Compared to java.io.Serializable, this can cut serialized data size by a factor of two or more (especially helpful with Distributed caches, as they generally cache data in serialized form). Java.io.Externalizable – This requires developers to implement serialization manually, but can provide significant performance benefits. Java.io.Serializable – The simplest, but slowest option.
#Oracle coherence portable#
See Chapter 20, "Using Portable Object Format." POF was designed to be incredibly efficient in both space and time and is the recommended serialization option in Coherence. See Part III, "Using Caches" for detailed information on configuring and using caches.īecause serialization is often the most expensive part of clustered data management, Coherence provides the following options for serializing/deserializing data:Ĭom.tangosol.io.pof.PofSerializer – The Portable Object Format (also referred to as POF) is a language agnostic binary format. This is useful for both dedicated cache servers and co-located caching (cache partitions stored within the application server JVMs). Tiered caching (using the Near Cache functionality) enables you to couple local caches on the application server with larger, partitioned caches on the cache servers, combining the raw performance of local caching with the scalability of partitioned caching. This is accomplished by using the Partitioned cache implementation and simply disabling local storage on client nodes through a single command-line option or a one-line entry in the XML configuration. This can be helpful when you want to partition workloads (to avoid stressing the application servers). Out-of-process (client/server) caching provides the option of using dedicated cache servers.
This benefit is most directly realized by the Local, Replicated, Optimistic and Near Cache implementations. In-process caching provides the highest level of raw performance, since objects are managed within the local JVM. Several different near-cache strategies are available and offer a trade-off between performance and synchronization guarantees. Near Cache-Provides the performance of local caching with the scalability of distributed caching. The distribution algorithm minimizes network traffic and avoids service pauses by incrementally shifting data.
Data is automatically, dynamically and transparently partitioned across nodes. Replicated Cache-Perfect for small, read-heavy caches.ĭistributed Cache-True linear scalability for both read and write access. Local Cache-Local on-heap caching for non-clustered caching. Coherence provides several cache implementations:
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