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Physically reorders a heap storage table on disk according to an index. Not a recommended operation in Greenplum Database.
CLUSTER indexname ON tablename CLUSTER tablename CLUSTER
CLUSTER orders a heap storage table based on an index. CLUSTER is not supported on append-optmized storage tables. Clustering an index means that the records are physically ordered on disk according to the index information. If the records you need are distributed randomly on disk, then the database has to seek across the disk to get the records requested. If those records are stored more closely together, then the fetching from disk is more sequential. A good example for a clustered index is on a date column where the data is ordered sequentially by date. A query against a specific date range will result in an ordered fetch from the disk, which leverages faster sequential access.
Clustering is a one-time operation: when the table is subsequently updated, the changes are not clustered. That is, no attempt is made to store new or updated rows according to their index order. If one wishes, one can periodically recluster by issuing the command again.
When a table is clustered using this command, Greenplum Database remembers on which index it was clustered. The form CLUSTER tablename reclusters the table on the same index that it was clustered before. CLUSTER without any parameter reclusters all previously clustered tables in the current database that the calling user owns, or all tables if called by a superuser. This form of CLUSTER cannot be executed inside a transaction block.
When a table is being clustered, an ACCESS EXCLUSIVE lock is acquired on it. This prevents any other database operations (both reads and writes) from operating on the table until the CLUSTER is finished.
- The name of an index.
- The name (optionally schema-qualified) of a table.
In cases where you are accessing single rows randomly within a table, the actual order of the data in the table is unimportant. However, if you tend to access some data more than others, and there is an index that groups them together, you will benefit from using CLUSTER. If you are requesting a range of indexed values from a table, or a single indexed value that has multiple rows that match, CLUSTER will help because once the index identifies the table page for the first row that matches, all other rows that match are probably already on the same table page, and so you save disk accesses and speed up the query.
During the cluster operation, a temporary copy of the table is created that contains the table data in the index order. Temporary copies of each index on the table are created as well. Therefore, you need free space on disk at least equal to the sum of the table size and the index sizes.
Because the query optimizer records statistics about the ordering of tables, it is advisable to run ANALYZE on the newly clustered table. Otherwise, the planner may make poor choices of query plans.
There is another way to cluster data. The CLUSTER command reorders the original table by scanning it using the index you specify. This can be slow on large tables because the rows are fetched from the table in index order, and if the table is disordered, the entries are on random pages, so there is one disk page retrieved for every row moved. (Greenplum Database has a cache, but the majority of a big table will not fit in the cache.) The other way to cluster a table is to use a statement such as:
CREATE TABLE newtable AS SELECT * FROM table ORDER BY column;
This uses the Greenplum Database sorting code to produce the desired order, which is usually much faster than an index scan for disordered data. Then you drop the old table, use ALTER TABLE ... RENAME to rename newtable to the old name, and recreate the table's indexes. The big disadvantage of this approach is that it does not preserve OIDs, constraints, granted privileges, and other ancillary properties of the table — all such items must be manually recreated. Another disadvantage is that this way requires a sort temporary file about the same size as the table itself, so peak disk usage is about three times the table size instead of twice the table size.
Cluster the table employees on the basis of its index emp_ind:
CLUSTER emp_ind ON emp;
Cluster a large table by recreating it and loading it in the correct index order:
CREATE TABLE newtable AS SELECT * FROM table ORDER BY column; DROP table; ALTER TABLE newtable RENAME TO table; CREATE INDEX column_ix ON table (column); VACUUM ANALYZE table;
There is no CLUSTER statement in the SQL standard.