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Optimizing ATLAS data storage: the impact of compression algorithms on ATLAS physics analysis data formats

The increased footprint foreseen for Run-3 and HL-LHC data will soon expose the limits of currently available storage and CPU resources. Data formats are already optimized according to the processing chain for which they are designed. ATLAS events are stored in ROOT-based reconstruction output files...

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Autores principales: Marcon, Caterina, Carminati, Leonardo, Van Gemmeren, Peter, Mete, Alaettin Serhan
Lenguaje:eng
Publicado: 2023
Materias:
Acceso en línea:http://cds.cern.ch/record/2857279
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author Marcon, Caterina
Carminati, Leonardo
Van Gemmeren, Peter
Mete, Alaettin Serhan
author_facet Marcon, Caterina
Carminati, Leonardo
Van Gemmeren, Peter
Mete, Alaettin Serhan
author_sort Marcon, Caterina
collection CERN
description The increased footprint foreseen for Run-3 and HL-LHC data will soon expose the limits of currently available storage and CPU resources. Data formats are already optimized according to the processing chain for which they are designed. ATLAS events are stored in ROOT-based reconstruction output files called Analysis Object Data (AOD), which are then processed within the derivation framework to produce Derived AOD (DAOD) files. Numerous DAOD formats, tailored for specific physics and performance groups, have been in use throughout the ATLAS Run-2 phase. In view of Run-3, ATLAS has changed its Analysis Model, which entailed a significant reduction of the existing DAOD flavors. Two new, unfiltered and skimmable on read, formats have been proposed as replacements: DAOD_PHYS, designed to meet the requirements of the majority of the analysis workflows, and DAOD_PHYSLITE, a smaller format containing already calibrated physics objects. As ROOT-based formats, they natively support four lossless compression algorithms: Lzma, Lz4, Zlib and Zstd. In this study, the effects of different compression settings on file size, compression time, compression factor and reading speed are investigated considering both DAOD_PHYS and DAOD_PHYSLITE formats. Total as well as partial event reading strategies have been tested. Moreover, the impact of AutoFlush and SplitLevel, two parameters controlling how in-memory data structures are serialized to ROOT files, has been evaluated. This study yields quantitative results that can serve as a paradigm on how to make compression decisions for different ATLAS' use cases. As an example, for both DAOD_PHYS and DAOD_PHYSLITE, the Lz4 library exhibits the fastest reading speed, but results in the largest files, whereas the Lzma algorithm provides larger compression factors at the cost of significantly slower reading speeds. In addition, guidelines for setting appropriate AutoFlush and SplitLevel values are outlined.
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institution Organización Europea para la Investigación Nuclear
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publishDate 2023
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spelling cern-28572792023-04-30T19:25:45Zhttp://cds.cern.ch/record/2857279engMarcon, CaterinaCarminati, LeonardoVan Gemmeren, PeterMete, Alaettin SerhanOptimizing ATLAS data storage: the impact of compression algorithms on ATLAS physics analysis data formatsParticle Physics - ExperimentThe increased footprint foreseen for Run-3 and HL-LHC data will soon expose the limits of currently available storage and CPU resources. Data formats are already optimized according to the processing chain for which they are designed. ATLAS events are stored in ROOT-based reconstruction output files called Analysis Object Data (AOD), which are then processed within the derivation framework to produce Derived AOD (DAOD) files. Numerous DAOD formats, tailored for specific physics and performance groups, have been in use throughout the ATLAS Run-2 phase. In view of Run-3, ATLAS has changed its Analysis Model, which entailed a significant reduction of the existing DAOD flavors. Two new, unfiltered and skimmable on read, formats have been proposed as replacements: DAOD_PHYS, designed to meet the requirements of the majority of the analysis workflows, and DAOD_PHYSLITE, a smaller format containing already calibrated physics objects. As ROOT-based formats, they natively support four lossless compression algorithms: Lzma, Lz4, Zlib and Zstd. In this study, the effects of different compression settings on file size, compression time, compression factor and reading speed are investigated considering both DAOD_PHYS and DAOD_PHYSLITE formats. Total as well as partial event reading strategies have been tested. Moreover, the impact of AutoFlush and SplitLevel, two parameters controlling how in-memory data structures are serialized to ROOT files, has been evaluated. This study yields quantitative results that can serve as a paradigm on how to make compression decisions for different ATLAS' use cases. As an example, for both DAOD_PHYS and DAOD_PHYSLITE, the Lz4 library exhibits the fastest reading speed, but results in the largest files, whereas the Lzma algorithm provides larger compression factors at the cost of significantly slower reading speeds. In addition, guidelines for setting appropriate AutoFlush and SplitLevel values are outlined.ATL-SOFT-SLIDE-2023-111oai:cds.cern.ch:28572792023-04-29
spellingShingle Particle Physics - Experiment
Marcon, Caterina
Carminati, Leonardo
Van Gemmeren, Peter
Mete, Alaettin Serhan
Optimizing ATLAS data storage: the impact of compression algorithms on ATLAS physics analysis data formats
title Optimizing ATLAS data storage: the impact of compression algorithms on ATLAS physics analysis data formats
title_full Optimizing ATLAS data storage: the impact of compression algorithms on ATLAS physics analysis data formats
title_fullStr Optimizing ATLAS data storage: the impact of compression algorithms on ATLAS physics analysis data formats
title_full_unstemmed Optimizing ATLAS data storage: the impact of compression algorithms on ATLAS physics analysis data formats
title_short Optimizing ATLAS data storage: the impact of compression algorithms on ATLAS physics analysis data formats
title_sort optimizing atlas data storage: the impact of compression algorithms on atlas physics analysis data formats
topic Particle Physics - Experiment
url http://cds.cern.ch/record/2857279
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AT carminatileonardo optimizingatlasdatastoragetheimpactofcompressionalgorithmsonatlasphysicsanalysisdataformats
AT vangemmerenpeter optimizingatlasdatastoragetheimpactofcompressionalgorithmsonatlasphysicsanalysisdataformats
AT metealaettinserhan optimizingatlasdatastoragetheimpactofcompressionalgorithmsonatlasphysicsanalysisdataformats