BigMemory Go 4.3.1 | About BigMemory Go | Automatic Resource Control
 
Automatic Resource Control
Automatic Resource Control (ARC) gives you fine-grained controls for tuning performance and enabling trade-offs between throughput, latency and data access. Independently adjustable configuration parameters include differentiated tier-based sizing and pinning hot or eternal data in the most effective tier.
ARC offers a wealth of benefits, including:
*Sizing limitations on in-memory caches to avoid OutOfMemory errors
*Pooled sizing – no requirement to size caches individually
*Differentiated tier-based sizing for flexibility
*Sizing by bytes, entries, or percentages for more flexibility
Dynamically Sizing Stores
Tuning often involves sizing stores appropriately. There are a number of ways to size the different BigMemory Go storage tiers using simple configuration sizing attributes. For information about how to tune tier sizing by configuring dynamic allocation of memory and automatic balancing, see "Sizing Storage Tiers" in the Configuration Guide for BigMemory Go.
Pinning Data
One of the most important aspects of running an in-memory data store involves managing the life of the data in each tier. For more information about managing life of data in a tier using pinning, expiration, and eviction, see "Managing Data Life" in the Configuration Guide for BigMemory Go.

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