Analysis of Garbage Collection Patterns to Extend Microbenchmarks for Big Data Workloads-Reference-Cited by-同舟云学术

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Analysis of Garbage Collection Patterns to Extend Microbenchmarks for Big Data Workloads

Published:2022-07-14 Issue: Volume: Page:
ISSN:
Container-title:Companion of the 2022 ACM/SPEC International Conference on Performance Engineering
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Author:

Sarnayak Samyak S.¹,Ahuja Aditi¹,Kesavarapu Pranav¹,Naik Aayush¹,Kumar V. Santhosh¹,Kalambur Subramaniam¹

Affiliation:

1. PES University, Bangalore, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3491204.3527473

Reference23 articles.

1. Apache Hadoop team. 2012. Dancing Links codebase. http://svn.apache. org/viewvc/hadoop/common/trunk/hadoop-mapreduce-project/hadoopmapreduce- examples/src/main/java/org/apache/hadoop/examples/dancing/ Apache Hadoop team. 2012. Dancing Links codebase. http://svn.apache. org/viewvc/hadoop/common/trunk/hadoop-mapreduce-project/hadoopmapreduce- examples/src/main/java/org/apache/hadoop/examples/dancing/

2. The BBP Algorithm for Pi

3. Efficient Rebuilding of Large Java Heaps from Event Traces

4. On the Locality of Java 8 Streams in Real-Time Big Data Applications

5. Dask Development Team . 2016 . Dask: Library for dynamic task scheduling. https: //dask.org Dask Development Team. 2016. Dask: Library for dynamic task scheduling. https: //dask.org

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