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If the data value objects are small, but great in number, the per-entry overhead can add up to a significant memory requirement. This overhead can be reduced by grouping multiple data values into a single entry or by using containment relationships. For instance, you may choose to have your Order objects contain their line items instead of having a separate OrderLineItems region. If this option is available, it is worth considering as it may yield performance improvements in addition to space savings.

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Partitioned Region Scalability

Geode partitioned regions scale out by rebalancing their data buckets (partitions) in order to distribute the data evenly across all available nodes in a cluster. When new nodes are added to the cluster, rebalancing causes some buckets to move from the old to the new nodes such that the data is evenly balanced across all the nodes. For this to work well, so that the end result is a well balanced cluster, for each partitioned region there should be at least one order of magnitude more buckets than data nodes. In general, the more buckets the better the data distribution. However, since the number of buckets cannot be changed dynamically, without downtime, it has to be chosen with the projected horizontal scale-out taken into account. Otherwise, over time as the system scales out, the data may become less evenly distributed. In the extreme case, when the number of nodes exceeds the number of buckets, adding new nodes has no effect; the ability to scale out is lost.

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