defined "Hot Set" for Oasys experiement,
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@ -1369,17 +1369,27 @@ linked the benchmark's executable to the {\tt libmysqld} daemon library,
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bypassing the RPC layer. In experiments that used the RPC layer, test
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completion times were orders of magnitude slower.
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Figure~\ref{fig:OASYS} presents the performance of the three
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\yad optimizations, and the \oasys plugins implemented on top of other
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systems. As we can see, \yad performs better than the baseline
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systems, which is not surprising, since it is not providing the A
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property of ACID transactions. (Although it is applying each individual operation atomically.)
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Figure~\ref{fig:OASYS} presents the performance of the three \yad
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optimizations, and the \oasys plugins implemented on top of other
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systems. In this test, none of the systems were memory bound. As
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we can see, \yad performs better than the baseline systems, which is
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not surprising, since it is not providing the A property of ACID
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transactions. (Although it is applying each individual operation
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atomically.)
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In non-memory bound systems, the optimizations nearly double \yads
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performance by reducing the CPU overhead of object serialization{\rcs different word?} and
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the number of log entries written to disk. In the memory bound test,
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we see that update/flush indeed improves memory utilization.
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performance by reducing the CPU overhead of copying marshalling and
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unmarshalling objects, and by reducing the size of log entries written
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to disk.
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To determine the effect of the optimization in memory bound systems,
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we decreased \yads page cache size, and used O\_DIRECT to bypass the
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operating system's disk cache. We then partitioned the set of objects
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so that 10\% fit in a {\em hot set} that is small enough to fit into
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memory. We then measured \yads performance as we varied the
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percentage of object updates that manipulate the hot set. In the
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memory bound test, we see that update/flush indeed improves memory
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utilization.
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\subsection{Manipulation of logical log entries}
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