Example 1: Ongoing migration with adjusted ranges
You can create jobs to migrate data changes on an ongoing basis.
In this separate database, the tables and columns are identical to those in the production database, but additional indexes exist to support different usage. The tables in the separate database are referred to as shadow tables.
For this example, assume that you are a DBA for a nation-wide travel agency. The president of the agency wants to monitor data concerning the number of customers receiving frequent-flyer discounts. He wants to search for data by a different index, and he wants to check the data on a daily basis.
You decide to set up a decision-support database to track and report on customers receiving frequent-flyer discounts. You create a set of shadow tables and populate them with data from the production database. The production database and the decision-support database have the same primary index with differing secondary indexes. You define a log mark at a quiesce of the table spaces involved.
The following figure shows the overall process of migrating the data with an ongoing job:
You can run the ongoing job repeatedly, without changing the syntax. Notice how Log Master tracks the open transactions at the end of a run, and adjusts the scan range to include those transactions in the next run. Log Master does not reprocess any transactions that were completed during a previous run, even though it might scan part of the same log range again.
Following table provides a high-level task list for this example.
Task | References |
---|---|
Create the decision-support database. | |
Define a filter that selects specific table space transactions. | |
Define a time frame that starts from the same point of consistency used by BMC AMI Recover, and ends at the current time. |
|
Define the time frame as an Ongoing Process. | |
Modify the output options for the default Summary report and SQL file (as needed). | |
Save your selections in a work ID. | |
Generate JCL and save it for batch submittal. |
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