|Oracle® Database Administrator's Guide
10g Release 2 (10.2)
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Storing a table in a hash cluster is an optional way to improve the performance of data retrieval. A hash cluster provides an alternative to a non-clustered table with an index or an index cluster. With an indexed table or index cluster, Oracle Database locates the rows in a table using key values that the database stores in a separate index. To use hashing, you create a hash cluster and load tables into it. The database physically stores the rows of a table in a hash cluster and retrieves them according to the results of a hash function.
Oracle Database uses a hash function to generate a distribution of numeric values, called hash values, that are based on specific cluster key values. The key of a hash cluster, like the key of an index cluster, can be a single column or composite key (multiple column key). To find or store a row in a hash cluster, the database applies the hash function to the cluster key value of the row. The resulting hash value corresponds to a data block in the cluster, which the database then reads or writes on behalf of the issued statement.
To find or store a row in an indexed table or cluster, a minimum of two (there are usually more) I/Os must be performed:
One or more I/Os to find or store the key value in the index
Another I/O to read or write the row in the table or cluster
In contrast, the database uses a hash function to locate a row in a hash cluster; no I/O is required. As a result, a minimum of one I/O operation is necessary to read or write a row in a hash cluster.
See Also:Chapter 14, "Managing Space for Schema Objects" is recommended reading before attempting tasks described in this chapter.
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.
A hash cluster is created using a
CREATE CLUSTER statement, but you specify a
HASHKEYS clause. The following example contains a statement to create a cluster named
trial_cluster that stores the
trial table, clustered by the
trialno column (the cluster key); and another statement creating a table in the cluster.
CREATE CLUSTER trial_cluster (trialno NUMBER(5,0)) TABLESPACE users STORAGE (INITIAL 250K NEXT 50K MINEXTENTS 1 MAXEXTENTS 3 PCTINCREASE 0) HASH IS trialno HASHKEYS 150; CREATE TABLE trial ( trialno NUMBER(5,0) PRIMARY KEY, ...) CLUSTER trial_cluster (trialno);
As with index clusters, the key of a hash cluster can be a single column or a composite key (multiple column key). In this example, it is a single column.
HASHKEYS value, in this case 150, specifies and limits the number of unique hash values that can be generated by the hash function used by the cluster. The database rounds the number specified to the nearest prime number.
HASH IS clause is specified, the database uses an internal hash function. If the cluster key is already a unique identifier that is uniformly distributed over its range, you can bypass the internal hash function and specify the cluster key as the hash value, as is the case in the preceding example. You can also use the
HASH IS clause to specify a user-defined hash function.
You cannot create a cluster index on a hash cluster, and you need not create an index on a hash cluster key.
For additional information about creating tables in a cluster, guidelines for setting parameters of the
CREATE CLUSTER statement common to index and hash clusters, and the privileges required to create any cluster, see Chapter 18, "Managing Clusters". The following sections explain and provide guidelines for setting the parameters of the
CREATE CLUSTER statement specific to hash clusters:
In a sorted hash cluster, the rows corresponding to each value of the hash function are sorted on a specified set of columns in ascending order, which can improve response time during subsequent operations on the clustered data.
For example, a telecommunications company needs to store detailed call records for a fixed number of originating telephone numbers through a telecommunications switch. From each originating telephone number there can be an unlimited number of telephone calls.
Calls are stored as they are made and processed later in first-in, first-out order (FIFO) when bills are generated for each originating telephone number. Each call has a detailed call record that is identified by a timestamp. The data that is gathered is similar to the following:
|Originating Telephone Numbers||Call Records Identified by Timestamp|
|650-555-1212||t0, t1, t2, t3, t4, ...|
|650-555-1213||t0, t1, t2, t3, t4, ...|
|650-555-1214||t0, t1, t2, t3, t4, ...|
In the following SQL statements, the
telephone_number column is the hash key. The hash cluster is sorted on the
call_duration columns. The number of hash keys is based on 10-digit telephone numbers.
CREATE CLUSTER call_detail_cluster ( telephone_number NUMBER, call_timestamp NUMBER SORT, call_duration NUMBER SORT ) HASHKEYS 10000 HASH IS telephone_number SIZE 256; CREATE TABLE call_detail ( telephone_number NUMBER, call_timestamp NUMBER SORT, call_duration NUMBER SORT, other_info VARCHAR2(30) ) CLUSTER call_detail_cluster ( telephone_number, call_timestamp, call_duration );
Given the sort order of the data, the following query would return the call records for a specified hash key by oldest record first.
SELECT * WHERE telephone_number = 6505551212;
You can also create a single-table hash cluster, which provides fast access to rows in a table. However, this table must be the only table in the hash cluster. Essentially, there must be a one-to-one mapping between hash keys and data rows. The following statement creates a single-table hash cluster named
peanut with the cluster key
CREATE CLUSTER peanut (variety NUMBER) SIZE 512 SINGLE TABLE HASHKEYS 500;
The database rounds the
HASHKEYS value up to the nearest prime number, so this cluster has a maximum of 503 hash key values, each of size 512 bytes. The
SINGLE TABLE clause is valid only for hash clusters.
HASHKEYS must also be specified.
See Also:Oracle Database SQL Reference for the syntax of the
When creating a hash cluster, it is important to choose the cluster key correctly and set the
HASHKEYS parameters so that performance and space use are optimal. The following guidelines describe how to set these parameters.
Choosing the correct cluster key is dependent on the most common types of queries issued against the clustered tables. For example, consider the
emp table in a hash cluster. If queries often select rows by employee number, the
empno column should be the cluster key. If queries often select rows by department number, the
deptno column should be the cluster key. For hash clusters that contain a single table, the cluster key is typically the entire primary key of the contained table.
The key of a hash cluster, like that of an index cluster, can be a single column or a composite key (multiple column key). A hash cluster with a composite key must use the internal hash function of the database.
HASH IS parameter only if the cluster key is a single column of the
NUMBER datatype, and contains uniformly distributed integers. If these conditions apply, you can distribute rows in the cluster so that each unique cluster key value hashes, with no collisions (two cluster key values having the same hash value), to a unique hash value. If these conditions do not apply, omit this clause so that you use the internal hash function.
If the hash cluster is to contain only a single table and the hash key values of the rows in that table are unique (one row for each value),
SIZE can be set to the average row size in the cluster.
If the hash cluster is to contain multiple tables,
SIZE can be set to the average amount of space required to hold all rows associated with a representative hash value.
Further, once you have determined a (preliminary) value for
SIZE, consider the following. If the
SIZE value is small (more than four hash keys can be assigned for each data block) you can use this value for
SIZE in the
CREATE CLUSTER statement. However, if the value of
SIZE is large (four or fewer hash keys can be assigned for each data block), then you should also consider the expected frequency of collisions and whether performance of data retrieval or efficiency of space usage is more important to you.
If the hash cluster does not use the internal hash function (if you specified
HASH IS) and you expect few or no collisions, you can use your preliminary value of
SIZE. No collisions occur and space is used as efficiently as possible.
If you expect frequent collisions on inserts, the likelihood of overflow blocks being allocated to store rows is high. To reduce the possibility of overflow blocks and maximize performance when collisions are frequent, you should adjust
SIZE as shown in the following chart.
|Available Space for each Block / Calculated SIZE||Setting for SIZE|
Overestimating the value of
SIZE increases the amount of unused space in the cluster. If space efficiency is more important than the performance of data retrieval, disregard the adjustments shown in the preceding table and use the original value for
The following examples show how to correctly choose the cluster key and set the
HASHKEYS parameters. For all examples, assume that the data block size is 2K and that on average, 1950 bytes of each block is available data space (block size minus overhead).
You decide to load the
emp table into a hash cluster. Most queries retrieve employee records by their employee number. You estimate that the maximum number of rows in the
emp table at any given time is 10000 and that the average row size is 55 bytes.
In this case,
empno should be the cluster key. Because this column contains integers that are unique, the internal hash function can be bypassed.
SIZE can be set to the average row size, 55 bytes. Note that 34 hash keys are assigned for each data block.
HASHKEYS can be set to the number of rows in the table, 10000. The database rounds this value up to the next highest prime number: 10007.
CREATE CLUSTER emp_cluster (empno NUMBER) . . . SIZE 55 HASH IS empno HASHKEYS 10000;
Conditions similar to the previous example exist. In this case, however, rows are usually retrieved by department number. At most, there are 1000 departments with an average of 10 employees for each department. Department numbers increment by 10 (0, 10, 20, 30, . . . ).
In this case,
deptno should be the cluster key. Since this column contains integers that are uniformly distributed, the internal hash function can be bypassed. A preliminary value of
SIZE (the average amount of space required to hold all rows for each department) is 55 bytes * 10, or 550 bytes. Using this value for
SIZE, only three hash keys can be assigned for each data block. If you expect some collisions and want maximum performance of data retrieval, slightly alter your estimated
SIZE to prevent collisions from requiring overflow blocks. By adjusting
SIZE by 12%, to 620 bytes (refer to "Setting SIZE"), there is more space for rows from expected collisions.
HASHKEYS can be set to the number of unique department numbers, 1000. The database rounds this value up to the next highest prime number: 1009.
CREATE CLUSTER emp_cluster (deptno NUMBER) . . . SIZE 620 HASH IS deptno HASHKEYS 1000;
Oracle Database guarantees that the initial allocation of space is sufficient to store the hash table according to the settings
HASHKEYS. If settings for the storage parameters
MINEXTENTS do not account for the hash table size, incremental (additional) extents are allocated until at least
SIZE*HASHKEYS is reached. For example, assume that the data block size is 2K, the available data space for each block is approximately 1900 bytes (data block size minus overhead), and that the
HASH parameters are specified in the
CREATE CLUSTER statement as follows:
STORAGE (INITIAL 100K NEXT 150K MINEXTENTS 1 PCTINCREASE 0) SIZE 1500 HASHKEYS 100
In this example, only one hash key can be assigned for each data block. Therefore, the initial space required for the hash cluster is at least 100*2K or 200K. The settings for the storage parameters do not account for this requirement. Therefore, an initial extent of 100K and a second extent of 150K are allocated to the hash cluster.
Alternatively, assume the
HASH parameters are specified as follows:
SIZE 500 HASHKEYS 100
In this case, three hash keys are assigned to each data block. Therefore, the initial space required for the hash cluster is at least 34*2K or 68K. The initial settings for the storage parameters are sufficient for this requirement (an initial extent of 100K is allocated to the hash cluster).
ALTER CLUSTER emp_dept . . . ;
The implications for altering a hash cluster are identical to those for altering an index cluster, described in "Altering Clusters". However, the
HASH IS parameters cannot be specified in an
ALTER CLUSTER statement. To change these parameters, you must re-create the cluster, then copy the data from the original cluster.
DROP CLUSTER emp_dept;
A table in a hash cluster is dropped using the
DROP TABLE statement. The implications of dropping hash clusters and tables in hash clusters are the same as those for dropping index clusters.
See Also:"Dropping Clusters"
The following views display information about hash clusters:
||These views map table columns to cluster columns.|
||These views list hash functions for hash clusters.|
See Also:Oracle Database Reference for complete descriptions of these views