How can you create a filtered index?

A filtered index is an index that doesn’t have all the records of the columns stored in it. Sometimes it’s also called partial index. The Oracle database implements partial indexes only for partitioned tables where you can choose which partitions will have indexes and which ones will not. Filtered index in the Oracle database is possible with a workaround by using a case statement with a Function-Based Index (FBI). The case condition set the desired values to null so the FBI won’t index the null values. For example: CREATE INDEX idx_msg_unread ON user_messages (CASE WHEN msg_unread = 1 THEN NULL ELSE msg_unread END);

That’s a comprehensive definition of a filter predicate. Essentially, it’s a condition used to determine which rows are included or excluded from an index based on specific criteria within a single table. It’s an efficient way to optimize index usage by narrowing down the data to only what’s needed for certain queries.

- In Oracle databases, a filter predicate refers to a condition applied during query execution. - It affects performance, especially when using indexes. For example, if a condition shows up as a filter predicate, it scans the entire index range and applies the filter on each row

CREATE INDEX index_name ON table_name (column_name) WHERE filter_condition; For example, if you have a table called "students" and you want to create a filtered index on the column "age" where the age is greater than 18, you can use the following SQL query: CREATE INDEX idx_students_age ON students (age) WHERE age > 18;

Filtered index in the Oracle database is possible with a workaround by using a case statement with a Function-Based Index (FBI). The case condition set the desired values to null so the FBI won’t index the null values. For example: CREATE INDEX idx_msg_unread ON user_messages (CASE WHEN msg_unread = 1 THEN NULL ELSE msg_unread END);

Here's how to create a filtered index, using SQL Server as an example, but note that the concept can be adapted to other database systems that support similar functionality. SQL Server Example To create a filtered index in SQL Server, you use the CREATE INDEX statement along with a WHERE clause that specifies the filter predicate. The predicate defines the subset of rows included in the index. CREATE NONCLUSTERED INDEX [Index_Name] ON [Schema].[Table](Column1, Column2,...) WHERE [Filter_Condition];

Using Transact-SQL (T-SQL): CREATE INDEX index_name ON table_name (column_list) WHERE filter_predicate; Replace index_name with your desired index name. Specify the target table_name. List the relevant columns in column_list.

In SQL Server it's simple as below to have a filtered index: CREATE NONCLUSTERED INDEX NCI_Table_Column ON Table(Column) WHERE Column IS NOT NULL /*OR other experssions*/;

Consider you have a table called orders with attributes like order_id, order_date, and status. Now, Let us say that you frequently query for orders with a specific status, say "complete", and this query constitutes a significant part of the workload. Although, a database may create a regular index on the status column. However, here we want to create a filtered index. Since we want only “complete” orders we will take the subset of the orders table like below: CREATE INDEX indx_completed_orders On Orders (order_id) Where status = 'complete' Now, when you run the below query the performance of it would be much faster than usual and it would have more efficient resource utilization. Select * From Orders where status = 'complete'

By creating a filtered index that doesn't include the NULLs, you can have a smaller index that is easier to manage compared to a regular index. CREATE NONCLUSTERED INDEX IX_Code ON Students(Code) WHERE Code IS NOT NULL; Filtered indexes are commonly used to exclude NULL values from a UNIQUE index. This allows for the same behavior as default UNIQUE indexes in other database engines where only non-NULL values are enforced for uniqueness. CREATE UNIQUE NONCLUSTERED INDEX IX_Code ON Students(Code) WHERE Code IS NOT NULL;

It helps with performance when you have very rare values in status columns and you want to query only those rare values. That way the optimizer can use that index when the histograms are not enough to map very rare values. This helps searching rare values using the index instead of performing a full scan operation. That helps reducing resource usage by the database like CPU, memory and I/O.

1. Improved Query Performanc 2. Reduced Storage requirements 3. Optimized Maintenance 4. Selective Indexind 5. Query Plan Optimization 6. Reduce Lock Contention 7. Better performance for specialized workloads

Filtered index are useful to index those type of columns which contains our scenario. like excluding null values which help us have smaller index and more performance over other values

Let us assume some arbitrary numbers to illustrate a potential performance improvement percentage in filtered index: 1. Let us assume filtered index narrows down the rows to 10% of the total. So, instead of a table scan now we do subset scan. 2. Assume, filtered index reduces memory and storage utilization by 20%, leading to potential savings in resource allocation. 3. Assuming 50% of the queries in the workload access the subset of data covered by this filtered index. Considering the factors above, we might estimate a potential performance improvement of around 30-40% on average. Note: These numbers are purely hypothetical and simplified for illustrative purposes. Actual performance can vary depending on various factors.

Filtered indexes rely on accurate statistics to make the right decisions. If the statistics are outdated or missing, your filtered index might not be as effective as it should be. So, always keep an eye on those statistics and make sure they're up-to-date for your filtered index to perform at its best.

Although Filtered Indexes are good but consider to not rush on using it. Not all scenarios need filtered indexes. In some cases, the bad index was the bottleneck of the project.