Java SQL statement optimization experience and PostgreSQL statement Optimization

Java SQL statement optimization experience and PostgreSQL statement Optimization

Java SQL statement optimization experience

(1) select the most efficient table name sequence (only valid in the rule-based seo/'target = '_ blank'> Optimizer ):
The ORACLE parser processes the table names in the FROM clause in the order FROM right to left. The table written in the FROM clause (basic table driving table) will be processed first, when the FROM clause contains multiple tables, You must select the table with the least number of records as the base table. If more than three tables are connected for query, You need to select an intersection table as the base table, which is the table referenced by other tables.

(2) join order in the WHERE clause .:
ORACLE uses the bottom-up sequence to parse the WHERE clause. According to this principle, the join between tables must be written before other WHERE conditions. The conditions that can filter out the maximum number of records must be written at the end of the WHERE clause.

(3) Avoid using '*' in the SELECT clause '*':
During the parsing process, ORACLE converts '*' into all column names in sequence. This is done by querying the data dictionary, which means it takes more time.

(4) Reduce the number of times to access the get = '_ blank'> database:
ORACLE has performed a lot of internal work: parsing SQL statements, estimating index utilization, binding variables, and reading data blocks;

(5) re-set the ARRAYSIZE parameter in SQL * Plus, SQL * Forms, and Pro * C to increase the retrieval data volume for each get = '_ blank'> database access, recommended Value: 200

(6) use the DECODE function to reduce processing time:
You can use the DECODE function to avoid repeated scan of the same record or join the same table.

(7) simple integration, unrelated get = '_ blank'> database access:
If you have a few simple get = '_ blank'> database query statements, you can integrate them into a query (even if there is no relationship between them)

(8) delete duplicate records:
The most efficient way to delete duplicate records (because ROWID is used) is as follows:
Delete from emp e where e. ROWID> (select min (X. ROWID)
From emp x where x. EMP_NO = E. EMP_NO );

(9) replace DELETE with TRUNCATE:
When deleting records in a table, a rollback segment is usually used to store information that can be recovered. if you do not have a COMMIT transaction, ORACLE will recover the data to the State before the deletion (which is precisely the State before the deletion command is executed). When TRUNCATE is used, rollback segments no longer store any recoverable information. after the command is run, the data cannot be restored. therefore, few resources are called and the execution time is short. (The translator Press: TRUNCATE applies only to deleting the entire table, and TRUNCATE is DDL rather than DML)

(10) Try to use COMMIT as much as possible:
As long as possible, use COMMIT as much as possible in the program, so that the program's performance is improved, and the demand will also be reduced by the resources released by COMMIT:
Resources released by COMMIT:
A. Information used to restore data on the rollback segment.
B. Locks obtained by Program Statements
C. Space in redo log buffer
D. ORACLE manages the internal costs of the above three types of resources

(11) replace HAVING clause with the Where clause:
Avoid using the HAVING clause. HAVING filters the result set only after all records are retrieved. this process requires sorting, total, and other operations. if the WHERE clause can be used to limit the number of records, this overhead can be reduced. (in non-oracle) where on, where, and having can be added, on is the first statement to execute, where is the second clause, and having is the last clause, because on filters out records that do not meet the conditions before making statistics, it can reduce the data to be processed by intermediate operations. It is reasonable to say that the speed is the fastest, where should also be faster than having, because it performs sum only after filtering data, and on is used only when two tables are joined, so in a table, then we can compare where with having. In the case of single-Table query statistics, if the filter condition does not involve fields to be calculated, the results will be the same, but the where technology can be used, having cannot be used. In terms of speed, the latter must be slow. If a calculated field is involved, the value of this field is uncertain before calculation, according to the workflow written in the previous article, the where function time is completed before computing, and having works only after computing. In this case, the results are different. In multi-table join queries, on takes effect earlier than where. The system first combines multiple tables into a temporary table based on the join conditions between tables, then filters them by where, then computes them, and then filters them by having after calculation. It can be seen that to filter a condition to play a correct role, you must first understand when the condition should take effect, and then decide to put it there.

(12) Reduce table queries:
In SQL statements containing subqueries, pay special attention to reducing the number of queries to the table. Example:
SELECT TAB_NAME from tables where (TAB_NAME, DB_VER) = (SELECT
TAB_NAME, DB_VER FROM TAB_COLUMNS where version = 604)

(13) Improve SQL efficiency through internal functions .:
Complex SQL statements tend to sacrifice execution efficiency. It is very meaningful to grasp the above methods to solve problems by using functions.

(14) use the table Alias (Alias ):
When connecting multiple tables in an SQL statement, use the table alias and prefix the alias on each Column. in this way, the parsing time can be reduced and the syntax errors caused by Column ambiguity can be reduced.

(15) Replace IN with EXISTS and not exists instead of not in:
In many basic table-based queries, to meet one condition, you often need to join another table. in this case, using EXISTS (or not exists) usually improves the query efficiency. IN a subquery, the not in Clause executes an internal sorting and merging. IN either case, not in is the most inefficient (because it executes a full table traversal for the table IN the subquery ). to avoid the use of not in, we can rewrite it into an Outer join (Outer Joins) or not exists.
Example:

(Efficient) SELECT * from emp (basic table) where empno> 0 and exists (SELECT 'x' from dept where dept. DEPTNO = EMP. deptno and loc = 'melb ')
(Inefficient) SELECT * from emp (basic table) where empno> 0 and deptno in (select deptno from dept where loc = 'melb ')

(16) Identifying 'inefficient execution' SQL statements:
Although various graphical tools related to SQLseo/'target = '_ blank'> are emerging, writing your own SQL tools to solve the problem is always the best method:
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;

(17) using indexes to improve efficiency:
An index is a conceptual part of a table to improve data retrieval efficiency. ORACLE uses a complex self-balancing B-tree structure. data Query by index is usually faster than full table scan. when ORACLE finds the optimal path for executing the query and Update statements, ORACLEseo/'target = '_ blank'> optimizer uses the index. using indexes when joining multiple tables can also improve efficiency. another advantage of using an index is that it provides uniqueness verification for the primary key .. For those LONG or long raw data types, You Can index almost all columns. generally, using indexes in large tables is particularly effective. of course, you will also find that using indexes to scan small tables can also improve efficiency. although the index can improve the query efficiency, we must pay attention to its cost. the index requires space for storage and regular maintenance. The index itself is also modified whenever a record is increased or decreased in the table or the index column is modified. this means that the INSERT, DELETE, and UPDATE operations for each record will pay four or five more disk I/O. because indexes require additional storage space and processing, unnecessary indexes will slow the query response time .. Regular index reconstruction is necessary .:
ALTER INDEX REBUILD

(18) replace DISTINCT with EXISTS:
When you submit a query that contains one-to-many table information (such as the Department table and employee table), avoid using DISTINCT in the SELECT clause. in general, you can consider replacing it with EXIST, and EXISTS makes the query more rapid, because the RDBMS core module will return the result immediately after the subquery conditions are 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 );

(19) server/'target = '_ blank'> SQL statements are capitalized, because oracle always first parses server/'target = '_ blank'> SQL statements, convert lowercase letters into uppercase letters and then execute

(20) try to use the connector "+" to connect strings in java code!

(21) Avoid using NOT in index columns,
We should avoid using NOT in the index column, NOT will have the same impact as using the function in the index column. when ORACLE Encounters "NOT", it stops using indexes and performs full table scanning.

(22) Avoid using computation on index columns.
In the WHERE clause, if the index column is part of the function, seo/'target = '_ blank'> the optimizer uses full table scanning instead of using the index.
Example:
Inefficiency:
SELECT... From dept where sal * 12> 25000;
Efficient:
SELECT... From dept where sal> 25000/12;

(23) Replace with> =>
Efficient:
SELECT * from emp where deptno> = 4
Inefficiency:
SELECT * from emp where deptno> 3
The difference between the two lies in that the former DBMS will jump directly to the first record whose DEPT is equal to 4, while the latter will first locate the record whose DEPTNO is = 3 and scan forward to the record whose first DEPT is greater than 3.
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(24) replace OR with UNION (applicable to index columns)
In general, replacing OR in the WHERE clause with UNION will produce better results. using OR for index columns will scan the entire table. note that the preceding rules are only valid for multiple index columns. if a column is not indexed, the query efficiency may be reduced because you did not select OR. in the following example, both LOC_ID and REGION have indexes.
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"
Inefficiency:
SELECT LOC_ID, LOC_DESC, REGION
FROM LOCATION
WHERE LOC_ID = 10 or region = "MELBOURNE"
If you insist on using OR, you need to write the index columns with the least records at the beginning.

(25) use IN to replace OR
This is a simple and easy-to-remember rule, but the actual execution results must be tested. in ORACLE8i, the execution paths of the two seem to be the same.
Inefficiency:
SELECT .... From location where LOC_ID = 10 OR LOC_ID = 20 OR LOC_ID = 30
Efficient
SELECT... From location where LOC_IN IN (10, 20, 30 );

(26) Avoid using is null and is not null in the index column.
To avoid using any columns that can be empty in the index, ORACLE will not be able to use this index. this record does not exist in the index if the column contains a null value. for a composite index, if each column is empty, this record does not exist in the index. if at least one column is not empty, the record is stored in the index. for example, if the unique index is created in column A and column B of the table, and the and B values of A record exist in the table are (123, null ), ORACLE will not accept the next record with the same A, B value (123, null) (insert ). however, if all index columns are empty, ORACLE considers the entire key value to be null, but null is not equal to null. therefore, you can insert 1000 records with the same key value. Of course, they are empty! Because the null value does not exist in the index column, the Null Value Comparison of the index column in The WHERE clause will disable ORACLE.
Inefficiency: (index failure)
SELECT... From department where DEPT_CODE is not null;
Efficient: (index valid)
SELECT... From department where DEPT_CODE> = 0;

(27) always use the first column of the index:
If the index is created on multiple columns, only when its first column (leading column) is referenced by the where clause, seo/'target = '_ blank'> the optimizer selects to use this index. this is also a simple and important rule. When only the second column of the index is referenced, the seo/'target = '_ blank'> optimizer uses a full table scan and ignores the index.

(28) replace UNION with UNION-ALL (if possible ):
When an SQL statement needs to UNION two query result sets, these two result sets are merged in the form of UNION-ALL and sorted before the final result is output. if union all is used to replace UNION, sorting is unnecessary. the efficiency will be improved accordingly. note that union all will repeatedly output the same records in the two result sets. therefore, you still need to analyze the feasibility of using union all from the business needs. UNION sorts the result set. This operation uses SORT_AREA_SIZE memory. seo/'target = '_ blank'> Optimization for this memory is also very important. the following SQL can be used to query the consumption of sorting
Inefficiency:
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) replace order by with WHERE:
The order by clause only uses indexes under two strict conditions.
All columns in order by must be included in the same index and maintained in the ORDER of the index.
All columns in order by must be defined as non-empty.
The index used BY the WHERE clause and the index used in the order by clause cannot be tied together.
For example:
The DEPT table contains the following columns:
DEPT_CODE PK NOT NULL
DEPT_DESC NOT NULL
DEPT_TYPE NULL
Inefficiency: (indexes are not used)
SELECT DEPT_CODE from dept order by DEPT_TYPE
Efficiency: (using indexes)
SELECT DEPT_CODE from dept where DEPT_TYPE> 0

(30) Avoid changing the index column type .:
ORACLE automatically converts columns to different types of data.
Assume that EMPNO is a numeric index column.
SELECT... From emp where empno = '20140901'
In fact, after ORACLE type conversion, the statement is converted:
SELECT... From emp where empno = TO_NUMBER ('123 ')
Fortunately, the type conversion does not occur on the index column, and the purpose of the index is not changed.
Assume that EMP_TYPE is a character-type index column.
SELECT... From emp where EMP_TYPE = 123
This statement is converted:
SELECT... From emp WHERETO_NUMBER (EMP_TYPE) = 123
This index will not be used because of internal type conversion! To avoid implicit type conversion for your SQL statements, it is best to explicitly convert the type conversion. Note that when comparing the character and value, ORACLE will first convert the value type to the character type.

(31) WHERE clause to be careful:
The WHERE clause in some SELECT statements does not use indexes. Here are some examples.
In the example below, (1 )'! = 'No index is used. remember, indexes only tell you what exists in the table, but not what does not exist in the table. (2) '|' is a character concatenation function. as with other functions, indexes are disabled. (3) '+' is a mathematical function. as with other mathematical functions, indexes are disabled. (4) The same index Columns cannot be compared with each other, which enables full table scan.

(32) a. If the retrieved data volume exceeds 30% of the number of records in the table, using indexes will not significantly improve the efficiency.
B. in certain cases, using indexes may be slower than full table scanning, but this is an order of magnitude difference. in general, using an index is several times or even several thousand times more than a full table scan!

(33) Avoid resource-consuming operations:
SQL statements with DISTINCT, UNION, MINUS, INTERSECT, and order by will start the SQL engine.
Execute the resource-consuming sorting (SORT) function. DISTINCT requires a sorting operation, while other operations require at least two sorting operations. generally, SQL statements with UNION, MINUS, and INTERSECT can be rewritten in other ways. if your get = '_ blank'> database SORT_AREA_SIZE is well configured, you can also consider using UNION, MINUS, and INTERSECT. After all, they are highly readable.

(34) seo/'target = '_ blank'> optimize group:
To improve the efficiency of the group by statement, you can filter out unnecessary records before group by. The following two queries return the same results, but the second query is much faster.
Inefficiency:
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