, a clustered index scan is generally faster than a standard table scan, as not all records in the table always have to be searched when a clustered index scan is run, unlike a standard table scan. Generally, the only thing you can do to change a clustered index scan to a clustered index seek is to rewrite the query so that it is more restrictive and fewer rows are returned.
In most cases, the query optimizer will analyze joins and JOIN the tables using the most efficient join type, and in the most efficient order. But not always. In the graphical query plan you will see icons that represent the different types of JOINs used in the query. In addition, each of the JOIN icons will have two arrows pointing to it. The upper arrow pointing to the JOIN icon represents the outer table in the join, and the lower arrow pointing to the JOIN icon represent the inner table in the join. Follow the arrows back to see the name of the tables being joined.
Sometimes, in queries with multiple JOINs, tracing the arrow back won't reveal a table, but another JOIN. If you place the cursor over the arrows pointing to the upper and lower JOINs, you will see a popup window that tells you how many rows are being sent to the JOIN for processing. The upper arrow should always have fewer rows than the lower arrow. If not, then the JOIN order selected by the query optimizer might be incorrect (see more on this below).
First of all, let's look at JOIN types. SQL Server can JOIN a table using three different techniques: nested loop, hash, and merge. Generally, the fastest type of join in a nested loop, but if that is not feasible, then a hash JOIN or merge JOIN is used (as appropriate), both of which tend to be slower than the nested JOIN.
When very large tables are JOINed, a merge join, not a nested loop join, may be the best option. The only way to know is to try both and see which one is the most efficient.
If a particular query is slow, and you suspect it may be because the JOIN type is not the optimum one for your data, you can override the query optimizer's choice by using a JOIN hint. Before you use a JOIN hint, you will want to take some time to learn about each of the JOIN types and how each one works. This is a complicated subject, beyond the scope of this tip.
JOIN order is also selected by the query optimizer, which it trying to select the most efficient order to JOIN tables. For example, for a nested loop join, the upper table should be the smaller of the two tables. For hash joins, the same is true; the upper table should be the smaller of the two tables. If you feel that the query optimizer is selecting the wrong order, you can override it using JOIN hints.
In many cases, the only way to know for sure if using a JOIN hint to change JOIN type or JOIN order will boost or hinder performance is to give them a try and see what happens.
Often, when viewing a graphical query execution plan, you see an icon labeled "Bookmark Lookup." Bookmark lookups are quite common to see. Essentially, they are telling you that the Query Processor had to look up the row columns it needs from a heap or a clustered index, instead of being able to read it directly from a non-clustered index.
For example, if all of the columns in the SELECT, JOIN, and WHERE clauses of a query don't all exist in the non-clustered index used to locate the rows that meet the query's criteria, then the Query Optimizer has to do extra work and look at the heap or clustered index to find all the columns it needs to satisfy the query.
Another cause of a bookmark lookup is using SELECT *, which should never be used, as in most cases it will return more data that you really need.
Bookmark lookups are not ideal from a performance perspective because extra I/O is required to look up all the columns for the rows to be returned.
If you think that a bookmark lookup is hurting a query's performance, you have four potential options to avoid it. First, you can create a clustered index that will be used by the WHERE clause, you can take advantage of index intersection, you can create a covering non-clustered index, or you can (if you have SQL Server 2000/2005 Enterprise Edition, create an indexed view. If none of these are possible, or if using one of these will use more resources than using the bookmark lookup, then the bookmark lookup is the optimal choice.

In a graphical query execution plan, often you see the Stream Aggregate icon. This just means that some sort of aggregation into a single input is being performed. This is most commonly seen when a DISTINCT clause is used, or any aggregation operator, such as AVG, COUNT, MAX, MIN, or SUM.