Suppose we have a table similar to this:
CREATE TABLE test1 (
id integer,
content varchar
);and the application issues many queries of the form:
SELECT content FROM test1 WHERE id = constant;With no advance preparation, the system would have to scan the entiretest1table, row by row, to find all matching entries. If there are many rows intest1and only a few rows (perhaps zero or one) that would be returned by such a query, this is clearly an inefficient method. But if the system has been instructed to maintain an index on theidcolumn, it can use a more efficient method for locating matching rows. For instance, it might only have to walk a few levels deep into a search tree.
A similar approach is used in most non-fiction books: terms and concepts that are frequently looked up by readers are collected in an alphabetic index at the end of the book. The interested reader can scan the index relatively quickly and flip to the appropriate page(s), rather than having to read the entire book to find the material of interest. Just as it is the task of the author to anticipate the items that readers are likely to look up, it is the task of the database programmer to foresee which indexes will be useful.
The following command can be used to create an index on the id column, as discussed:
CREATE INDEX test1_id_index ON test1 (id);The name test1_id_index can be chosen freely, but you should pick something that enables you to remember later what the index was for.
To remove an index, use the DROP INDEX command. Indexes can be added to and removed from tables at any time.
Once an index is created, no further intervention is required: the system will update the index when the table is modified, and it will use the index in queries when it thinks doing so would be more efficient than a sequential table scan. But you might have to run the ANALYZE command regularly to update statistics to allow the query planner to make educated decisions.
After an index is created, the system has to keep it synchronized with the table. This adds overhead to data manipulation operations. Therefore indexes that are seldom or never used in queries should be removed.