This section helps you decide when to use hash clusters by contrasting situations where hashing is most useful against situations where there is no advantage. If you find your decision is to use indexing rather than hashing, then you should consider whether to store a table individually or as part of a cluster.
Note:Even if you decide to use hashing, a table can still have separate indexes on any columns, including the cluster key.
Hashing is useful when you have the following conditions:
Most queries are equality queries on the cluster key:
SELECT ... WHERE cluster_key = ...;
In such cases, the cluster key in the equality condition is hashed, and the corresponding hash key is usually found with a single read. In comparison, for an indexed table the key value must first be found in the index (usually several reads), and then the row is read from the table (another read).
The tables in the hash cluster are primarily static in size so that you can determine the number of rows and amount of space required for the tables in the cluster. If tables in a hash cluster require more space than the initial allocation for the cluster, performance degradation can be substantial because overflow blocks are required.
Hashing is not advantageous in the following situations:
Most queries on the table retrieve rows over a range of cluster key values. For example, in full table scans or queries such as the following, a hash function cannot be used to determine the location of specific hash keys. Instead, the equivalent of a full table scan must be done to fetch the rows for the query.
SELECT . . . WHERE cluster_key < . . . ;
With an index, key values are ordered in the index, so cluster key values that satisfy the
WHERE clause of a query can be found with relatively few I/Os.
The table is not static, but instead is continually growing. If a table grows without limit, the space required over the life of the table (its cluster) cannot be predetermined.
Applications frequently perform full-table scans on the table and the table is sparsely populated. A full-table scan in this situation takes longer under hashing.
You cannot afford to preallocate the space that the hash cluster will eventually need.