SQL Performance Tuning daily accumulation "turn"

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• (1) Select the most efficient table name order (valid only in the rule-based optimizer)
• (2) connection order in the WHERE clause
• (3) Avoid using ' * ' in the SELECT clause
• (4) Reduce the number of accesses to the database
• (5) Reset the ArraySize parameter in Sql*plus, sql*forms and pro*c to increase the amount of data retrieved per database access, with a recommended value of 200
• (6) Use the Decode function to reduce processing time
• (7) Integrated simple, no associated database access
• (8) Delete duplicate records
• (9) Replace Delete with truncate
• (10) Use commit as much as possible
• (11) Replace the HAVING clause with a WHERE clause
• (12) Reduce the query on the table
• (13) Improve SQL efficiency with intrinsic functions
• (14) Aliases for using the table (alias)
• (15) substituting exists with not exists instead of in
• (16) SQL statement identifying ' inefficient execution '
• (17) Improve efficiency with index
• (18) Replace distinct with exists
• SQL statements are capitalized, because Oracle always parses the SQL statements first, converting lowercase letters to uppercase and then executing
• (20) Use the connector "+" connection string sparingly in Java code!
• (21) Avoid using not on indexed columns usually
• (22) Avoid using calculations on indexed columns
• (23) Replace > with >=
• (24) Replace or with union (for indexed columns)
• (25) Replace or with in
• (26) Avoid using is null and is not NULL on an indexed column
• (27) Always use the first column of an index
• (28) Replace union with Union-all (if possible)
• (30) Avoid changing the type of indexed columns
• (31) Where clause to be careful
• A. If the number of records in a table that has more than 30% data is retrieved. Using indexes will not be significantly more efficient
• (33) Avoid using resource-intensive operations
• (34) Optimize GROUP BY
• The difference between select COUNT (*) and select COUNT (1)
• (*) is null and is not NULL
• (37) Join column
• ($) Order by statement
• (a) Not

We have to do not only write SQL, but also to write a good performance of SQL, the following for the author to learn, excerpts, and summarize some of the information to share with you!

Back to Top (1) Select the most efficient table name order (valid only in the rule-based optimizer)

The ORACLE parser processes the table names in the FROM clause in a right-to-left order, and the FROM clause is written in the final table (the underlying table, driving tables) will be processed first, and in the case where the FROM clause contains more than one table, you must select the table with the fewest number of record bars as the underlying table. If you have more than 3 tables connected to the query, you need to select the crosstab (intersection table) as the underlying table, which refers to the table that is referenced by the other table.

Back to Top (2) connection order in the WHERE clause

Oracle uses a bottom-up sequential parsing where clause, according to which the connection between tables must be written before other where conditions, and those that can filter out the maximum number of records must be written at the end of the WHERE clause.

Back to top (3) Avoid using ' * ' in the SELECT clause

In the process of parsing, Oracle converts ' * ' to all column names, which is done by querying the data dictionary, which means more time is spent

Back to Top (4) reduce the number of times the database is accessed

Oracle has done a lot of work internally: Parsing SQL statements, estimating index utilization, binding variables, reading chunks, and so on;

Back to Top (5) Reset the ArraySize parameter in Sql*plus, Sql*forms, and pro*c to increase the amount of data retrieved per database access, with a recommended value of 200 back to top (6) Use Decode function to reduce processing time

Use the Decode function to avoid duplicate scans of the same record or duplicate connections to the same table.

Back to Top (7) Integrated simple, no associated database access

If you have a few simple database query statements, you can integrate them into a single query (even if they are not related)

Back to Top (8) Delete duplicate records

The most efficient method of deleting duplicate records (because of the use of rowID) Example:

DELETE from EMP E WHERE e.rowid > (SELECT MIN (X.ROWID)

From EMP X WHERE x.emp_no = e.emp_no);

Back to Top (9) Replace Delete with truncate

When you delete a record in a table, in general, the rollback segment (rollback segments) is used to hold information that can be recovered. If you do not have a COMMIT transaction, Oracle restores the data to the state it was before it was deleted (exactly before the delete command was executed) and when the truncate is applied, the rollback segment no longer holds any recoverable information. When the command runs, The data cannot be restored. So very few resources are invoked and execution times are short. (Translator Press: truncate only in Delete full table applies, truncate is DDL is not DML)

Back to Top (10) Use commit as much as possible

Whenever possible, use commit as many of the programs as possible, so that the performance of the program is improved and the requirements are reduced by the resources freed by the commit:

Resources Freed by Commit:

A. Information for recovering data on a rollback segment.

B. Locks acquired by program statements

C. Redo space in the log buffer

D. Oracle manages internal spending on 3 of these resources

Back to Top (11) Replace the HAVING clause with a WHERE clause

Avoid having a HAVING clause that filters the result set only after all records have been retrieved. This processing requires sorting, totals, and so on. If you can limit the number of records through the WHERE clause, you can reduce this overhead. (Non-Oracle) on, where, have the three clauses that can be added conditionally, on is the first execution, where the second, having the last, because on is the non-qualifying records filtered before the statistics, it can reduce the intermediate operation to process the data, It should be said that the speed is the fastest, where should also be faster than having to, because it filters the data before the sum, in two table joins only use on, so in a table, the left where and have compared. In the case of this single-table query statistics, if the conditions to be filtered do not involve the fields to be calculated, then they will be the same result, but where you can use the Rushmore technology, and have not, at the speed of the latter slow if you want to relate to the calculated field, it means that before the calculation, The value of this field is indeterminate, according to the workflow of the previous write, where the action time is done before the calculation, and having is calculated after the function, so in this case, the results will be different. On a multi-table join query, on has an earlier effect than where. The system first synthesizes a temporary table based on the conditions of the joins between the tables, then the where is filtered, then calculated, and then filtered by having. Thus, to filter the conditions to play the right role, first of all to understand when this condition should play a role, and then decided to put it there

Back to Top (12) Reduce the query on the table

In the SQL statement that contains the subquery, pay particular attention to reducing the query on the table. Example:

Select Tab_name from TABLES WHERE (tab_name,db_ver) = (select

Tab_name,db_ver from tab_columns WHERE VERSION = 604)

Back to top (13) improve SQL efficiency with intrinsic functions

Complex SQL often sacrifices execution efficiency. The ability to master the above application function to solve the problem is very meaningful in practical work.

Back to Top (14) Alias using table

When you concatenate multiple tables in an SQL statement, use the alias of the table and prefix the alias to each column. This reduces the time to parse and reduces the syntax errors caused by column ambiguity.

Back to Top (15) Replace in with exists with not exists instead of in

In many base-table-based queries, it is often necessary to join another table in order to satisfy one condition. In this case, using EXISTS (or not EXISTS) will usually improve the efficiency of the query. In a subquery, the NOT IN clause performs an internal sort and merge. In either case, not in is the least effective (because it performs a full table traversal of the table in the subquery). To avoid using not, we can change it to an outer join (Outer Joins) or not EXISTS.

Example:

(efficient) SELECT * from EMP (base table) where EMPNO > 0 and EXISTS (select ' X ' from DEPT where DEPT. DEPTNO = EMP. DEPTNO and LOC = ' Melb ')

(Low efficiency) SELECT * from EMP (base table) where EMPNO > 0 and DEPTNO in (SELECT DEPTNO from DEPT where LOC = ' Melb ')

Back to Top (16) SQL statement identifying ' inefficient execution '

Although there are many graphical tools for SQL optimization, it is always a good idea to write your own SQL tools to solve the problem:

SELECT executions, disk_reads, Buffer_gets,

ROUND ((buffer_gets-disk_reads)/buffer_gets,2) Hit_radio,

ROUND (disk_reads/executions,2) Reads_per_run,

Sql_text

From V$sqlarea

WHERE executions>0

and buffer_gets > 0

and (Buffer_gets-disk_reads)/buffer_gets < 0.8

ORDER by 4 DESC;

Back to Top (17) Improve efficiency with indexes

An index is a conceptual part of a table used to improve the efficiency of retrieving data, and Oracle uses a complex self-balancing b-tree structure. In general, querying data through an index is faster than a full table scan. When Oracle finds the best path to execute queries and UPDATE statements, the Oracle Optimizer uses the index. Also, using indexes when joining multiple tables can improve efficiency. Another advantage of using an index is that it provides the uniqueness of the primary key (primary key) Validation: Those long or long raw data types, you can index almost all the columns. In general, using indexes in large tables is particularly effective. Of course, you will also find that using indexes can also improve efficiency when scanning small tables. Although the use of indexes can improve the efficiency of query, but we must also pay attention to its cost. Indexes require space to store, and they need to be maintained regularly, and the index itself is modified whenever a record is added to a table or the index column is modified. This means that each record's insert, DELETE, and update will pay more than 4, 5 disk I/O. Because indexes require additional storage space and processing, those unnecessary indexes can slow query response time. It is necessary to periodically refactor the index.:

ALTER INDEX <INDEXNAME> REBUILD <TABLESPACENAME>

Back to Top (18) replace distinct with exists

Avoid using DISTINCT in the SELECT clause when submitting a query that contains one-to-many table information, such as a departmental table and an employee table. It is generally possible to consider replacing with exist, EXISTS makes the query faster because the RDBMS core module will return the results immediately after the conditions of the subquery have been met. Example:

(inefficient):

SELECT DISTINCT dept_no,dept_name from DEPT D, EMP E

WHERE d.dept_no = E.dept_no

(efficient):

Select Dept_no,dept_name from DEPT D WHERE EXISTS (select ' X '

From EMP E WHERE e.dept_no = d.dept_no);

Go back to the top (+) SQL statement in uppercase; Because Oracle always parses SQL statements first, the lowercase letters are converted to uppercase and then back to the top (20) in Java code as little as possible with the connector "+" connection string! Back to top (21) Avoid using not on indexed columns usually

We want to avoid using not on indexed columns, and not to have the same effect as using functions on indexed columns. When Oracle "encounters" not, he stops using the index instead of performing a full-table scan.

Back to top (22) Avoid using calculations on indexed columns

Where clause, if the index column is part of a function. The optimizer will use a full table scan without using an index.

Example:

Low efficiency:

SELECT ... From DEPT WHERE SAL * > 25000;

Efficient:

SELECT ... From DEPT WHERE SAL > 25000/12;

Back to Top (23) Replace > with >=

Efficient:

SELECT * from EMP WHERE DEPTNO >=4

Low efficiency:

SELECT * from EMP WHERE DEPTNO >3

The difference between the two is that the former DBMS will jump directly to the first record that dept equals 4 and the latter will first navigate to the Deptno=3 record and scan forward to the first record with a dept greater than 3.

Back to Top (24) Replace or with union (for indexed columns)

In general, replacing or in a WHERE clause with Union will have a good effect. Using or on an indexed column causes a full table scan. Note that the above rules are valid only for multiple indexed columns. If a column is not indexed, the query efficiency may be reduced because you did not select or. In the following example, indexes are built on both loc_id and region.

Efficient:

SELECT loc_id, Loc_desc, Region

From location

WHERE loc_id = 10

UNION

SELECT loc_id, Loc_desc, Region

From location

WHERE region = "MELBOURNE"

Low efficiency:

SELECT loc_id, Loc_desc, Region

From location

WHERE loc_id = ten OR region = "MELBOURNE"

If you persist in using or, you need to return the least logged index column to the front.

Back to Top (25) Replace or with in

This is a simple and easy-to-remember rule, but the actual execution effect has to be tested, and under Oracle8i, the execution path seems to be the same.

Low efficiency:

SELECT .... From location WHERE loc_id = ten or loc_id = or loc_id = 30

Efficient

SELECT ... From location WHERE loc_in in (10,20,30);

Back to Top (26) Avoid using is null and is not NULL on index columns

To avoid using any nullable columns in the index, Oracle will not be able to use the index. For single-column indexes, this record will not exist in the index if the column contains null values.　For composite indexes, if each column is empty, the same record does not exist in the index. If at least one column is not empty, the record exists in the index. For example, if a uniqueness index is established on column A and column B of a table, and the table has a value of a, a and a record of (123,null), Oracle will not accept the next record (insert) with the same A, B value (123,null). However, if all the index columns are empty, Oracle will assume that the entire key value is empty and null is not equal to NULL. So you can insert 1000 records with the same key value, of course they are empty! Because null values do not exist in the index column, a null comparison of indexed columns in the WHERE clause causes Oracle to deactivate the index.

Inefficient: (Index invalidation)

SELECT ... From DEPARTMENT WHERE dept_code are not NULL;

Efficient: (Index valid)

SELECT ... From DEPARTMENT WHERE Dept_code >=0;

Back to top (27) Always use the first column of an index

If the index is built on more than one column, the optimizer chooses to use the index only if its first column (leading column) is referenced by a WHERE clause. This is also a simple and important rule, when referencing only the second column of an index, the optimizer uses a full table scan and ignores the index

Back to Top (28) Replace union with Union-all (if possible)

When the SQL statement requires a union of two query result sets, the two result sets are merged in a union-all manner and then sorted before the final result is output. If you use UNION ALL instead of union, this sort is not necessary. Efficiency will therefore be improved. It is important to note that the UNION all will output the same record in the two result set repeatedly. So you still have to analyze the feasibility of using union all from the business requirements. The UNION will sort the result set, which will use the memory of the sort_area_size. The optimization of this memory is also very important. The following SQL can be used to query the consumption of sorts

Low efficiency:

SELECT Acct_num, Balance_amt

From Debit_transactions

WHERE tran_date = ' 31-dec-95 '

UNION

SELECT Acct_num, Balance_amt

From Debit_transactions

WHERE tran_date = ' 31-dec-95 '

Efficient:

SELECT Acct_num, Balance_amt

From Debit_transactions

WHERE tran_date = ' 31-dec-95 '

UNION All

SELECT Acct_num, Balance_amt

From Debit_transactions

WHERE tran_date = ' 31-dec-95 '

(29) Where to replace order by:

The ORDER by clause uses the index only under two strict conditions.

All columns in an order by must be in the same index and remain in the order in which they are arranged in the index.

All columns in the ORDER by must be defined as non-empty.

The index used in the WHERE clause and the index used in the ORDER BY clause cannot be tied.

For example:

Table Dept contains the following:

Dept_code PK not NULL

Dept_desc not NULL

Dept_type NULL

Inefficient: (index not used)

SELECT Dept_code from DEPT ORDER by Dept_type

Efficient: (using index)

SELECT Dept_code from DEPT WHERE dept_type > 0

Back to top (30) avoid changing the type of indexed columns

Oracle automatically makes simple type conversions to columns when comparing data of different data types.

Suppose Empno is an indexed column of a numeric type.

SELECT ... From EMP WHERE EMPNO = ' 123 '

In fact, after the Oracle type conversion, the statement translates to:

SELECT ... From EMP WHERE EMPNO = to_number (' 123 ')

Fortunately, the type conversion did not occur on the index column, and the purpose of the index was not changed.

Now, suppose Emp_type is an indexed column of a character type.

SELECT ... From EMP WHERE Emp_type = 123

This statement is translated by Oracle to:

SELECT ... From EMP Whereto_number (emp_type) =123

This index will not be used because of the type conversions that occur internally! To avoid the implicit type conversion of your SQL by Oracle, it is best to explicitly express the type conversions. Note When comparing characters to numbers, Oracle takes precedence over numeric types to character types

Back to Top (31) The WHERE clause to be careful

The WHERE clause in some SELECT statements does not use an index. Here are some examples.

In the following example, (1) '! = ' will not use the index. Remember, the index can only tell you what exists in the table, not what does not exist in the table. (2) ' | | ' is a character join function. As with other functions, the index is deactivated. (3) ' + ' is a mathematical function. As with other mathematical functions, the index is deactivated. (4) The same index columns cannot be compared to each other, which will enable full table scanning.

Back to Top (+) A. If the number of records in a table that has more than 30% data is retrieved. Using indexes will not be significantly more efficient

B. In certain situations, using an index may be slower than a full table scan, but this is the same order of magnitude difference. In general, the use of indexes than the full table scan to block several times or even thousands of times!

Back to top (33) Avoid using resource-intensive operations

SQL statements with Distinct,union,minus,intersect,order by will start the SQL engine

Performs a resource-intensive sorting (sort) function. Distinct requires a sort operation, while the others need to perform at least two sorting. Typically, SQL statements with union, minus, and intersect can be overridden in other ways. If your database is well-sort_area_size, using union, minus, intersect can also be considered, after all, they are very readable

Back to Top (34) Optimize GROUP BY

Increase the efficiency of the group BY statement by filtering out unwanted records before group by. The following two queries return the same result but the second one is significantly faster.

Low efficiency:

SELECT JOB, AVG (SAL)

From EMP

GROUP by JOB

Having JOB = ' president '

OR JOB = ' MANAGER '

Efficient:

SELECT JOB, AVG (SAL)

From EMP

WHERE JOB = ' President '

OR JOB = ' MANAGER '

GROUP by JOB

Back to Top (+) SELECT COUNT (*) and select COUNT (1) Difference

In general, select COUNT (*) and select COUNT (1) both return the same result

If the table does not have a primary key (Primary key), then count (1) is faster than COUNT (*),

If there is a primary key, the primary key is the fastest when the condition of Count is the count (primary key)

If your table has only one field, then count (*) is the fastest

Count (*), like the result of Count (1), includes statistics for NULL, and Count (column) is a statistic that does not include null

Selelct Constants from ... For all rows, the return is always only one value, constant. So normal will only be used to determine if there is or not (such as the EXISTS clause). and select * From ... is all columns that return all rows.

The difference in performance, the key to see your from and WHERE clauses. For example, if your where condition can be indexed, then the Select 1 obviously from ... Performance than select * From ... Good.

Select COUNT (*) returns the number of records that meet the criteria at this time with the select SUM (1)

But sum () can pass arbitrary numbers, negative numbers, floating-point numbers, the returned value is the passed-in value N # satisfies the condition record m

Back to Top (+) is null and is not NULL

You cannot use NULL as an index, and any column that contains null values will not be included in the index. Even if the index has more than one column, the column is excluded from the index as long as there is a column in the column that contains null. This means that if a column has a null value, even indexing the column does not improve performance.

Any statement optimizer that uses is null or is not NULL in the WHERE clause is not allowed to use the index.

Back to Top (37) Join column

For a joined column, the optimizer does not use the index, even if the last join value is a static value. Let's take a look at an example, assuming that there is a staff table (employee), for a worker's surname and name in two columns (First_Name and last_name), now to query a Bill Clinton Cliton.

Here is an SQL statement that takes a join query.

SELECT * from Employss where first_name| | ' | | last_name = ' Beill Cliton ';

The above statement can be used to find out if there is a bill Cliton this employee, but it is important to note that the System optimizer does not use an index created based on last_name.

When written in this SQL statement, the Oracle system can take an index created based on last_name.

where first_name = ' Beill ' and last_name = ' Cliton ';

. A like statement with wildcard characters (%)

This is also the case with the above example. The current demand is such that the workers ' table should be queried for the person whose name contains Cliton. You can use the following query SQL statement:

SELECT * from the employee where last_name like '%cliton% ';

This is because the wildcard character (%) appears at the beginning of the search term, so the Oracle system does not use the last_name index. In many cases it may not be possible to avoid this, but be sure to be in the bottom of your mind, so using a wildcard will slow down the query. However, when wildcards appear elsewhere in a string, the optimizer can take advantage of the index. The indexes are used in the following query:

SELECT * from the employee where last_name like ' c% ';

Go back to the top of the Order by statement

The order BY statement determines how Oracle will sort the returned query results. The ORDER BY statement has no special restrictions on the columns to be sorted, or it can be added to a column (like joins or additions). Any non-indexed item in the ORDER BY statement, or a computed expression, will slow down the query.

Double-check the order BY statement to find non-indexed items or expressions that degrade performance. The solution to this problem is to rewrite the order BY statement to use the index, or you can establish another index for the column you are using, and you should absolutely avoid using an expression in the ORDER BY clause.

Back to Top (NO)

We often use logical expressions in the WHERE clause when querying, such as greater than, less than, equal to, and not equal to, and can also use and (with), or (or), and not (non). Not can be used to negate any logical operation symbol. The following is an example of a NOT clause:

... where not (status = ' VALID ')

If you want to use not, you should precede the phrase with parentheses and precede the phrase with the NOT operator. The NOT operator is included in another logical operator, which is the not equal to (<>) operator. In other words, the not is still in the operator, even if the not word is not explicitly added to the query where clause, see the following example:

... where status <> ' INVALID ';

For this query, it can be rewritten to not use not:

SELECT * FROM employee where salary<3000 or salary>3000;

Although the results of these two queries are the same, the second query scenario is faster than the first query scenario. The second query allows Oracle to use indexes on salary columns, while the first query cannot use indexes.

Although the results of these two queries are the same, the second query scenario is faster than the first query scenario. The second query allows Oracle to use indexes on salary columns, while the first query cannot use indexes.

SQL Performance Tuning daily accumulation "turn"