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18 results with keyword: 'window queries over data streams'

Window Queries Over Data Streams

For example, the input stream may be split and processed through different sub-queries (such as might be needed for network-protocol simulation), and the

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2021
Incremental Evaluation of Sliding-Window Queries over Data Streams ∗

Upon receiving a negative tuple, instead of re-performing the join operation, the time- message optimization performs the following steps: (1) Removes the corresponding positive

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2021
Low-latency Estimates for Window-Aggregate Queries over Data Streams

I study the effects of varying aggressiveness in prodding (i.e. how early a system asks a window for results) on the overall result latency gains and result accuracy, using input

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2021
Processing Sliding Window Multi-Joins in Continuous Queries over Data Streams⁄

We test a possible implementation of these algorithms and show that, as expected, hash joins are faster than NLJs for performing equi-joins, and that the overall processing cost

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2021
Continuous Queries over Data Streams

In such a system, traditional one-time queries are replaced or augmented with continuous queries, and techniques such as synopsis and online data structures, approximate re- sults,

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2021
Processing Sliding Window Multi-Joins in Continuous Queries over Data Streams

In effect, the window at the top of the join order always consists of only one tuple and the join order changes in response to the origin of the incoming tuple (Table 4). This

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2021
Load Shedding using Window Aggregation Queries on Data Streams

The Novel feedback control-based load shedding scheme for data stream processing is to identify system identification to establish a dynamic model to describe a

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2020
Load Shedding for Aggregation Queries over Data Streams

(In fact, this assumption is unnecessary, as we will explain in Section 3.2.1.) Then our task is re- duced to solving the following problem: Given a data flow diagram along with a

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2022
Continuous Queries over Data Streams – Semantics and Implementation

Since queries expressed in our query language are translated into a query plan composed of operators from our stream algebra, the se- mantics of a query results from the semantics

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2021
Data Stream Management Systems

Software to process queries Software to access streams and data Data streams Meta – data DSMS Continuous queries (CQs) Data streams Stored Data... The LOFAR Instrument

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2021
*La cuisine espagnole. Summer-Fall 2013

Unless otherwise stipulated and subject to all terms indicated in the following paragraph, all applicable prices at the time of the order are the prices to be charged at the time

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2021
Mission Critical Metallics

Supply Balances Demand Supply Orders Inventory Forecast Capacity Balanced Demand Supply Inventory Orders Capacity Forecast. Strong Demand-

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2021
Mining frequent closed itemsets from a landmark window over online data streams

Muntz, Moment: Maintaining closed frequent itemsets over a stream sliding window, in: Int’l Conference on Data Mining, November 2004.

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2021
Characterizing persistent unburned islands within the Inland Northwest USA

5 Maps illustrating the proportional area of each 6 km × 6 km grid cell that is covered by ( a ) fire perimeters within the Inland Pacific Northwest from 1984 to 2014

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2020
Continuous Top-k Queries over Real-Time Web Streams

Through these experiments we compare the performance of the R 2 T S algorithm implemen- tations over the simple candidates (Simple), the lazy ordering (LazyOrder) and the

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2021
Processing nested complex sequence pattern queries over event streams

Although the results of nested CEP queries obtained from the it- erative execution strategy are correct, it produces results at a very slow rate which is attributed to

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2021
Wire-Speed Implementation of Sliding-Window Aggregate Operator over Out-of-Order Data Streams

With the proposed approach, a sliding-window query can be implemented on an FPGA as an order-agnostic operator, which can process input tuples in their arrival order without

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2021
Regular Programming Over Data Streams

The functions expressible using DReX and QREs coincide with the class of regular string transformations, which is a robust class with multiple characterizations and appealing

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2020

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