lesforgesdessalles.info Religion SQL PERFORMANCE EXPLAINED PDF

Sql performance explained pdf

Saturday, May 25, 2019 admin Comments(0)

I updated the PDF edition of “SQL Performance Explained” (all E.g. MySQL supports function-based indexes now, and SQL Server raised. SQL Performance Explained. Everything developers need to know about SQL performance. Markus Winand. Vienna, Austria. lesforgesdessalles.info - Download as PDF File .pdf), Text File .txt) or read online.


Author: WINIFRED LALONDE
Language: English, Spanish, Dutch
Country: Chile
Genre: Biography
Pages: 323
Published (Last): 22.08.2016
ISBN: 745-1-28291-305-5
ePub File Size: 21.63 MB
PDF File Size: 16.80 MB
Distribution: Free* [*Regsitration Required]
Downloads: 22331
Uploaded by: MARCELINO

lesforgesdessalles.info and purchase your own copy. Thank you for respecting the hard work of the author. This copy is. Contribute to marshalljj/book development by creating an account on GitHub. SQL Performance Explained: Everything Developers Need to Know about SQL SQL Performance Explained (Markus Winand) · The Mirror Site (1) - PDF.

It needs to read 18 records. Another aspect is that the Oracle database can perform the read operations for a in a more efficient way than for an index lookup. Over Indexing In case the concept of function based indexing is new to you.. This technique works also if date and time are stored as strings. To compare it with the execution plan on the better index. As expected.

If you bought it at your local book dealer, tell me when and where you bought it. I'll check your original purchase and grant you the discount. That is, however, a manual procedure and may take a while.

No matter in which order you buy, you'll get the discount if you can prove your previous purchase. Finally, I have to tell you that I'll be abroad in the next few week and I cannot dispatch international orders during this time.

That means, the last international dispatch from my office will take place on Friday. So, place your orders now. Regardless of that, there are more than enough copies on stock at Amazon. They will take care of your order at any time but might charge shipping fees. Oh, I forgot one more thing. Some readers from the United States have reported that they didn't have to pay any custom duties or other fees after receiving the hard copy.

So, if you are in the US, it seems that you don't need to worry about customs when ordering the hard copy. SQL Performance Explained. Markus Winand teaches efficient SQL— inhouse and online.

He minimizes the development time using modern SQL and optimizes the runtime with smart indexing. Buy on Amazon paperback only. Surrogate keys have become the predominant form of primary keys for many good reasons. Tip http: Deferred constraints are required to propagate data into tables with circular foreign key dependencies. Tip The execution plan sometimes explain plan or query plan shows the steps to execute a statement.

The subsequent table access is therefore not at risk to read many blocks. It can be gathered with the explain plan command. In case the searched key is the last in its leaf node. The primary key lookup. They are easy to handle. According to the previous chapter. Because the constraint still maintains the uniqueness of every key.

An can not return more than one. In that case. As first example. Almost independent of the data volume. The Oracle database creates a unique index according to the definition of the primary key automatically.

As expected. One reason to intentionally use a nonunique index to enforce a primary key or unique constraint is to make the constraint deferrable. The database must perform an additional step. There is no need for a separate create index statement in that case.

Surrogate Keys Primary keys are often generated from a sequence and stored in an column for the sole purpose to serve as surrogate key. You don't need to know more than that to follow the examples but if you like to try them out for yourself.

The constellation becomes more interesting when the where clause doesn't contain all the indexed columns. The indexes used to support the search on multiple columns are called concatenated or composite indexes. The values can be reassigned—theoretically—because it's not a natural but a surrogate key. Myth Directory has more details. Adding a new column to maintain the uniqueness is often the path of least resistance. The database must read and process the index nodes in a block-by-block manner.

A closer look into the index leaf nodes makes it more apparent. The is amongst the most critical operations used by the database and almost always a problem in online systems. The values of the subsequent index columns are not centralized within the leaf node structure and cannot be localized with a tree traversal. The database doesn't use the index because it is not suitable for this query. The database performs a. After all. A must read the entire table anyway.

As a consequence. No index is used. To repeat the most important lesson from the previous chapter: Although this sounds odd in the first place. A reads all table blocks and evaluates every row against the where clause. The order of the individual columns within a concatenated index is not only a frequent cause of confusion but also the foundation for an extraordinary resistant myth. A query to fetch the name of a particular employee has to state both columns in the where clause: As intended and expected.

If the number of selected rows is a considerable fraction of the overall table size. Unfortunately the surrogate key values used in our table collide with those used by the Very Big Company. Full Table Scan There are several cases when the database considers a the most effective way to retrieve the requested data.

Concatenated Keys Although surrogate keys are widely accepted and implemented. The truth is that the column order affects the number of statements that can use the index. All of that should not hide the fact that a is often caused by a missing or inadequate index.

In case multiple columns are indexed. Another aspect is that the Oracle database can perform the read operations for a in a more efficient way than for an index lookup. For the sake of demonstration. The new employee table contains all employees from both companies and has ten times as many records as before. The primary key is extended accordingly. The performance degrades linear with the data volume. The blocks needed for an index lookup are not known in advance. The tree cannot be used to find those entries.

The original definition served queries for only while the new definition supports queries on only. Although the solution seems to be perfectly reasonable. To choose the right index. The following SQL template returns the indexed columns in index order.

The easiest solution to tune the query is to create a new index on. The index consists of the and columns in that order. Although the two-index solution will also yield very good select performance. Tip Visualizing an index like Figure 2. The trick is to change the column order in the index so that the new index definition is as follows: The index is still unique. If you insert the index definition and the corresponding table name into that statement.

Although such a figure is very nice. It is usually enough to see the index order and know that the tree can quickly localize one particular place within this sequence. It seems like the primary key index doesn't support the query to list all employees of a subsidiary.

Ask yourself where you would start to search for the required data. Although two index entries match the filter. The reversed column order changed which statements can be supported by the index. Concatenated Index Figure 2. Important When defining an index.

Figure 2. This index boosts the queries performance immediately: The execution plan shows an on the new index. Considering that a search for an in any subsidiary is very unlikely. If there isn't any particular place where the searched values appear together.

The preserved space might even increase the cache-hit rate so that the overall scalability improves. The search for is not supported by the index because the matching entries are distributed over a wide range of the index. An external performance consultant can have a very hard time to figure out which columns can go alone into the where clause and which are always paired with other attributes.

The knowledge about dependencies between various attributes is essential to define an index correctly. The only place where the technical database knowledge meets the functional knowledge of the business domain is the development department. As long as you are not familiar with the business domain. Despite the fact that internal database administrators know the industry of their company often better than external consultants.

I know that it becomes a very depressing task if practiced on an every day basis. Although I admit that reverse engineering can be fun if practiced every now and then.

This section drafts a constellation that tempts the optimizer to use an inappropriate index. This process is often called parsing.

A step-by-step investigation of the execution plan is the best way to find the problem. The following statement uses a hint that instructs the optimizer not to use the new index for this query: The original execution plan uses a and has a higher cost value than the: Even though the must read all table blocks and process all table rows.

Although the switchboard operators enter as much search criteria as possible. Although the changed index improves performance of all queries that use a subsidiary filter without any other clause. An index lookup for one particular record should outperform the —but it doesn't. The new problem—after the index change—is that the telephone directory application has become very slow.

Calculating the cost value is a complex matter that easily fills a book of its own. Bearing in mind that the original index definition—with in the first position—didn't support the statement. The cost value serves as benchmark to compare the various execution plans.

The original execution plan can be checked with the use of an optimizer hint. From users perspective it is sufficient to know that the optimizer believes a lower cost value results in a better statement execution.

The so-called Cost Based Optimizer CBO generates various execution plan permutations and assigns a cost value to each one. The optimizer is well aware that my name isn't very common and estimates a total row count of one. It's the optimizer's job to decide which index to use—or not to use an index at all. It turns out that the following SQL is very slow: The execution plan is: Example 2.

Please note that the query uses the redefined primary key index. You probably know from your own experience: Part II The previous chapter has demonstrated that a changed column order can gain additional benefits from an existing index. An index change can influence all statements that access the corresponding table. Because the second filter criteria—on —is not included in the index. Hints provide additional information to the optimizer in form of particularly formatted SQL comments. The first step is the which finds all entries that match the filter.

Even if an index can support a query. The Query Optimizer The query optimizer is the database component that transforms an SQL statement into an execution plan. An index is used and the cost value is rather low. Slow Indexes. At least not without comprehensive testing beforehand.

Execution plan with revised primary key index On the first sight. The operation has the operation Id 2. The most important statistics for an are the size of the index number of rows in the index and the selectivity of the respective predicate the fraction that satisfies the filter. That means that it reads a small fraction of the table during query planning to get a basis for the estimates. The next step in the execution plan is the that fetches the identified rows from the table.

As of Oracle 11g it is also possible to collect extended statistics for column concatenations and expressions. The discussion about bad index performance and a fast should not hide the fact that a properly defined index is the best solution.

The optimizer uses these values to estimate the selectivity of the predicates in the where clause. The most important index statistics are the tree depth. Dynamic sampling is enabled per default since Oracle release 9.

The new estimates are very close to the actual values: Fetching records individually with the is rather expensive. Most statistics are collected per table column: The expensive operation is the..

For a small subsidiary— e. There are only very few statistics for the table as such: The optimizer will automatically prefer the because its cost of indicates a better performance.

Execution Plan with Dedicated Index. The estimated rows count for the changed to The performance of this select statement is vastly depended on the number of employees in the particular subsidiary.

Once the complete row— with all columns—is available. It reveals the optimizer's estimation that the will return 40 rows—Example 2.

The second filter—on —is expected to reduce the result set down to a single row. The cost value of the new execution plan has grown to almost They consist of various information about the tables and indexes in the database. A closer look to the plan reveals that the is.

The optimizer uses the so-called optimizer statistics for its estimates. They are usually collected and updated on a regular basis by the administrator or an automated job. To support a search by last name. If there are no statistics available—as I deleted them on purpose.

Release 10g changed the default to perform dynamic sampling more aggressively. The result of the is a list of matching that satisfy the filter on. Correct statistics lead to more realistic estimates in the execution plan. If there are no statistics available. Depending on the size of the subsidiary. This information can help to understand why the optimizer has chosen a particular execution plan.

Statistics and Dynamic Sampling The optimizer can use a variety of statistics on table. Besides the individual steps performed during the query. All the rows returned from the are read from the table and filtered by the predicate related to the operation: The phone directory lookup is slow because the returns thousand records—all employees from the original company—and the must fetch all of them. The optimizer calculates a cost value of 3 for the new plan: The remaining rows are those that fulfill the entire where clause.

The default statistics suggest a small index with medium selectivity and lead to the estimation that the will return 40 rows. Under this presumption.

Because of the statistics, the optimizer knows that is more selective than the. It estimates that only one row will fulfill the predicate of the index lookup—on —so that only row has to be retrieved from the table. Please note that the difference in the execution plans as shown in figures Example 2. The performed operations are the same and the cost is low in both cases.

Nevertheless the second plan performs much better than the first. The efficiency of an —especially when accompanied by a —can vary in a wide range. Just because an index is used doesn't mean the performance is good. Functions The index in the previous section has improved the performance considerably, but you probably noticed that it works only if the names are stored in all caps.

That's obviously not the way we would like to store our data. This section describes the solution to this kind of problem as well as the limitations. The backup solution is to create a real column in the table that holds the result of the expression. The column must be maintained by a trigger or by the application layer—whatever is more appropriate.

The new column can be indexed like any other, SQL statements must query the new column without the expression. MySQL is case-insensitive by default, but that can be controlled on column level.

Virtual columns are in the queue for version 6. Oracle The Oracle database supports function based indexes since release 8i.

Pdf explained sql performance

Virtual columns were additionally added with 11g. Case-Insensitive Search The SQL for a case-insensitive search is very simple—just upper case both sides of the search expression:. The query works by converting both sides of the comparison to the same notation. No matter how the is stored, or the search term is entered, the upper case on both sides will make them match. From functional perspective, this is a reasonable SQL statement.

However, let's have a look at the execution plan:. It's a comeback of our old friend the full table scan. The index on is unusable because the search is not on last name—it's on. From the database's perspective, that's something entirely different. It's a trap we all fall into. In fact, the optimizer's picture is more like that:.

The function is just a black box—hence the index on cannot be used. Tip Thinking of a black box instead of the real function helps to understand the optimizer's point of view. Evaluating Literal Expressions The optimizer is able to evaluate the expression on the right hand side of the comparison because it doesn't refer to table data or bind parameters.

That's very similar to a compiler that is able to evaluate constant expressions at compile time. Analogous, the optimizer can evaluate literal expressions at parse time.

The predicate information section of the execution plan shows the evaluated expression. To support that query, an index on the actual search expression is required; that is, a so-called function based index.

Although the name function based index suggests a special feature, it is just an ordinary B-Tree index that is applied upon an expression instead of a column. The following statement creates an index that supports the query:. The create statement for a function based index is very similar to a regular index—there is no special keyword. The difference is that an expression is used instead of a column name.

The index stores the all capitalized notation of the column. It can be shown like described in the tip on index visualization:. The Oracle database can use a function based index if the exact expression of the index definition appears in an SQL statement—like in the example above—so that the new execution plan uses the index:.

It is a normal. My general advice is to always backup statistics before updating them.

Pdf explained sql performance

The box Collecting Statistics has more information why the table statistics are relevant and what to take care of when updating statistics.

Previous releases might behave differently. Although the execution performance is not improved by the updated statistics—because the index was correctly used anyway—it is always good to have a look at the optimizer's estimates.

Statistics for a function based index FBI are implemented as virtual columns on table level. Although the index statistics are automatically collected on index creation since 10g. Such statistics will enable Oracle Database to correctly decide when to use the index. Warning and is sometimes used without developer's knowledge. The package can collect the statistics on the virtual column after the FBI was created—when the virtual column exists.

Collecting and updating statistics is a task that should be coordinated with the DBAs. This particular problem has a very common cause. The number of rows processed for each step cardinality is a very important figure for the optimizer—getting them right for simple queries can easily pay off for complex queries.

How can the table access match records if the preceding index scan returned only 40 rows? After updating the table statistics.

Note Statistics for function based indexes and multi-column statistics were introduced with Oracle release 11g.. The Oracle documentation says: After creating a function-based index.

The optimizer is heavily depending on the statistics— there is a high risk to run into trouble. The execution plan has one more issue: The number of rows returned by the table access is even higher than the number of rows expected from the. Anatomy of an Index. Collecting Statistics The column statistics. The reason behind this limitation is easily explained. Caution The Oracle database trusts the keyword—that means. Besides being deterministic.

The only way to update an individual index entry is to update an indexed column of the respective record.

Just remember that the return value of the function will be physically stored in the index when the record is inserted. Other examples for functions that cannot be indexed are the members of the package and functions that implicitly depend on the environment—such as NLS National Language Support settings.

The function converts the date of birth into an age—according to the current system time. Regardless of that. It can be used in the select-list to query an employees age.

In particular. Only functions that always return the same result for the same parameters—functions that are deterministic—can be indexed. Although it's a very convenient way search for all employees who are 42 years old. The function can be declared so that the database allows an index on. There is no background job that would update the age on the employee's birthday—that's just not happening. User Defined Functions A case-insensitive search is probably the most common use for a function based index—but other functions can be "indexed" as well.

In fact. Tip Unify the access path in all statements so that less indexes can achieve more. The better solution— for this particular query—is to use the same expression for all case-insensitive searches on.

Real world examples are much more subtle—unfortunately. Every statement puts a huge burden on the database: Warning and is sometimes used without developers knowledge. Every index has its cost. That is often the most useful information you can put into an index.

Consider the case-insensitive search again: All of that. Use it wisely. Tip Always aim to index the original data. Over Indexing In case the concept of function based indexing is new to you.. But there are other ways to implement a case-insensitive search: That query can't use the index—it's a different expression! An index on would be redundant—obviously. Another question to think about is when to use function based indexes? Do you have examples? Try to find the solution and share your thoughts on the forum.

Open your mind to find the solution. But watch out. In this respect. The actual values for the placeholder are provided through a separate API call. The general rule is therefore to use bind variables in programs.

Bind parameter—also called dynamic parameters or bind variables—are an alternative way to provide data to the database.. Different search terms can. Re-using an execution plan means that the same execution plan will be used for different search terms. That means.. Instead of putting the values literally into the SQL statement. An execution plan that is tailor-made for a particular search value doesn't came for free.

Tip Status flags such as "todo" and "done" have a nonuniform distribution very often. That's for two reasons: Security Bind variables are the best way to prevent SQL injection. The histogram indicates which values appear more often than others. Column Histograms A column histogram is the part of the table statistics that holds the outline of the data distribution of a column. The use of bind parameters might prevent the best possible execution plan for each status value.

The optimizer has to re-create the execution plan every time a new distinct value appears. While an is best for small and medium subsidiaries. The Oracle database uses two different types of histograms that serve the same purpose: Performance The Oracle optimizer can re-use a cached execution plan if the very same statement is executed multiple times. In this case. As soon as the SQL statement differs—e. If bind variables are used. Bind Parameter This section covers a topic that is way too often ignored in textbooks.

Even though literal values are very handy for ad-hoc statements. There is. That has. On the other hand is parsing a very expensive task that should be avoided whenever possible. In the compiler analogy. Instead of. On the one hand. The application developer can come to help with this dilemma. C Instead of use the following Further documentation: Please note that the SQL standard defines positional parameters only—not named ones.

The dilemma is that the optimizer doesn't know in advance if the different values will result in a different execution plan. Tip In case of doubt. The database has a little dilemma when deciding to use a cached version of the execution plan or to parse the statement again. The following code snippets are examples how to use bind parameters.

Java Instead of use the following Further documentation: Most databases and abstraction layers support named bind parameters nevertheless—in a nonstandard way. The rule is to use bind values except for fields where you expect a benefit from a column histogram—e. Perl Instead of use the following Further documentation: Programming the Perl DBI.

If you insert the index definition and the corresponding table name into that statement. The trick is to change the column order in the index so that the new index definition is as follows: The index is still unique. Although such a figure is very nice.

Important When defining an index. Tip Visualizing an index like Figure 2. Although I admit that reverse engineering can be fun if practiced every now and then.

Despite the fact that internal database administrators know the industry of their company often better than external consultants.

I know that it becomes a very depressing task if practiced on an every day basis. The knowledge about dependencies between various attributes is essential to define an index correctly. An external performance consultant can have a very hard time to figure out which columns can go alone into the where clause and which are always paired with other attributes.

The only place where the technical database knowledge meets the functional knowledge of the business domain is the development department.

As long as you are not familiar with the business domain. The optimizer is well aware that my name isn't very common and estimates a total row count of one. A step-by-step investigation of the execution plan is the best way to find the problem. The following statement uses a hint that instructs the optimizer not to use the new index for this query: The original execution plan uses a and has a higher cost value than the: Even though the must read all table blocks and process all table rows.

The new problem—after the index change—is that the telephone directory application has become very slow. It turns out that the following SQL is very slow: The execution plan is: Example 2.

Although the changed index improves performance of all queries that use a subsidiary filter without any other clause. An index lookup for one particular record should outperform the —but it doesn't. The original execution plan can be checked with the use of an optimizer hint. Even if an index can support a query. The so-called Cost Based Optimizer CBO generates various execution plan permutations and assigns a cost value to each one.

Bearing in mind that the original index definition—with in the first position—didn't support the statement. The Query Optimizer The query optimizer is the database component that transforms an SQL statement into an execution plan. It's the optimizer's job to decide which index to use—or not to use an index at all.

Execution plan with revised primary key index On the first sight. The cost value serves as benchmark to compare the various execution plans. This process is often called parsing. The operation has the operation Id 2. Part II The previous chapter has demonstrated that a changed column order can gain additional benefits from an existing index. An index change can influence all statements that access the corresponding table.

An index is used and the cost value is rather low. At least not without comprehensive testing beforehand. Slow Indexes. Because the second filter criteria—on —is not included in the index. From users perspective it is sufficient to know that the optimizer believes a lower cost value results in a better statement execution. Calculating the cost value is a complex matter that easily fills a book of its own.

The first step is the which finds all entries that match the filter. Please note that the query uses the redefined primary key index. Although the switchboard operators enter as much search criteria as possible. You probably know from your own experience: Hints provide additional information to the optimizer in form of particularly formatted SQL comments. This section drafts a constellation that tempts the optimizer to use an inappropriate index.

The second filter—on —is expected to reduce the result set down to a single row. Once the complete row— with all columns—is available. Statistics and Dynamic Sampling The optimizer can use a variety of statistics on table. They are usually collected and updated on a regular basis by the administrator or an automated job.

The optimizer will automatically prefer the because its cost of indicates a better performance. This information can help to understand why the optimizer has chosen a particular execution plan. The discussion about bad index performance and a fast should not hide the fact that a properly defined index is the best solution. Execution Plan with Dedicated Index. The expensive operation is the. The cost value of the new execution plan has grown to almost Most statistics are collected per table column: The performance of this select statement is vastly depended on the number of employees in the particular subsidiary.

The most important index statistics are the tree depth. The new estimates are very close to the actual values: Fetching records individually with the is rather expensive. Dynamic sampling is enabled per default since Oracle release 9. The optimizer calculates a cost value of 3 for the new plan: The default statistics suggest a small index with medium selectivity and lead to the estimation that the will return 40 rows. That means that it reads a small fraction of the table during query planning to get a basis for the estimates.

Release 10g changed the default to perform dynamic sampling more aggressively. The phone directory lookup is slow because the returns thousand records—all employees from the original company—and the must fetch all of them. If there are no statistics available—as I deleted them on purpose.

Besides the individual steps performed during the query. The optimizer uses these values to estimate the selectivity of the predicates in the where clause. The most important statistics for an are the size of the index number of rows in the index and the selectivity of the respective predicate the fraction that satisfies the filter.

The result of the is a list of matching that satisfy the filter on. Correct statistics lead to more realistic estimates in the execution plan. They consist of various information about the tables and indexes in the database.

Convinced: Selling a PDF edition of SQL Performance Explained for EUR

The optimizer uses the so-called optimizer statistics for its estimates. The next step in the execution plan is the that fetches the identified rows from the table.. Depending on the size of the subsidiary. To support a search by last name. There are only very few statistics for the table as such: The remaining rows are those that fulfill the entire where clause.

For a small subsidiary— e. A closer look to the plan reveals that the is. Under this presumption. The estimated rows count for the changed to It reveals the optimizer's estimation that the will return 40 rows—Example 2.

If there are no statistics available. All the rows returned from the are read from the table and filtered by the predicate related to the operation: As of Oracle 11g it is also possible to collect extended statistics for column concatenations and expressions. Because of the statistics, the optimizer knows that is more selective than the. It estimates that only one row will fulfill the predicate of the index lookup—on —so that only row has to be retrieved from the table.

Please note that the difference in the execution plans as shown in figures Example 2. The performed operations are the same and the cost is low in both cases. Nevertheless the second plan performs much better than the first.

The efficiency of an —especially when accompanied by a —can vary in a wide range. Just because an index is used doesn't mean the performance is good. Functions The index in the previous section has improved the performance considerably, but you probably noticed that it works only if the names are stored in all caps.

That's obviously not the way we would like to store our data. This section describes the solution to this kind of problem as well as the limitations. The backup solution is to create a real column in the table that holds the result of the expression. The column must be maintained by a trigger or by the application layer—whatever is more appropriate. The new column can be indexed like any other, SQL statements must query the new column without the expression.

MySQL is case-insensitive by default, but that can be controlled on column level. Virtual columns are in the queue for version 6. Oracle The Oracle database supports function based indexes since release 8i. Virtual columns were additionally added with 11g. Case-Insensitive Search The SQL for a case-insensitive search is very simple—just upper case both sides of the search expression:. The query works by converting both sides of the comparison to the same notation.

No matter how the is stored, or the search term is entered, the upper case on both sides will make them match.

From functional perspective, this is a reasonable SQL statement. However, let's have a look at the execution plan:. It's a comeback of our old friend the full table scan. The index on is unusable because the search is not on last name—it's on. From the database's perspective, that's something entirely different. It's a trap we all fall into. In fact, the optimizer's picture is more like that:. Tip Thinking of a black box instead of the real function helps to understand the optimizer's point of view.

Evaluating Literal Expressions The optimizer is able to evaluate the expression on the right hand side of the comparison because it doesn't refer to table data or bind parameters. That's very similar to a compiler that is able to evaluate constant expressions at compile time.

Analogous, the optimizer can evaluate literal expressions at parse time. The predicate information section of the execution plan shows the evaluated expression. To support that query, an index on the actual search expression is required; that is, a so-called function based index. Although the name function based index suggests a special feature, it is just an ordinary B-Tree index that is applied upon an expression instead of a column.

The following statement creates an index that supports the query:. The create statement for a function based index is very similar to a regular index—there is no special keyword. The difference is that an expression is used instead of a column name.

The index stores the all capitalized notation of the column. It can be shown like described in the tip on index visualization:. The Oracle database can use a function based index if the exact expression of the index definition appears in an SQL statement—like in the example above—so that the new execution plan uses the index:.

Warning and is sometimes used without developer's knowledge. Collecting Statistics The column statistics. The package can collect the statistics on the virtual column after the FBI was created—when the virtual column exists. This particular problem has a very common cause. The Oracle documentation says: After creating a function-based index. Anatomy of an Index. The number of rows processed for each step cardinality is a very important figure for the optimizer—getting them right for simple queries can easily pay off for complex queries.

Although the index statistics are automatically collected on index creation since 10g. The execution plan has one more issue: How can the table access match records if the preceding index scan returned only 40 rows?

Blog Archive

Previous releases might behave differently. Note Statistics for function based indexes and multi-column statistics were introduced with Oracle release 11g.

My general advice is to always backup statistics before updating them. After updating the table statistics. Such statistics Collecting and updating statistics is a task that should be coordinated with the DBAs. Although the execution performance is not improved by the updated statistics—because the index was correctly used anyway—it is always good to have a look at the optimizer's estimates.

Statistics for a function based index FBI are implemented as virtual columns on table level. The box Collecting Statistics has more information why the table statistics are relevant and what to take care of when updating statistics.

It is a normal. The optimizer is heavily depending on the statistics— there is a high risk to run into trouble. The number of rows returned by the table access is even higher than the number of rows expected from the. Regardless of that. The reason behind this limitation is easily explained. There is no background job that would update the age on the employee's birthday—that's just not happening.

Only functions that always return the same result for the same parameters—functions that are deterministic—can be indexed. It can be used in the select-list to query an employees age. The function converts the date of birth into an age—according to the current system time. Other examples for functions that cannot be indexed are the members of the package and functions that implicitly depend on the environment—such as NLS National Language Support settings.

In fact. The function can be declared so that the database allows an index on.

SQL Performance Explained - Markus Winand

In particular. Although it's a very convenient way search for all employees who are 42 years old. The only way to update an individual index entry is to update an indexed column of the respective record. Caution The Oracle database trusts the keyword—that means. User Defined Functions A case-insensitive search is probably the most common use for a function based index—but other functions can be "indexed" as well.

Just remember that the return value of the function will be physically stored in the index when the record is inserted. Besides being deterministic. That is often the most useful information you can put into an index. Every index has its cost. Use it wisely. Consider the case-insensitive search again: Over Indexing In case the concept of function based indexing is new to you. Tip Always aim to index the original data.

Every statement puts a huge burden on the database: The better solution— for this particular query—is to use the same expression for all case-insensitive searches on. Tip Unify the access path in all statements so that less indexes can achieve more. All of that. Real world examples are much more subtle—unfortunately.

But there are other ways to implement a case-insensitive search: That query can't use the index—it's a different expression! An index on would be redundant—obviously.

Warning and is sometimes used without developers knowledge. Another question to think about is when to use function based indexes? Do you have examples? Open your mind to find the solution. But watch out.

Performance explained pdf sql

Try to find the solution and share your thoughts on the forum. In this respect. If bind variables are used. The general rule is therefore to use bind variables in programs. The use of bind parameters might prevent the best possible execution plan for each status value.

That's for two reasons: Security Bind variables are the best way to prevent SQL injection. In this case. An execution plan that is tailor-made for a particular search value doesn't came for free. There is. Different search terms can. The histogram indicates which values appear more often than others. The optimizer has to re-create the execution plan every time a new distinct value appears.

Bind Parameter This section covers a topic that is way too often ignored in textbooks. Tip Status flags such as "todo" and "done" have a nonuniform distribution very often. Even though literal values are very handy for ad-hoc statements. Instead of putting the values literally into the SQL statement. Column Histograms A column histogram is the part of the table statistics that holds the outline of the data distribution of a column. That has.

The actual values for the placeholder are provided through a separate API call. Performance The Oracle optimizer can re-use a cached execution plan if the very same statement is executed multiple times. Re-using an execution plan means that the same execution plan will be used for different search terms. Bind parameter—also called dynamic parameters or bind variables—are an alternative way to provide data to the database. The Oracle database uses two different types of histograms that serve the same purpose: As soon as the SQL statement differs—e.

While an is best for small and medium subsidiaries. On the one hand. The following code snippets are examples how to use bind parameters. The application developer can come to help with this dilemma.

On the other hand is parsing a very expensive task that should be avoided whenever possible. Most databases and abstraction layers support named bind parameters nevertheless—in a nonstandard way.. The database has a little dilemma when deciding to use a cached version of the execution plan or to parse the statement again.

C Instead of use the following Further documentation: Instead of. Perl Instead of use the following Further documentation: Programming the Perl DBI. In the compiler analogy. Please note that the SQL standard defines positional parameters only—not named ones. The dilemma is that the optimizer doesn't know in advance if the different values will result in a different execution plan.

Java Instead of use the following Further documentation: The rule is to use bind values except for fields where you expect a benefit from a column histogram—e. Tip In case of doubt. All those features attempt to cope with a problem that can be handled by the application. In other words.. The problem with that approach is its nondeterministic behavior: Note Bind parameters cannot change the structure of an SQL statement.

The execution plan can change every time the database is restarted or. This feature enables the database to have multiple execution plans for the same SQL statement. On top of that. With release 9i. Bind peeking enables the optimizer to use the actual bind values of the first execution during parsing.

The Oracle database does not natively support question marks but uses the colon syntax for named placeholder. If there is a heavy imbalance upon the distribution of search keys. Oracle introduced the so-called bind peeking. Ruby Instead of use the following: Further documentation: That means that the first execution must run slow before the second execution can benefit.

Release 11g introduced adaptive cursor sharing to cope with the problem. The PDO interface supports prepared statements as well. For that reason. Oracle Cursor Sharing. In case one execution runs much slower than the others. Oracle has introduced the setting that allows the database to re-write the SQL to use bind parameters typically named. The by far most common problem are applications that do not use bind parameters at all.

Non of the following two bind parameters works: If you need to change the structure of an SQL statement. DB2 DB2 does not treat the empty string as. Other side effects are much more subtle—but have a huge performance impact.

Some of them need special attention in SQL—e. This section describes the most common performance issues when handling in the Oracle database—in that respect. Although the basic idea of —to represent missing data—is rather simple. Oracle The Oracle database does not include rows into an index if all indexed columns are. As soon as any index column is not null. The index is postfixed with a constant string that can never be.

Even faked columns can be used. This index can therefore support a query for all employees of a specific subsidiary where the date of birth is null: Please note that the index covers the entire where clause. Like with any other concatenated index.

That makes sure that the index has all rows.. This concept can be extended to find all records where date of birth is null—regardless of the subsidiary. DB2 DB2 includes into every index. The new row is included in the demo index because the subsidiary is not null for that row. Any column that cannot be —e. Tip Putting a column that cannot be into an index allows indexing It is.

The property of the column is lost. As soon as the not null constraint is removed. An index on a user defined function.

Although we can see that the function passes the input value straight through. It's not possible to use the index to find all records. Tip A missing constraint is often causing statements to do a full table scan. Altering system generated virtual columns to is possible. The statement can use the index because it selects only the records where the expression is not null.

Removing the constraint on the base columns renders the index. Virtual columns serve a similar purpose as functional indexes. But that's for internal The function preserves the unusable: They are.. But they can be indexed. The added where clause is an indirect way to put the not null constraint on the expression. These virtual columns can have a constraint: Databases with native support for partial indexes can use it to select all and records—but not for any other state.

New items are constantly put into the queue. The Oracle database doesn't support partial indexes as demonstrated above but has an implicit clause in every index. An index on state is a good candidate for a partial index that doesn't contain the "done" records.

Partial Indexes. Whenever a query selects the "done" rows. The index definition. A partial index is an index that does not contain all rows from the table.

Oracle The Oracle database has only indirect support for partial indexes that is described in this section. This scenario will lead to a non-uniform data distribution because the "done" records accumulate over the time. Part II As of Oracle release 11g. Mapping any value that shall not be indexed to simulates a partial index: The oddity with that is that the SQL statement must use the function—otherwise the index can't be used: Although this kind of emulated partial index is known to work.

This is. There is no equivalent for the feature that is described here. In case you would like to try the new approach. Documentation is available in the PostgreSQL manual. It is often implemented as where clause in the index definition. In other words. The new approach does not exploit the trick and does therefore not belong into this section anyway. The purpose of a partial index is to keep the index small.

DB2 DB2 does not support partial indexes.