One of the features in PostgreSQL designed to enhance index performance is the use of a clustered index. For people coming from MS SQL Server shops, this may look familiar to you and actually serves the same purpose, but is implemented differently and this implementation distinction is very important to understand and be aware of. In PostgreSQL 8.3 the preferred syntax of how you cluster has changed. For details check out 8.3 CLUSTER 8.2 CLUSTER 8.0 CLUSTER. A lot of what I'm going to say is somewhat of a regurgitation of the docs, but in slightly different words.
First in short - clustering on an index forces the physical ordering of the data to be the same as the index order of the index chosen. Since you can have only one physical order of a table, you can have only one clustered index per table and should carefully pick which index you will use to cluster on or if you even want to cluster. Unlike Microsoft SQL Server, clustering on an index in PostgreSQL does not maintain that order. You have to reapply the CLUSTER process to maintain the order. Clustering helps by reducing page seeks. Once an index search is done and found, pulling out the data on the same page is vastly faster since once you find the start point all successive data nearby is easy picking.
As a corrollary to the above, it doesn't help too much for non-range queries. E.g. if you have dummy ids for records and you are just doing single record select queries, clustering is fairly useless to you. It is only really useful if you are doing range queries like between date ranges or spatial ranges or queries where the neighboring data to an index match is likely to be pulled. For example if you have an order items table, then clustering on a compound index such as order_id,order_item_id may prove useful since neighboring data is something you likely want to pull for range and summations.
Now lets see how we create a clustered index and then talk about the pros and gotchas
--First we create the index CREATE INDEX member_name_idx ON member USING btree (upper(last_name), upper(first_name)); ALTER TABLE member CLUSTER ON member_name_idx;
Once a clustered index is created to force a recluster, you simply do this
To force a cluster on all tables that have clustered indexes, you do this
Again those coming from Microsoft SQL Server will recognize FILLFACTOR syntax. IBM Informix also has a FILLFACTOR syntax that serves the same purpose as the SQL Server and PostgreSQL ones. For more details here PostgreSQL docs: Create Index. FillFactor basically creates page gaps in an index page. So a Fill Factor of 80 means leave 20% of an index page empty for updates and inserts to the index so minimal reshuffering of existing data needs to happen as new records are added or indexed fields are updated in the system. This is incorporated into the index creation statement.
CREATE INDEX member_name_idx ON member USING btree (upper(last_name), upper(first_name)) WITH (FILLFACTOR=80); ALTER TABLE member CLUSTER ON member_name_idx; -- note we do this to update the planner statistics information. Its important since this information helps the planner at selecting indexes and scan approach. ANALYZE member;
After an index is created on a table, this information is then used in several scenarios
First for fairly static tables such as large lookup tables, that rarely change or when they change are bulk changes, there is little point in leaving blank space in pages. It takes up disk space and causes Postgres to scan thru useless air. In these cases - you basically want to set your FillFactor high to like 99.
Then there are issues of how data is inserted, if you have only one index and new data usually resides at the end of the index and the indexed field are rarely updated, again having a low fill factor is probably not terribly useful even if the data is updated often. You'll never be using that free space so why have it.
For fairly updated data that changes such that you are randomly adding 10% new data per week or so in middle of page, then a fill factor of say 90 is the general rule of thumb.
The approach PostgreSQL has taken to cluster means that unlike the SQL Server approach, there is no additional penalty during transactions of having a clustered index. It is simply used to physically order the data and all new data goes to the end of the table. In the SQL Server approach all non-clustered indexes are keyed by the clustered index, which means any change to a clustered field requires rebuilding of the index records for the other indexes and also any insert or update may require some amount of physical shuffling. There are also other consequences with how the planner uses this information that are too detailed to get into.
The bad is that since there is no additional overhead aside from the usual index key creation during table inserts and updates, you need to schedule reclustering to maintain your fine order and the clustering causes a table lock. The annoying locking hopefully will be improved in later versions. Scheduling a cluster can be done with a Cron Job or the more OS agnostic PgAgent approach. In another issue, we'll cover how to use PgAgent for backup and other scheduling maintenance tasks such as this.