Abstract
Nowadays, numerous programming languages and frameworks offer concurrency based on the actor model. Among the actor libraries for the Java Virtual Machine, Akka is the most used one, as it is employed in various parallel and distributed applications and frameworks. Unfortunately, despite the spread of actors libraries, Akka in particular, existing profiling tools are not very effective at identifying performance drawbacks in applications using actors. In this tool paper, we aim at filling this gap by presenting AkkaProf, a profiling tool for Akka actors. AkkaProf provides detailed metrics on actor utilization and on the communication between them, two fundamental aspects of actor-based applications that are overlooked by other profilers. AkkaProf aids performance analysis in several applications and frameworks in both parallel and distributed environments.
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Notes
- 1.
- 2.
Akka actors have replaced Scala actors since Scala 2.10.
- 3.
All evaluation results are measured on a multicore platform (Intel Xeon E5-2680 2.7 GHz with 16 cores, 128 GB of RAM, CPU frequency scaling and Turbo mode disabled, Oracle JDK 1.8.0_66 b17 Hotspot Server VM 64-bit, Ubuntu Linux Server 64-bit version 14.04.3 64-bit). Each Spark o Flink worker is deployed on one such platform.
- 4.
We applied the algorithm on a reduced set of 20k webpages taken from a public data source [18].
- 5.
With this term, we refer to the Pearson product-moment correlation coefficient.
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Acknowledgments
This work has been supported by the Swiss National Science Foundation (project 200021_141002) and by the European Commission (contract ACP2-GA-2013-605442).
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Rosà, A., Chen, L.Y., Binder, W. (2016). AkkaProf: A Profiler for Akka Actors in Parallel and Distributed Applications. In: Igarashi, A. (eds) Programming Languages and Systems. APLAS 2016. Lecture Notes in Computer Science(), vol 10017. Springer, Cham. https://doi.org/10.1007/978-3-319-47958-3_8
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