Compression Caching Low-Level Communication Optimizations
12.8 Low-Level Communication Optimizations
There are number of optimizations you can make to the low-level communication infrastructure. These optimizations can be difficult to implement, and it is usually easier to buy these types of optimizations than to build them.12.8.1 Compression
Where the distributed application is transferring large amounts of data over a network, the communications layer can be optimized to support compression of the data transfers. In order to minimize compression overhead for small data transfers, the compression mechanism should have a filter size below which compression is not used for data packets. The JDK documentation includes an extended example of installing a compression layer in the RMI communications layer the main documentation index page leads to RMI documentation under the Enterprise Features heading. The following code illustrates a simple example of adding compression into a communications layer. The bold type shows the extra code required: void writeTransferbyte[] transferbuffer, int offset, int len { if len = 0 return; int newlen = compresstransferbuffer, offset, len; communicationSocket.writelen; communicationSocket.writenewlen; communicationSocket.writetransferbuffer, offset, newlen; communicationSocket.flush ; } byte[] readTransfer throws IOException { int len = communicationSocket.read ; if len = 0 throw new IOExceptionblah blah; int newlen = communicationSocket.read ; if newlen = 0 throw new IOExceptionblah blah; int readlen = 0; byte[] transferbuffer = new byte[len]; int n; whilereadlen newlen { n = communicationSocket.readtransferbuffer, readlen, len-readlen; n = communicationSocket.readtransferbuffer, readlen, newlen-readlen; if n = 0 readlen += n; else - 277 - throw new IOExceptionblah blah again; } int decompresslen = decompresstransferbuffer, 0, newlen; if decompresslen = len throw new IOExceptionblah blah decompression; return transferbuffer; }12.8.2 Caching
Caching at the low-level communications layer is unusual and often a fallback position where the use of the communications layer is spread too widely within the application to retrofit low-level caching in the application itself. But caching is generally one of the best techniques for speeding up clientserver applications and should be used whenever possible, so you could consider low-level caching when caching cannot be added directly to the application. Caching at the low-level communications layer cannot be achieved generically. The following code illustrates an example of adding the simplest low-level caching in the communications layer. The bold type shows the extra code required: void writeTransferbyte[] transferbuffer, int offset, int len { if len = 0 return; check if we can cache this code CacheObject cacheObj = isCachabletransferbuffer, offset, len; if cacheObj = null { Assume this is simple non-interleaved writes, so we can simply set this cache obj as the cache to be read. The isCachable method must have filled in the cache, so it may include a remote transfer if this is the first time we cached this object. LastCache = cacheObj; return; } else { cacheObj = null; realWriteTransfertransferbuffer, offset, len; } } void realWriteTransferbyte[] transferbuffer, int offset, int len { communicationSocket.writelen; communicationSocket.writetransferbuffer, offset, len; communicationSocket.flush ; } byte[] readTransfer throws IOException { if LastCache = null { byte[] transferbuffer = LastCache.transferBuffer ; LastCache = null; return transferbuffer; } int len = communicationSocket.read ; if len = 0 throw new IOExceptionblah blah; int readlen = 0; - 278 - byte[] transferbuffer = new byte[len]; int n; whilereadlen newlen { n = communicationSocket.readtransferbuffer, readlen, len-readlen; if n = 0 readlen += n; else throw new IOExceptionblah blah again; } return transferbuffer; }12.8.3 Transfer Batching
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» OReilly.Java.performance tuning
» The Tuning Game System Limitations and What to Tune
» A Tuning Strategy Introduction
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» Comparing Communication Layers Distributed Computing
» Batching I Application Partitioning
» Compression Caching Low-Level Communication Optimizations
» Transfer Batching Low-Level Communication Optimizations
» Batching II Distributed Garbage Collection
» Performance Checklist Distributed Computing
» When Not to Optimize Tuning Class Libraries and Beans
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