Ensure that the target environment meets the following requirements:
- The Cassandra cluster is not set up as Active-Active across multiple data centers. The following procedure does not apply to Active-Active setups.
- The adaptive rule versions are in sync with the versions in the source environment.
- In the source environment, export the pyADMFactory data
set.This data set is a database table that contains all the adaptive model instances in your system. For more information, see Exporting data into a data set.
- Log on to the target environment and perform the remaining steps there.
- On the Services landing page, on the Adaptive Decision Manager tab, decommission all ADM nodes by selecting the appropriate action from the Action menu.
- Open the pyADMFactory data set, and then from the Actions menu, select Run.
- In the Run Data Set dialog box, from the Operation list, select Truncate.
- If the target system has any models that report data in the following tables,
prevent inaccurate reports by manually truncating the following tables:
- Connect to a Cassandra database on a Decision Data Store node.For more information, see Connecting to an external Cassandra database through the Decision Data Store service.
- Remove any ADM (response) data that may cause a conflict with the source data
by using the following CQL commands:
- drop keyspace adm_commitlog
- drop keyspace null_adm (if present)
- drop keyspace adm (if present)
- Import the pyADMFactory data set from the source
environment.For more information, see Importing data into a data set.
- Recommission all ADM nodes.The first node that you recommission creates scoring models from the imported factory data. For more information, see Connecting to an external Cassandra database through the Decision Data Store service.