We are now witnessing an unprecedented growth of data that needs to be processed at always increasing rates in order to extract valuable insights. Big Data streaming analytics tools have been developed to cope with the online dimension of data processing: they enable real-time handling of live data sources by means of stateful aggregations (operators). Current state-of-art frameworks (e.g. Apache Flink [1]) enable each operator to work in isolation by creating data copies, at the expense of increased memory utilization. In this paper, we explore the feasibility of deduplication techniques to address the challenge of reducing memory footprint for window-based stream processing without significant impact on performance. We design a deduplicat...
The ability to process large volumes of data on the fly, as soon as they become available, is a fund...
At the moment we are witnessing the maturation of distributed streaming dataflow systems whose use-c...
The topic of Data Stream Processing is a recent and highly active research area dealing with the in-...
We are now witnessing an unprecedented growth of data that needs to be processed at always increasin...
International audienceWe are now witnessing an unprecedented growth of data that needs to be process...
First-generation streaming systems did not pay much attention to state management via ACID transacti...
Big Data applications are rapidly moving from a batch-oriented execution model to a streaming execut...
International audienceBig Data applications are rapidly moving from a batch-oriented execution model...
Modern distributed stream processors predominantly rely on LSM-based key-value stores to manage the ...
International audienceDistributed stream processing engines continuously execute series of operators...
International audienceOver the past decade, given the higher number of data sources (e.g., Cloud app...
Under the pressure of massive, exponentially increasing amounts ofheterogeneous data that are genera...
Current systems for data-parallel, incremental processing and view maintenance over high-rate stream...
Data-stream management systems have for long been considered as a promising architecture for fast da...
The adoption of the serverless architecture and the Function-as-a-Service model has significantly in...
The ability to process large volumes of data on the fly, as soon as they become available, is a fund...
At the moment we are witnessing the maturation of distributed streaming dataflow systems whose use-c...
The topic of Data Stream Processing is a recent and highly active research area dealing with the in-...
We are now witnessing an unprecedented growth of data that needs to be processed at always increasin...
International audienceWe are now witnessing an unprecedented growth of data that needs to be process...
First-generation streaming systems did not pay much attention to state management via ACID transacti...
Big Data applications are rapidly moving from a batch-oriented execution model to a streaming execut...
International audienceBig Data applications are rapidly moving from a batch-oriented execution model...
Modern distributed stream processors predominantly rely on LSM-based key-value stores to manage the ...
International audienceDistributed stream processing engines continuously execute series of operators...
International audienceOver the past decade, given the higher number of data sources (e.g., Cloud app...
Under the pressure of massive, exponentially increasing amounts ofheterogeneous data that are genera...
Current systems for data-parallel, incremental processing and view maintenance over high-rate stream...
Data-stream management systems have for long been considered as a promising architecture for fast da...
The adoption of the serverless architecture and the Function-as-a-Service model has significantly in...
The ability to process large volumes of data on the fly, as soon as they become available, is a fund...
At the moment we are witnessing the maturation of distributed streaming dataflow systems whose use-c...
The topic of Data Stream Processing is a recent and highly active research area dealing with the in-...