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This revision made February 10, 2012 20:47, by nicolasmichael

Performance Data Analyzer Wiki

The Performance Data Analyzer (PDA) is a tool for analysis and correlation of performance data, as well as for report generation. Its parsers are capable of parsing various different file formats, from OS statistics as iostat, mpstat, vmstat, sar, etc., over garbage collection logfiles, generic CSV parsers to parsers that extract events from logfiles. Its extensible parser framework allows to easily add more parsers for any arbitrary format - as long as it can be expressed as values over time.

The heart of PDA is an interactive GUI which allows to plot samples from various different files (using various different parsers) in one single graph, thus correlating data from multiple sources based on a common time scale. Zooming allows to further zoom into the graph. A statistics function can generate statistics about the selected data.

PDA also allows to create HTML reports containing graphs and tables from data it finds crawling though a directory and analyzing this data based on a pre-defined configuraiton.

Getting Started with PDA


After downloading PDA, follow his short demo on a tour explaining the basic concepts of PDA.

Difference compared to previous revision
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Th<span style="text-decoration:underline;color:green">e heart of PDA </span>is <span style="text-decoration:underline;color:green">an interactive GUI </span>w<span style="text-decoration:underline;color:green">h</span>i. This wi<span style="text-decoration:line-through;color:red">k</span>i<span style="text-decoration:underline;color:green">ch allows to plot samples from var</span><span style="text-decoration:underline;color:green">ous</span> <span style="text-decoration:underline;color:green">different files (</span>us<span style="text-decoration:underline;color:green">ing various diff</span>e<span style="text-decoration:underline;color:green">rent par</span>s<span style="text-decoration:underline;color:green">ers)</span>i uses <span style="text-decoration:line-through;color:red">M</span> <span style="text-decoration:underline;color:green">in on</span>e<span style="text-decoration:underline;color:green"> single graph, thus correlating </span>d<span style="text-decoration:underline;color:green">ata from mult</span>i<span style="text-decoration:underline;color:green">ple sources b</span>a<span style="text-decoration:underline;color:green">sed on a common time scale. Zooming allo</span>w<span style="text-decoration:underline;color:green">s to further zoom </span>ediawi<span style="text-decoration:line-through;color:red">k</span>i<span style="text-decoration:underline;color:green">nto the graph. A stat</span><span style="text-decoration:underline;color:green">stics</span> f<span style="text-decoration:underline;color:green">uncti</span>o<span style="text-decoration:underline;color:green">n can gene</span>r<span style="text-decoration:underline;color:green">ate statistics about the selected data. PDA also allows to create HTML reports containing graphs and tables fro</span>m<span style="text-decoration:underline;color:green"> d</span>at<span style="text-decoration:underline;color:green">a i</span>t<span style="text-decoration:underline;color:green"> f</span>in<span style="text-decoration:underline;color:green">ds crawlin</span>g<span style="text-decoration:underline;color:green"> though a directory and analyzing this data based on a pre-defined configuraiton</span>. <span style="text-decoration:underline;color:green"> == Getting Started with PDA After downloading PDA, follow [[tGettingStarted|his short demo]] on a tour explaining the basic concepts of PDA.</span><span>
 
 
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