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Updated exeperimental setup, (esp object serialization) and acknowledgements.

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Sears Russell 2006-04-24 07:57:33 +00:00
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@ -1073,7 +1073,6 @@ use of a fixed pool of threads with a fixed think time. We found that
the latency of Berkeley DB and \yad were similar, showing that \yad is the latency of Berkeley DB and \yad were similar, showing that \yad is
not simply trading latency for throughput during the concurrency benchmark. not simply trading latency for throughput during the concurrency benchmark.
\subsection{Object serialization}
\begin{figure*}[t!] \begin{figure*}[t!]
\includegraphics[width=3.3in]{figs/object-diff.pdf} \includegraphics[width=3.3in]{figs/object-diff.pdf}
@ -1084,39 +1083,31 @@ not simply trading latency for throughput during the concurrency benchmark.
The effect of \yad object serialization optimizations under low and high memory pressure.} The effect of \yad object serialization optimizations under low and high memory pressure.}
\end{figure*} \end{figure*}
\subsection{Object persistance mechanisms} \subsection{Object persistance}
\rcs{ This belongs somewhere else: Instead, it leaves decisions regarding abstract data types and
algorithm design to system developers or language designers. For
instance, while \yad has no concept of object oriented data types, two
radically different approaches toward object persistance have been
implemented on top of it~\ref{oasys}.}
\rcs{We could have just as easily written a persistance mechanism for a
functional programming language, or a particular application (such as
an email server). Our experience building data manipulation routines
on top of application-specific primitives was favorable compared to
past experiences attempting to restructure entire applications to
match pre-existing computational models, such as SQL's declarative
interface.}
Numerous schemes are used for object serialization. Support for two Numerous schemes are used for object serialization. Support for two
different styles of object serialization have been eimplemented in different styles of object serialization have been eimplemented in
\yad. The first, pobj, provided transactional updates to objects in \yad. We could have just as easily implemented a persistance
Titanium, a Java variant. It transparently loaded and persisted mechanism for a statically typed functional programming language, a
dynamically typed scripting language, or a particular application,
such as an email server. In each case, \yads lack of a hardcoded data
model would allow us to choose a representation and transactional
semantics that made the most sense for the system at hand.
The first object persistance mechanism, pobj, provides transactional updates to objects in
Titanium, a Java variant. It transparently loads and persists
entire graphs of objects. entire graphs of objects.
The second variant was built on top of a generic C++ object The second variant was built on top of a generic C++ object
serialization library, \oasys. \oasys makes use of pluggable storage serialization library, \oasys. \oasys makes use of pluggable storage
modules to actually implement persistant storage, and includes plugins modules that implement persistant storage, and includes plugins
for Berkeley DB and MySQL. This section will describe how the \yads for Berkeley DB and MySQL.
This section will describe how the \yad
\oasys plugin reduces the runtime serialization/deserialization cpu \oasys plugin reduces the runtime serialization/deserialization cpu
overhead of write intensive workloads, while using half as much system overhead of write intensive workloads, while using half as much system
memory as the other two systems. memory as the other two systems.
We present three variants of \yad here. The first treats \yad like We present three variants of the \yad plugin here. The first treats \yad like
Berkeley DB. The second customizes the behavior of the buffer Berkeley DB. The second customizes the behavior of the buffer
manager. Instead of maintaining an up-to-date version of each object manager. Instead of maintaining an up-to-date version of each object
in the buffer manager or page file, it allows the buffer manager's in the buffer manager or page file, it allows the buffer manager's
@ -1124,32 +1115,108 @@ view of live application objects to become stale. This is safe since
the system is always able to reconstruct the appropriate page entry the system is always able to reconstruct the appropriate page entry
form the live copy of the object. form the live copy of the object.
By allowing the buffer manager to contain stale data, we reduce the
number of times the \yad \oasys plugin must serialize objects to
update the page file. The reduced number of serializations decreases
CPU utilization, and it also allows us to drastically decrease the
size of the page file. In turn this allows us to increase the size of
the application's cache of live objects.
We implemented the \yad buffer pool optimization by adding two new
operations, update(), which only updates the log, and flush(), which
updates the page file.
The reason it would be difficult to do this with Berkeley DB is that The reason it would be difficult to do this with Berkeley DB is that
we still need to generate log entries as the object is being updated. we still need to generate log entries as the object is being updated.
Otherwise, commit would not be durable, and the application would be Otherwise, commit would not be durable, unless we queued up log
unable to abort() transactions. Even if we decided to disallow entries, and wrote them all before committing.
application aborts, we would still need to write log entries
committing. This would cause Berekley DB to write data back to the committing. This would cause Berekley DB to write data back to the
page file, increasing the working set of the program, and increasing page file, increasing the working set of the program, and increasing
disk activity. disk activity.
Under \yad, we implemented this optimization by adding two new Furthermore, because objects may be written to disk in an
operations, update(), which only updates the log, and flush(), which order that differs from the order in which they were updated, we need
updates the page file. We decrease the size of the page file, so to maintain multiple LSN's per page. This means we need to register a
flush() is likely to incur disk overhead. However, we have roughly callback with the recovery routing to process the LSN's. (A similar
doubled the number of objects that are cached in memory, and expect callback will be needed in Section~\ref{sec:zeroCopy}.) Also,
flush() to be called relatively infrequently. we must prevent \yads storage routine from overwriting the per-object
LSN's of deleted objects that may still be addressed during abort or recovery.
The third \yad plugin to \oasys incorporated all of the updates of the Alternatively, we could arrange for the object pool to cooperate
second, but arranged to only the changed portions of objects to the further with the buffer pool by atomically updating the buffer
log. manager's copy of all objects that share a given page, removing the
need for multiple LSN's per page, and simplifying storage allocation.
Figure~\ref{objectSerialization} presents the performance of the three However, the simplest solution to this problem is to observe that
updates (not allocations or deletions) to fixed length objects meet
the requirements of the LSN free transactional update scheme, and that
we may do away with per-object LSN's entirely.\endnote{\yad does not
yet implement LSN-free pages. In order to obtain performance
numbers for object serialization, we made use of our LSN page
implementation. The runtime performance impact of LSN-free pages
should be negligible.} Allocation and deletion can then be handled
as updates to normal LSN containing pages. At recovery time, object
updates are executed based on the existence of the object on the page,
and a conservative estimate of its LSN. (If the page doesn't contain
the object during REDO, then it must have been written back to disk
after the object was deleted. Therefore, we do not need to apply the
REDO.)
The third \yad plugin to \oasys incorporates all of the optimizations
present in the second plugin, but arranges to only write the changed
portions of objects to the log. Because of \yad's support for custom
log entry formats, this optimization is straightforward.
In addition to the buffer pool optimizations, \yad provides several
options to handle UNDO records in the context
of object serialization. The first is to use a single transaction for
each object modification, avoiding the cost of generating or logging
any UNDO records. The second option is to assume that the
application will provide a custom UNDO for the delta,
which increases the size of the log entry generated by each update,
but still avoids the need to read or update the page
file.
The third option is to relax the atomicity requirements for a set of
object updates and again avoid generating any UNDO records. This
assumes that the application cannot abort individual updates,
and is willing to
accept that some prefix of logged but uncommitted updates may
be applied to the page
file after recovery. These ``transactions'' would still be durable
after commit(), as it would force the log to disk.
For the benchmarks below, we
use this approach, as it is the most aggressive and is
not supported by any other general-purpose transactional
storage system (that we know of).
The operations required for these two optimizations required a mere
150 lines of C code, including whitespace, comments and boilerplate
function registrations.\endnote{These figures do not include the
simple LSN free object logic required for recovery, as \yad does not
yet support LSN free operations.} Although the reasoning required
to ensure the correctness of this code is complex, the simplicity of
the implementation is encouraging.
In this experiment, Berkeley DB was configured as described above. We
ran MySQL using InnoDB for the table engine, as it is the fastest
engine that provides similar durability to \yad. For this test, we
also linked directly with the libmysqld daemon library, bypassing the
RPC layer. In experiments that used the RPC layer, test completion
times were orders of magnitude slower.
Figure~\ref{fig:OASYS} presents the performance of the three
\yad optimizations, and the \oasys plugins implemented on top of other \yad optimizations, and the \oasys plugins implemented on top of other
systems. As we can see, \yad performs better than the baseline systems. As we can see, \yad performs better than the baseline
systems. More interestingly, in non-memory bound systems, the systems, which is not surpising, since it is not providing the A
optimizations nearly double \yads performance, and we see that in the property of ACID transactions.
memory-bound setup, update/flush indeed improves memory utilization.
In non-memory bound systems, the optimizations nearly double \yads
performance by reducing the CPU overhead of object serialization and
the number of log entries written to disk. In the memory bound test,
we see that update/flush indeed improves memory utilization.
\subsection{Manipulation of logical log entries} \subsection{Manipulation of logical log entries}
@ -1294,7 +1361,16 @@ mechanism. (Section~\ref{logging})
\section{Acknowledgements} \section{Acknowledgements}
mike demmer, others? The idea behind the \oasys buffer manager optimization is from Mike
Demmer. He and Bowei Du implemented \oasys. Gilad and Amir were
responsible for pobj. Jim Blomo, Jason Bayer, and Jimmy
Kittiyachavalit worked on an earliy version of \yad.
Thanks to C. Mohan for pointing out the need for tombstones with
per-object LSN's. Jim Gray provided feedback on an earlier version of
this paper, and suggested we build a resource manager to manage
dependencies within \yads API. Joe Hellerstein and Mike Franklin
provided us with invaluable feedback.
\section{Availability} \section{Availability}