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  • #16
    thanks ikarzali.

    One other metric that would be interesting is your object graph shape / read/write ratio. Meaning do you have 10K, 100K, or 10MB objects? And do those objects change? At what rate (50% write, 25% write, etc.)?
    I'm not too worried about the writes on this application - they're all File IO writes, and on zOS those go pretty fast. It's the reading of the database and cache priming I'd like to know more about.

    I suspect that each unique initial request will fetch data form the DB, and TC will then store it in it's cache. Subsequent requests for the same data will be pulled from cache. Is this correct? Does TC handle the caching transparently based on service requests?

    I think the objects will all be less than 1k each - it's really just an address with two or three more attributes. That's the extent of the transfer objects. On response there's a bit more data, but still less than 2k each.



    • #17
      Any update on Spring Batch with GridGain.
      Please share more on this.



      • #18
        GridGain is an adequate platform for implementing the PartitionHandler SPI (see user guide for more details). The nice thing about it is the network classloading (so no need to deploy jar files in remote workers).


        • #19
          GigaSpaces Spring Batch PU

          You may find a running example here:

          The GiagSpaces Spring Batch PU provides:
          Enhanced performance:
          - Distributed parallel processing.
          - Distributed Task execution partitioning.
          - In-memory distributed state management.

          Management and Monitoring:
          - Task execution queuing.
          - Distributed Deployment environment.
          - Continuous High-Availability.

          - Elastic and Dynamic scalability of the Spring batch PU instances.

          Shay Hassidim