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The ATLAS detector at CERN has completed its first full year of recordingcollisions at 7 TeV, resulting in billions of events and petabytes of data. Atthese scales, physicists must have the capability to read only the data ofinterest to their analyses, with the importance of efficient selective accessincreasing as data taking continues. ATLAS has developed a sophisticatedevent-level metadata infrastructure and supporting I/O framework allowing eventselections by explicit specification, by back navigation, and by selectionqueries to a TAG database via an integrated web interface. These systems andtheir performance have been reported on elsewhere. The ultimate success of sucha system, however, depends significantly upon the efficiency of selective eventretrieval. Supporting such retrieval can be challenging, as ATLAS stores itsevent data in column-wise orientation using ROOT trees for a number of reasons,including compression considerations, histogramming use cases, and more. For2011 data, ATLAS will utilize new capabilities in ROOT to tune the persistentstorage layout of event data, and to significantly speed up selective eventreading. The new persistent layout strategy and its implications for I/Operformance are described in this paper.

Persistent Data Layout and Infrastructure for Efficient Selective Retrieval of Event Data in ATLAS