Τίτλος:
Dione: A Framework for Automatic Profiling and Tuning Big Data
Applications
Γλώσσες Τεκμηρίου:
Αγγλικά
Περίληψη:
In this demonstration we present Dione a novel framework for automatic
profiling and tuning big data applications. Our system allows a
non-expert user to submit Spark or Flink applications to his/her cluster
and Dione automatically determines the impact of different configuration
parameters on the application's execution time and monetary cost. Dione
is the first framework that exploits similarities in the execution plans
of different applications to narrow down the amount of profiling runs
that are required for building prediction models that capture the impact
of the configuration parameters on the metrics of interest. Dione
exploits these prediction models to tune the configuration parameters in
a way that minimizes the application's execution time or the user's
budget. Finally, Dione's Web-UI visualizes the impact of the
configuration parameters on the execution time and the monetary cost,
and enables the user to submit the application with the recommended
parameters' values.
Συγγραφείς:
Zacheilas, Nikos
Maroulis, Stathis
Priovolos, Thanasis and
Kalogeraki, Vana
Gunopulos, Dimitrios
Εκδότης:
IEEE Comput. Soc
Τίτλος συνεδρίου:
2018 IEEE 34TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE)
DOI:
10.1109/ICDE.2018.00195
