Recently, significant efforts have focused on developing novel data-processing systems to support a new class of applications that commonly require sophisticated and timely processing of high-volume data streams. Early work in stream processing has primarily focused on streamoriented languages and resource-constrained, one-pass query-processing. High availability, an increasingly important goal for virtually all data processing systems, is yet to be addressed
Present-day computing systems have to deal with a continuous growth of data rate and volume. Process...
Stream processing is a popular paradigm to process huge amounts of unbounded data, which has gained ...
Developers increasingly use streaming languages to write their data processing applications. While a...
Stream-processing systems are designed to support an emerging class of applications that require sop...
Data stream processing has gained increasing popularity in the last few years as an effective paradi...
Stream processing languages and stream processing engines have become more popular as they emerged f...
Stream processing languages and stream processing engines have become more popu-lar as they emerged ...
Stream programs represent an important class of high-performance computations. Defined by their reg...
Stream processing is a term that is used widely in the literature to describe a variety of systems. ...
Deploying an infrastructure to execute queries on distributed data streams sources requires to ident...
We present a collaborative, self-configuring high availability (HA) approach for stream processing t...
Rapid technical advances have made it possible to instrument even massive computing systems. However...
Rapid technical advances have made it possible to instrument even massive computing systems. However...
Stream processing is a term that is used widely in the literature to describe a variety of systems. ...
This paper describes our ongoing work developing the Stanford Stream Data Manager (STREAM), a system...
Present-day computing systems have to deal with a continuous growth of data rate and volume. Process...
Stream processing is a popular paradigm to process huge amounts of unbounded data, which has gained ...
Developers increasingly use streaming languages to write their data processing applications. While a...
Stream-processing systems are designed to support an emerging class of applications that require sop...
Data stream processing has gained increasing popularity in the last few years as an effective paradi...
Stream processing languages and stream processing engines have become more popular as they emerged f...
Stream processing languages and stream processing engines have become more popu-lar as they emerged ...
Stream programs represent an important class of high-performance computations. Defined by their reg...
Stream processing is a term that is used widely in the literature to describe a variety of systems. ...
Deploying an infrastructure to execute queries on distributed data streams sources requires to ident...
We present a collaborative, self-configuring high availability (HA) approach for stream processing t...
Rapid technical advances have made it possible to instrument even massive computing systems. However...
Rapid technical advances have made it possible to instrument even massive computing systems. However...
Stream processing is a term that is used widely in the literature to describe a variety of systems. ...
This paper describes our ongoing work developing the Stanford Stream Data Manager (STREAM), a system...
Present-day computing systems have to deal with a continuous growth of data rate and volume. Process...
Stream processing is a popular paradigm to process huge amounts of unbounded data, which has gained ...
Developers increasingly use streaming languages to write their data processing applications. While a...