11.1. introduction

suppose we have a table similar to this:

create table test1 (     id integer,     content varchar );

and the application requires a lot of queries of the form

select content from test1 where id = constant;

with no advance preparation, the system would have to scan the entire test1 table, row by row, to find all matching entries. if there are a lot of rows in test1 and only a few rows (perhaps only zero or one) that would be returned by such a query, then this is clearly an inefficient method. but if the system has been instructed to maintain an index on the id column, then 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 books of non-fiction: 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 the readers are likely to look up, it is the task of the database programmer to foresee which indexes will be of advantage.

the following command would be used to create the 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 this would be more efficient than a sequential table scan. but you may have to run the analyze command regularly to update statistics to allow the query planner to make educated decisions. see chapter 13 for information about how to find out whether an index is used and when and why the planner may choose not to use an index.

indexes can also benefit update and delete commands with search conditions. indexes can moreover be used in join searches. thus, an index defined on a column that is part of a join condition can significantly speed up queries with joins.

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.