research-article

Efficient Rebuilding of Large Java Heaps from Event Traces

Authors:

Verena Bitto,

Philipp Lengauer,

Hanspeter MössenböckAuthors Info & Claims

PPPJ '15: Proceedings of the Principles and Practices of Programming on The Java Platform

Pages 76 - 89

https://doi.org/10.1145/2807426.2807433

Published: 08 September 2015 Publication History

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Abstract

Understanding and tracking down memory-related performance problems, such as long garbage collection times and memory leaks, is a tedious task in large and complex applications. Memory profilers can support developers in this task by recording detailed traces of the application's memory behavior which can then be analyzed offline. Unfortunately, these traces can become huge, and processing them is a real challenge. If the goal is to rebuild the heap from a trace in order to analyze it, most state-of-the-art tools perform badly, because they are either too slow or provide only a coarse-grained view of the monitored application.

In this paper we present novel techniques and data structures for efficiently processing large event traces and for reconstructing the heap with only a fraction of the monitored application's memory. The reconstructed heap contains vital information about all objects, such as their addresses, their types, their allocation sites, and their allocating threads.

We also provide a detailed evaluation of our approach on 33 benchmarks, showing that we can rebuild the heap from a trace efficiently using only about 18% of the memory that was used in the monitored application.

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Cited By

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Sarnayak SAhuja AKesavarapu PNaik AKumar V. SKalambur SFeng DBecker SHerbst NLeitner P(2022)Analysis of Garbage Collection Patterns to Extend Microbenchmarks for Big Data WorkloadsCompanion of the 2022 ACM/SPEC International Conference on Performance Engineering10.1145/3491204.3527473(121-128)Online publication date: 14-Jul-2022
https://dl.acm.org/doi/10.1145/3491204.3527473
Weninger MGander EMössenböck H(2021)Guided ExplorationProceedings of the ACM on Human-Computer Interaction10.1145/34617315:EICS(1-34)Online publication date: 29-May-2021
https://dl.acm.org/doi/10.1145/3461731
Weninger MMakor LMossenbock H(2020)Memory Cities: Visualizing Heap Memory Evolution Using the Software City Metaphor2020 Working Conference on Software Visualization (VISSOFT)10.1109/VISSOFT51673.2020.00017(110-121)Online publication date: Sep-2020
https://doi.org/10.1109/VISSOFT51673.2020.00017
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Index Terms

Efficient Rebuilding of Large Java Heaps from Event Traces
1. Information systems
  1. Information storage systems
    1. Record storage systems
      1. Record storage alternatives
2. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language types
  2. Software organization and properties
    1. Contextual software domains
      1. Operating systems
        Memory management
        Garbage collection

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PPPJ '15: Proceedings of the Principles and Practices of Programming on The Java Platform

September 2015

190 pages

ISBN:9781450337120

DOI:10.1145/2807426

General Chair:
Ryan Stansifer
Florida Institute of Technology, USA
,
Program Chair:
Andreas Krall
Vienna University of Technology, Austria

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

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Published: 08 September 2015

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Christian Doppler Forschungsgesellschaft

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PPPJ '15

PPPJ '15: Principles and Practices of Programming on the Java Platform

September 8 - 11, 2015

FL, Melbourne, USA

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PPPJ '15 Paper Acceptance Rate 15 of 27 submissions, 56%;

Overall Acceptance Rate 29 of 58 submissions, 50%

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Sarnayak SAhuja AKesavarapu PNaik AKumar V. SKalambur SFeng DBecker SHerbst NLeitner P(2022)Analysis of Garbage Collection Patterns to Extend Microbenchmarks for Big Data WorkloadsCompanion of the 2022 ACM/SPEC International Conference on Performance Engineering10.1145/3491204.3527473(121-128)Online publication date: 14-Jul-2022
https://dl.acm.org/doi/10.1145/3491204.3527473
Weninger MGander EMössenböck H(2021)Guided ExplorationProceedings of the ACM on Human-Computer Interaction10.1145/34617315:EICS(1-34)Online publication date: 29-May-2021
https://dl.acm.org/doi/10.1145/3461731
Weninger MMakor LMossenbock H(2020)Memory Cities: Visualizing Heap Memory Evolution Using the Software City Metaphor2020 Working Conference on Software Visualization (VISSOFT)10.1109/VISSOFT51673.2020.00017(110-121)Online publication date: Sep-2020
https://doi.org/10.1109/VISSOFT51673.2020.00017
Weninger MGander EMössenböck HHosking AFinocchi I(2019)Detection of suspicious time windows in memory monitoringProceedings of the 16th ACM SIGPLAN International Conference on Managed Programming Languages and Runtimes10.1145/3357390.3361025(95-104)Online publication date: 21-Oct-2019
https://dl.acm.org/doi/10.1145/3357390.3361025
Weninger MMakor LGander EMössenböck HApte VDi Marco ALitoiu MMerseguer J(2019)AntTracks TrendVizCompanion of the 2019 ACM/SPEC International Conference on Performance Engineering10.1145/3302541.3313100(29-32)Online publication date: 27-Mar-2019
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Weninger MGander EMössenböck HApte VDi Marco ALitoiu MMerseguer J(2019)Analyzing Data Structure Growth Over Time to Facilitate Memory Leak DetectionProceedings of the 2019 ACM/SPEC International Conference on Performance Engineering10.1145/3297663.3310297(273-284)Online publication date: 4-Apr-2019
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Weninger MGander EMössenböck HTilevich EMössenböck H(2018)Utilizing object reference graphs and garbage collection roots to detect memory leaks in offline memory monitoringProceedings of the 15th International Conference on Managed Languages & Runtimes10.1145/3237009.3237023(1-13)Online publication date: 12-Sep-2018
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Weninger MMössenböck HWolter KKnottenbelt Wvan Hoorn ANambiar MKoziolek H(2018)User-defined Classification and Multi-level Grouping of Objects in Memory MonitoringProceedings of the 2018 ACM/SPEC International Conference on Performance Engineering10.1145/3184407.3184412(115-126)Online publication date: 30-Mar-2018
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Weninger MLengauer PMössenböck HBinder WCortellessa VKoziolek ASmirni EPoess M(2017)User-centered Offline Analysis of Memory Monitoring DataProceedings of the 8th ACM/SPEC on International Conference on Performance Engineering10.1145/3030207.3030236(357-360)Online publication date: 17-Apr-2017
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Lengauer PBitto VFitzek SWeninger MMössenböck HZheng YBinder WTůma P(2016)Efficient Memory Traces with Full Pointer InformationProceedings of the 13th International Conference on Principles and Practices of Programming on the Java Platform: Virtual Machines, Languages, and Tools10.1145/2972206.2972220(1-11)Online publication date: 29-Aug-2016
https://dl.acm.org/doi/10.1145/2972206.2972220
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Efficient Memory Traces with Full Pointer Information

Controlling garbage collection and heap growth to reduce the execution time of Java applications

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Efficient Memory Traces with Full Pointer Information

Controlling garbage collection and heap growth to reduce the execution time of Java applications

Implementing an on-the-fly garbage collector for Java

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