When Oracle database executes a query, it usually matches the query conditions and indexes to speed up the query and improve efficiency. However, in some cases, using an index is not always a better choice, and it may be more efficient to not use the index. This article will explore the circumstances under which indexes can be omitted in Oracle databases and how to optimize them.
1. The role and optimization of indexes
Before understanding the situation without indexing, let’s first understand the role of indexes. An index is a data structure that can quickly locate data. It is similar to a directory in a dictionary, allowing us to quickly find the data we need. In Oracle, we can use B-tree indexes to optimize query speed.
The operation of B-tree index is an ordered traversal process. By quickly locating the index node and then traversing down the leaf nodes to query the data, the query speed is greatly improved. When we execute the query statement, Oracle will match the query conditions and index to determine whether to use the B-tree index for optimization.
However, you need to pay attention to optimization when using the index to avoid index failure. For example, the index column is not in the query conditions, the string type uses fuzzy query statements such as LIKE '%xxx%', the table with a small amount of data or the index column value is relatively fixed, etc., may cause the index to fail, thereby reducing the query efficiency and even causing Full table scan.
2. Situations without indexing
The following introduces some situations where you can consider not using indexes to achieve better query results.
(1) Full table scan is faster
In some cases, performing a full table scan is faster than using an index, for example, the table has only a few dozen rows or the index column value is relatively fixed, etc. Special case. At this time, the query efficiency will be higher, and the index will only increase the query time. Therefore, you can consider scanning the entire table directly without using an index to achieve better query results.
(2) Expressions appearing in query conditions
If functions or operators are used in the query conditions, each record needs to be calculated. Using the index at this time will not improve query efficiency, but will slow down the query. For example, the following statement:
SELECT * FROM table_a WHERE ROUND(num) = 10;
If an index is created on the num column and brought into the ROUND function, the index cannot be used to optimize the query. . So in this case, not using an index can actually improve query efficiency.
(3) Modify table data with high concurrency
In the case of high concurrency, frequent modification operations will cause frequent index failures. Not using the index at this time will improve the efficiency of modification operations. For tables with large amounts of data, not using indexes often makes modification operations more optimized. However, if query operations are frequent, you still need to consider using indexes to improve query speed.
(4) Table data is updated too fast
If the table data is updated very quickly, such as data insertion, modification and deletion operations at high frequency, then the index refresh frequency at this time will be higher, resulting in lower index efficiency. At the same time, due to the high refresh frequency, it will also lead to an increase in IO operations and occupy more system resources. Not creating indexes or reducing indexes can reduce system resource usage.
(5) Grouping operation
We know that grouping operation requires reordering the data, so using indexes cannot optimize query efficiency. Instead of using indexes, query efficiency can be improved by reducing the process of repeatedly judging data. Therefore, for queries that require grouping operations, you can consider not using the index to improve efficiency.
3. Optimization Ideas
In actual development, if the above situation is found, you can consider not using indexes to improve query efficiency. However, when deciding not to use an index, optimization needs to be based on different specific circumstances. Several optimization methods are introduced below.
1. Improve the data structure
The long query time is usually related to the table structure of the data. If the structure of the data table is reasonable, using indexes can greatly optimize efficiency. On the contrary, if the table structure is not reasonable enough, even indexing will be very slow.
2. Data partitioning
Oracle partition table is a table that divides table data into multiple small blocks. It can widen a single table into multiple parts, and each part stores on different disks. We can place infrequently queried data in different areas to reduce the number of full table scans.
3. Use distributed database
When our database becomes larger and larger and the amount of data that needs to be processed gradually increases, distributed database will be a better choice. Not only can it improve database performance, but it can also provide better protection for data security. At the same time, data can be evenly distributed among multiple nodes, reducing the amount of data processed by each node, thereby improving overall data processing efficiency.
Finally, whether we use indexes or not, we need to consider them comprehensively based on the specific situation. On the premise of rationally planning the data structure and optimizing database performance, the index can be adjusted or not used for specific query situations to achieve optimal processing.
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