Bewegte Bilder
BriskStream: Scaling Data Stream Processing on Shared-Memory Multicore Architectures
We introduce BriskStream, an in-memory data stream processing system (DSPSs) specifically designed for modern shared-memory multicore architectures. BriskStream’s key contribution is an execution plan optimization paradigm, namely RLAS, which takes relative-location (i.e., NUMA distance) of each pair of producer-consumer operators into consideration. We propose a branch and bound based approach with three heuristics to resolve the resulting nontrivial optimization problem. The experimental evaluations demonstrate that BriskStream yields much higher throughput and better scalability than existing DSPSs on multi-core architectures when processing different types of workloads.
- Standort
-
Hannover TIB
- Umfang
-
376MB, 00:14:44:11 (unknown)
- Sprache
-
Englisch
- Anmerkungen
-
Audiovisuelles Material
- Erschienen in
-
SIGMOD 2019 ; (Jan. 2019)
- Ereignis
-
Veröffentlichung
- (wer)
-
ACM SIGMOD
- (wann)
-
2019-01-01
- Beteiligte Personen und Organisationen
-
Zhang, Shuhao
He, Jiong
Zhou, Amelie
He, Bingsheng
- DOI
-
10.5446/42978
- Letzte Aktualisierung
- 21.04.2026, 10:49 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Technische Informationsbibliothek (TIB).
Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- zweidimensionales bewegtes Bild
Beteiligte
- Zhang, Shuhao
- He, Jiong
- Zhou, Amelie
- He, Bingsheng
- ACM SIGMOD
Entstanden
- 2019-01-01
Ähnliche Objekte (12)
BriskStream: Scaling Data Stream Processing on Shared-Memory Multicore Architectures
AStream: Ad-hoc Shared Stream Processing
AStream: Ad-hoc Shared Stream Processing
Elasticutor: Rapid Elasticity for Realtime Stateful Stream Processing
Elasticutor: Rapid Elasticity for Realtime Stateful Stream Processing
Remembering the Probabilistic Analysis of Latent Semantic Indexing
SIGMOD Test-Of-Time Award Talk: Building Tools for Differentially Private Data Analysis
Topic Pages: From Articles to Answers
Algorithmic Fairness: Measures, Methods and Representations
Approximate Distinct Counts for Billions of Datasets
The Selfish Models Property: Bounding the Complexity of Query Containment and Entailment Problems
Responsible Data Science
BriskStream: Scaling Data Stream Processing on Shared-Memory Multicore Architectures
AStream: Ad-hoc Shared Stream Processing
AStream: Ad-hoc Shared Stream Processing
Elasticutor: Rapid Elasticity for Realtime Stateful Stream Processing
Elasticutor: Rapid Elasticity for Realtime Stateful Stream Processing
Remembering the Probabilistic Analysis of Latent Semantic Indexing
SIGMOD Test-Of-Time Award Talk: Building Tools for Differentially Private Data Analysis
Topic Pages: From Articles to Answers
Algorithmic Fairness: Measures, Methods and Representations
Approximate Distinct Counts for Billions of Datasets
The Selfish Models Property: Bounding the Complexity of Query Containment and Entailment Problems
Responsible Data Science
BriskStream: Scaling Data Stream Processing on Shared-Memory Multicore Architectures
AStream: Ad-hoc Shared Stream Processing
AStream: Ad-hoc Shared Stream Processing
Elasticutor: Rapid Elasticity for Realtime Stateful Stream Processing
Elasticutor: Rapid Elasticity for Realtime Stateful Stream Processing
Remembering the Probabilistic Analysis of Latent Semantic Indexing
SIGMOD Test-Of-Time Award Talk: Building Tools for Differentially Private Data Analysis
Topic Pages: From Articles to Answers
Algorithmic Fairness: Measures, Methods and Representations
Approximate Distinct Counts for Billions of Datasets
The Selfish Models Property: Bounding the Complexity of Query Containment and Entailment Problems