Indexes are a data structure that contains pointers to the contents of a table arranged in a specific order, to help the database optimize queries. They are similar to the index of book, where the pages (rows of the table) are indexed by their page number.
Several types of indexes exist, and can be created on a table. When an index exists on the columns used in a query's WHERE clause, JOIN clause, or ORDER BY clause, it can substantially improve query performance.
Remarks[edit | edit source]
Indexes are a way of speeding up read queries by sorting the rows of a table according to a column.
The effect of an index is not noticeable for small databases like the example, but if there are a large number of rows, it can greatly improve performance. Instead of checking every row of the table, the server can do a binary search on the index.
The tradeoff for creating an index is write speed and database size. Storing the index takes space. Also, every time an INSERT is done or the column is updated, the index must be updated. This is not as expensive an operation as scanning the entire table on a SELECT query, but it is still something to keep in mind.
Creating an Index[edit | edit source]
CREATE INDEX ix_cars_employee_id ON Cars (EmployeeId);
This will create an index for the column EmployeeId in the table Cars. This index will improve the speed of queries asking the server to sort or select by values in EmployeeId, such as the following:
SELECT * FROM Cars WHERE EmployeeId = 1
The index can contain more than 1 column, as in the following;
CREATE INDEX ix_cars_e_c_o_ids ON Cars (EmployeeId, CarId, OwnerId);
In this case, the index would be useful for queries asking to sort or select by all included columns, if the set of conditions is ordered in the same way. That means that when retrieving the data, it can find the rows to retrieve using the index, instead of looking through the full table.
For example, the following case would utilize the second index;
SELECT * FROM Cars WHERE EmployeeId = 1 Order by CarId DESC
If the order differs, however, the index does not have the same advantages, as in the following;
SELECT * FROM Cars WHERE OwnerId = 17 Order by CarId DESC
The index is not as helpful because the database must retrieve the entire index, across all values of EmployeeId and CarID, in order to find which items have
OwnerId = 17.
(The index may still be used; it may be the case that the query optimizer finds that retrieving the index and filtering on the
OwnerId, then retrieving only the needed rows is faster than retrieving the full table, especially if the table is large.)
Clustered, Unique, and Sorted Indexes[edit | edit source]
Indexes can have several characteristics that can be set either at creation, or by altering existing indexes.
CREATE CLUSTERED INDEX ix_clust_employee_id ON Employees(EmployeeId, Email);
The above SQL statement creates a new clustered index on Employees. Clustered indexes are indexes that dictate the actual structure of the table; the table itself is sorted to match the structure of the index. That means there can be at most one clustered index on a table. If a clustered index already exists on the table, the above statement will fail. (Tables with no clustered indexes are also called heaps.)
CREATE UNIQUE INDEX uq_customers_email ON Customers(Email);
This will create an unique index for the column Email in the table Customers. This index, along with speeding up queries like a normal index, will also force every email address in that column to be unique. If a row is inserted or updated with a non-unique Email value, the insertion or update will, by default, fail.
CREATE UNIQUE INDEX ix_eid_desc ON Customers(EmployeeID);
This creates an index on Customers which also creates a table constraint that the EmployeeID must be unique. (This will fail if the column is not currently unique - in this case, if there are employees who share an ID.)
CREATE INDEX ix_eid_desc ON Customers(EmployeeID Desc);
This creates an index that is sorted in descending order. By default, indexes (in MSSQL server, at least) are ascending, but that can be changed.
Sorted Index[edit | edit source]
If you use an index that is sorted the way you would retrieve it, the
SELECT statement would not do additional sorting when in retrieval.
CREATE INDEX ix_scoreboard_score ON scoreboard (score DESC);
When you execute the query
SELECT * FROM scoreboard ORDER BY score DESC;
The database system would not do additional sorting, since it can do an index-lookup in that order.
Dropping an Index, or Disabling and Rebuilding it[edit | edit source]
DROP INDEX ix_cars_employee_id ON Cars;
We can use command
DROP to delete our index. In this example we will
DROP the index called ix_cars_employee_id on the table Cars.
This deletes the index entirely, and if the index is clustered, will remove any clustering. It cannot be rebuilt without recreating the index, which can be slow and computationally expensive. As an alternative, the index can be disabled:
ALTER INDEX ix_cars_employee_id ON Cars DISABLE;
This allows the table to retain the structure, along with the metadata about the index.
Critically, this retains the index statistics, so that it is possible to easily evaluate the change. If warranted, the index can then later be rebuilt, instead of being recreated completely;
ALTER INDEX ix_cars_employee_id ON Cars REBUILD;
Partial or Filtered Index[edit | edit source]
SQL Server and SQLite allow to create indexes that contain not only a subset of columns, but also a subset of rows.
Consider a constant growing amount of orders with
order_state_id equal to finished (2), and a stable amount of orders with
order_state_id equal to started (1).
If your business make use of queries like this:
SELECT id, comment FROM orders WHERE order_state_id = 1 AND product_id = @some_value;
Partial indexing allows you to limit the index, including only the unfinished orders:
CREATE INDEX Started_Orders ON orders(product_id) WHERE order_state_id = 1;
This index will be smaller than an unfiltered index, which saves space and reduces the cost of updating the index.
Inserting with a Unique Index[edit | edit source]
UPDATE Customers SET Email = "firstname.lastname@example.org" WHERE id = 1;
This will fail if an unique index is set on the Email column of Customers. However, alternate behavior can be defined for this case:
UPDATE Customers SET Email = "email@example.com" WHERE id = 1 ON DUPLICATE KEY;
Rebuild index[edit | edit source]
Over the course of time B-Tree indexes may become fragmented because of updating/deleting/inserting data. In SQLServer terminology we can have internal (index page which is half empty ) and external (logical page order doesn't correspond physical order). Rebuilding index is very similar to dropping and re-creating it.
We can re-build an index with
ALTER INDEX index_name REBUILD;
By default rebuilding index is offline operation which locks the table and prevents DML against it , but many RDBMS allow online rebuilding. Also, some DB vendors offer alternatives to index rebuilding such as
REORGANIZE (SQLServer) or
SAP ASE: Drop index[edit | edit source]
This command will drop index in the table. It works on
SAP ASE server.
DROP INDEX [table name].[index name]
DROP INDEX Cars.index_1
Unique Index that Allows NULLS[edit | edit source]
CREATE UNIQUE INDEX idx_license_id ON Person(DrivingLicenseID) WHERE DrivingLicenseID IS NOT NULL GO
This schema allows for a 0..1 relationship - people can have zero or one driving licenses and each license can only belong to one person
Clustered index[edit | edit source]
When using clustered index, the rows of the table are sorted by the column to which the clustered index is applied. Therefore, there can be only one clustered index on the table because you can't order the table by two different columns.
Generally, it is best to use clustered index when performing reads on big data tables. The donwside of clustered index is when writing to table and data need to be reorganized (resorted).
An example of creating a clustered index on a table Employees on column Employee_Surname:
CREATE CLUSTERED INDEX ix_employees_name ON Employees(Employee_Surname);
Non clustered index[edit | edit source]
Nonclustered indexes are stored separately from the table. Each index in this structure contains a pointer to the row in the table which it represents.
This pointers are called a row locators. The structure of the row locator depends on whether the data pages are stored in a heap or a clustered table. For a heap, a row locator is a pointer to the row. For a clustered table, the row locator is the clustered index key.
An example of creating a non clustered index on table Employees and column Employee_Surname:
CREATE NONCLUSTERED INDEX ix_employees_name ON Employees(Employee_Surname);
There can be multiple nonclustered indexes on the table. The read operations are generally slower with non clustered indexes than with clustered indexes as you have to go first to index and than to the table. There are no restrictions in write operations however.
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