Unlock Real-Time Analytics with Oracle 12c In-Memory: Architecture & Best Practices
This article explains how Oracle 12c's In-Memory feature enables hybrid OLTP/OLAP workloads by storing columnar data in a dedicated memory area, covering its architecture, data loading, consistency mechanisms, query acceleration techniques, and integration with RAC for high‑availability deployments.
5. Integration with Real Application Clusters (RAC)
The in‑memory feature works with RAC when each instance has INMEMORY_SIZE set to a non‑zero value. Data can be distributed across nodes by: INMEMORY DISTRIBUTE BY ROWID RANGE – splits a table’s rows by ROWID ranges and loads each range on a different node. INMEMORY DISTRIBUTE BY PARTITION – places each partition (or sub‑partition) on a separate node, which is ideal for evenly‑distributed partitioned tables.
Redundancy of in‑memory data is only available on Exadata machines; on non‑Exadata RAC clusters the data is not duplicated to avoid excessive private‑network traffic.
When a node fails, RAC waits for a configurable timeout before redistributing the in‑memory data to the remaining nodes, preventing unnecessary network churn. Parallel query (AutoDOP) must be enabled so that each node executes the same SQL locally and only aggregates the final result sets, not the IMCUs, across the cluster.
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