The Design of Stream Database Engine in Concurrent Environment

Gorawski, Marcin; Chrószcz, Aleksander

doi:10.1007/978-3-642-05151-7_21

Cited by 3 publications

(1 citation statement)

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“…A Data stream [8,[12][13][14] can be defined as an infinite sequence of tuples with unique timestamps and attributes carrying information describing various phenomena at subsequent moments of time. Stream Processing Systems usually do not provide any storage operation in their work flow, since they are designed to produce answers immediately as new data arrive.…”

Section: Data Stream Storagementioning

confidence: 99%

Research and Analysis of the Stream Materialized Aggregate List

Gorawski

Pasterak

2015

IFIP Advances in Information and Communication Technology

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Abstract. The problem of low-latency processing of large amounts of data acquired in continuously changing environment has led to the genesis of Stream Processing Systems (SPS). However, sometimes it is crucial to process both historical (archived) and current data, in order to obtain full knowledge about various phenomena. This is achieved in a Stream Data Warehouse (StrDW), where analytical operations on both historical and current data streams are performed. In this paper we focus on Stream Materialized Aggregate List (StrMAL) -a stream repository tier of StrDW. As a motivating example, the liquefied petrol storage and distribution system, containing continuous telemetric data acquisition, transmission and storage, will be presented as possible application for Stream Materialized Aggregate List.

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Section: Data Stream Storagementioning

confidence: 99%