IBM Tivoli Netcool/OMNIbus Version 8.1

Creating indexes

Use Netcool/OMNIbus Administrator to create indexes on columns of database tables.

About this task

Tivoli Netcool/OMNIbus supports hash and tree index structures. The hash index supports equality comparisons in SQL queries. The tree index is an ordered index that stores column values in a sorted structure, and allows a wider range of comparisons, including equality, in SQL queries. Consequently, a tree index can be used in range queries and in queries with an ORDER BY clause.

Index names must begin with an alphabetic character in uppercase or lowercase. The name of the index must be unique within the ObjectServer. Use a naming convention for indexes for ease of identification and uniqueness.
Restriction: You cannot create indexes on the columns in system tables. These tables contain metadata about ObjectServer objects and are stored in the catalog database. Also, you cannot create a hash index on a single primary key field. You cannot create a tree index on columns with Boolean data values.

Procedure

To create column indexes:

  1. From the Netcool/OMNIbus Administrator window, select the System menu button.
  2. Click Databases. The Databases, Tables and Columns pane opens.
  3. Select the table containing the column that you want to index and then click the Data View tab. All currently indexed columns are denoted by an icon.
  4. To index the column, right-click the column and click Indexes > Add Column Index. A window is displayed showing the selectivity rating of the column index.
  5. To create the index, click Yes.
  6. Type a name for the index, specify the type of index, a hash index or a tree index, and click OK. The index is created. On the Data View tab, the newly indexed column is denoted by the index icon.

Results

You can verify that the table is indexed by checking the catalog.indexes table, either from the Netcool/OMNIbus Administrator interface, or by using the SELECT command. SQL queries against the indexed column should now execute faster and result in faster data retrieval.


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