I'm Peter Ohler and this is my site. Have a look around and check out the open
source projects linked by the large Os on the right side of the page. You can view my old pages by
clicking on the Old link. If you want to contact me you can email me
at peter@ohler.com.
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The latest addition to my open source projects
is Agoo,
is a high performance web server gem for
Ruby. Agoo includes a new publish and subscribe
model that the author
of Iodine
and I worked together
on. A short
article describes the API for pub/sub with some
example code.
Agoo turned out well enough that the code for it is
being folded back
into OpO. Future
enhancements to Agoo will also be part of OpO.
read more...
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How about a graph database? Performance on the
currently available graph databases or triple stores
is not that impressive. It seems like an area worth
exploring. OpO
is my attempt at triple store exploration. It's
looking pretty fast so far. On the long term road
map are support for RDF, TURTLE, and SPARQL.
The project re-uses some of the HTTP server code
from Piper Push
Cache and gets similar latency and
throughput. Even with REST over HTTP and not a
custom interface more than 100,000 retrievals per
second are possible.
read more...
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Most of the systems I develop use push to move data
around. JSON is another area I've accumulated a fair
amount of expertise in. Putting the two together in
a web server resulted
in Piper Push
Cache, a very fast scalable web server that has
build in support for push in a number of ways. The
performance surprised me as it performed better than
nginx. Check out
the benchmarks.
The first push technology is getting data in the
form of JSON out to web pages. This uses my own
WebSockets implementation. SSE is used for mobile
browsers. The second use of push is getting data
from the server to other applications. For
this NATS is used.
The final bit of fun
in Piper Push
Cache is a process flow engine. The fun part of
that was using Javascript to write a complete
process flow editor.
read more...
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OFlow is the latest in a series of process flow
tools I've worked on over the years going back to my first one at TIBCO Software.
OFlow relies on queues, immutable data, and a
separate thread for each task in a process flow. It is build to allow highly parallel
processing.
GemChart is a somewhat non trivial example of
how OFlow can be used. It also gave me an excuse
to put together a graphing application for charting downloads of my gems. It was fun to put
together and gave me a chance to test out the debugging and tracing tools
in OFlow.
read more...
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The disappearance of Apple's iDisk left a hole in my backup strategy that needed to be
filled. I no longer had a place to backup my files and pull them onto multiple
computers. iCloud, the iDisk replacement supports only Apple compliant product files and not
arbitrary files. It was the perfect opportunity or rather and excuse to try
out OPEE and
see how well the alternative threading approach worked. As long as I was rolling my own
solution for remote storage it might as well be encrypted and compressed. The result
is oDisk.
read more...
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The Object-based Parallel Evaluation Environment or OPEE project explores an alternative approach to
using multiple threads for system design. OPEE was purpose built to solve problem encountered
in system that involve significant processing and shared resources. Shared resources are
components such as file writers, hash tables, and summary data. A trading system design is
explored in this article.
read more...
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After writing
Ox, a fast XML
parser, a fast JSON parser seems like the good next project to tackle. The goal was to come up
with a parser that was as fast as possible while still providing a consistent and
understandable API. The JSON parser, Oj was so much faster than any of the other JSON
parsers that it seemed worth describing the process involved in how those results were
achieved.
read more...
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There are several ways to parse an XML document. Which one to choose depends on the
application. Three approaches are explored here. All three approaches parse an Apple plist XML
document and convert it into a Hash tree with native values and Arrays.
The first approach makes use of an in memory parser and then converts the resulting document
Ruby Objects into a Hash. The second uses a SAX like callback parser to create a Hash tree
directly. The third converts the XML to a serialized Object format and then loads that XML
directly into a Hash. Performance and simplicity is considered in all cases.
read more...
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Parse Approach Comparison |
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XML is a well documented, widely used, and well supported format for encoding data. It is
heavily used on the web and with languages such as Java. XML format is stable and well
documented. The downside is it is rather verbose but that is also what makes it readable by
humans as well as machines.The wide support in almost every language for XML makes it
extremely portable.
Until recently using XML with Ruby was not a high performance option. The two most common and
highest performing Ruby Gems were Nokogiri and LibXML. Both provide parsing to Ruby Object
representation of an XML document as well as a SAX like stream
parser. The Ox
gem was created to address the need for a more optimized XML parser so that the advantages of
XML could be made available in Ruby without suffering the performance impact.
read more...
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SAX Comparison |
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Parse Compare |
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In an attempt to use a more portable Object serialization method than Marshal that performed
as well or better, Ox was born. A Ruby implementation on top of Nokogiri
was prohibitively slower than using the native Ruby Marshal module.
Marshal has a number of problem though. The format changes from one Ruby version to the next
and it is not portable between any other languages. It is a binary format that is difficult to
read, debug, or edit.
As a extension, Ox is able to dump and load a Ruby Object to and from XML faster than the
native Ruby Marshal can. Ox also supports serialization of Exceptions better than Marshal.
read more...
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Load Results |
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Dump Results |
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