Complex event processing uses patterns to detect composite events in streams of simple
events. Typically, the events are logically partitioned by some key. For instance, the key can …

This paper is a survey of recent stream processing languages, which are programming
languages for writing applications that analyze data streams. Data streams, or continuous …

Reaction rules and event processing technologies play a key role in making business and
IT/Internet infrastructures more agile and active. While event processing is concerned with …

Streaming applications transform possibly infinite streams of data and often have both high
throughput and low latency requirements. They are comprised of operator graphs that …

This tutorial starts with a survey of optimizations for streaming applications. The survey is
organized as a catalog that introduces uniform terminology and a common categorization of …

Streaming applications process possibly infinite streams of data and often have both high
throughput and low latency requirements. They are comprised of operator graphs that …

Stream processing applications process high volume, continuous feeds from live data
sources, employ data‐in‐motion analytics to analyze these feeds, and produce near real …

Developers increasingly use streaming languages to write applications that process large
volumes of data with high throughput. Unfortunately, when picking which streaming …

Uncertain data streams can have tuples with both value and existential uncertainty. A tuple
has value uncertainty when it can assume multiple possible values. A tuple is existentially …

Stream processing applications are used to ingest, process, and analyze continuous data
streams from heterogeneous sources of live and stored data, generating streams of output …