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  • Non-distributed processing - The KPI calculations are performed in the KPI agent. This type of processing requires little initial configuration and is suitable when you want to process all of the data on a single EC/ECSA, or when manual sharding is an acceptable method of scaling. For further information about non-distributed processing, see 3. KPI Management - Non-Distributed Processing.
  • Distributed processing  - The KPI calculations are performed in a Spark cluster that is managed via a  service a Image Added service running on one or more SCs. You can scale the solution, without the need for manual “sharding” of the data, by adding Execution Container hosts and SCs. The KPI Cluster In and KPI Cluster Out agents are used to transfer data between Spark and the  workflows the Image Added workflows via Kafka/Zookeeper. For further information about distributed processing, see 4. KPI Management - Distributed Processing.

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