conference-paper
وصول مفتوح
Selecting Efficient Cluster Resources for Data Analytics: When and How to Allocate for In-Memory Processing?
Research footprint
At a glance
- الاستشهادات
- 2
- المراجع
- 15
- Comments
- 0
Paper overview
Abstract
Distributed dataflow systems such as Apache Spark or Apache Flink enable parallel, in-memory data processing on large clusters of commodity hardware. Consequently, the appropriate amount of memory to allocate to the cluster is a crucial consideration.
Record transparency
Publication details
- DOI
- 10.1145/3603719.3603733
- OpenAlex
- W4379932663
- Document type
- conference-paper
- Language
- EN
- Last metadata update
Comments
تسجيل الدخول للانضمام إلى النقاش.