At the moment we are witnessing the maturation of distributed streaming dataflow systems whose use-cases have departed from the mere analysis of streaming windows and complex-event processing, as they now extend to cloud applications, workflows and even e-commerce. The state of streaming operators has been so far hidden from external applications. In this thesis it is argued that exposing this internal state to outside applications by making it queryable, opens the road for novel use-cases. To this end, we introduce S-Query: a system and reference architecture where the state of stream operators can be queried - either live or through snapshots, achieving different isolation levels. It is shown how this can be implemented in an existing ope...
Under the pressure of massive, exponentially increasing amounts ofheterogeneous data that are genera...
Distributed Data Stream Management Systems (DSMS) are increasingly used for the processing of high-r...
We are now witnessing an unprecedented growth of data that needs to be processed at always increasin...
First-generation streaming systems did not pay much attention to state management via ACID transacti...
The need for scalable and efficient stream analysis has led to the development of many open-source s...
As users of “big data ” applications expect fresh results, we witness a new breed of stream processi...
The ability to process large volumes of data on the fly, as soon as they become available, is a fund...
As users of “big data ” applications expect fresh results, we witness a new breed of stream pro-cess...
Present-day computing systems have to deal with a continuous growth of data rate and volume. Process...
The processing of data streams plays a central role in emerging applications such as pervasive compu...
Current systems for data-parallel, incremental processing and view maintenance over high-rate stream...
Microsoft StreamInsight (StreamInsight, for brevity) is a platform for developing and deploying stre...
As users of “big data” applications expect fresh results, we witness a new breed of stream processin...
International audienceWe are now witnessing an unprecedented growth of data that needs to be process...
There are many academic and commercial stream processing engines (SPEs) today, each of them with its...
Under the pressure of massive, exponentially increasing amounts ofheterogeneous data that are genera...
Distributed Data Stream Management Systems (DSMS) are increasingly used for the processing of high-r...
We are now witnessing an unprecedented growth of data that needs to be processed at always increasin...
First-generation streaming systems did not pay much attention to state management via ACID transacti...
The need for scalable and efficient stream analysis has led to the development of many open-source s...
As users of “big data ” applications expect fresh results, we witness a new breed of stream processi...
The ability to process large volumes of data on the fly, as soon as they become available, is a fund...
As users of “big data ” applications expect fresh results, we witness a new breed of stream pro-cess...
Present-day computing systems have to deal with a continuous growth of data rate and volume. Process...
The processing of data streams plays a central role in emerging applications such as pervasive compu...
Current systems for data-parallel, incremental processing and view maintenance over high-rate stream...
Microsoft StreamInsight (StreamInsight, for brevity) is a platform for developing and deploying stre...
As users of “big data” applications expect fresh results, we witness a new breed of stream processin...
International audienceWe are now witnessing an unprecedented growth of data that needs to be process...
There are many academic and commercial stream processing engines (SPEs) today, each of them with its...
Under the pressure of massive, exponentially increasing amounts ofheterogeneous data that are genera...
Distributed Data Stream Management Systems (DSMS) are increasingly used for the processing of high-r...
We are now witnessing an unprecedented growth of data that needs to be processed at always increasin...