Resource-efficient shared query execution via exploiting time slackness
Shared query execution can reduce resource consumption by sharing common sub-
expressions across concurrent queries. We show that this is not always the case when …
expressions across concurrent queries. We show that this is not always the case when …
Integrating real-time and batch processing in a polystore
J Meehan, S Zdonik, S Tian, Y Tian… - 2016 IEEE High …, 2016 - ieeexplore.ieee.org
This paper describes a stream processing engine called S-Store and its role in the
BigDAWG polystore. Fundamentally, S-Store acts as a frontend processor that accepts input …
BigDAWG polystore. Fundamentally, S-Store acts as a frontend processor that accepts input …
SamzaSQL: Scalable fast data management with streaming SQL
M Pathirage, J Hyde, Y Pan… - 2016 IEEE international …, 2016 - ieeexplore.ieee.org
As the data-driven economy evolves, enterprises have come to realize a competitive
advantage in being able to act on high volume, high velocity streams of data. Technologies …
advantage in being able to act on high volume, high velocity streams of data. Technologies …
Concept-driven load shedding: Reducing size and error of voluminous and variable data streams
NR Katsipoulakis, A Labrinidis… - … Conference on Big …, 2018 - ieeexplore.ieee.org
Load shedding is a technique that aims to ameliorate the consequences of the Velocity and
the Volume of Big Data stream processing. When temporal input spikes appear, tuples are …
the Volume of Big Data stream processing. When temporal input spikes appear, tuples are …
StreamQL: a query language for processing streaming time series
L Kong, K Mamouras - Proceedings of the ACM on Programming …, 2020 - dl.acm.org
Real-time data analysis applications increasingly rely on complex streaming computations
over time-series data. We propose StreamQL, a language that facilitates the high-level …
over time-series data. We propose StreamQL, a language that facilitates the high-level …
Macrobase: Prioritizing attention in fast data
As data volumes continue to rise, manual inspection is becoming increasingly untenable. In
response, we present MacroBase, a data analytics engine that prioritizes end-user attention …
response, we present MacroBase, a data analytics engine that prioritizes end-user attention …
Scalable analytics on fast data
Today's streaming applications demand increasingly high event throughput rates and are
often subject to strict latency constraints. To allow for more complex workloads, such as …
often subject to strict latency constraints. To allow for more complex workloads, such as …
[PDF][PDF] Analytics on Fast Data: Main-Memory Database Systems versus Modern Streaming Systems.
Today's streaming applications demand increasingly high event throughput rates and are
often subject to strict latency constraints. To allow for more complex workloads, such as …
often subject to strict latency constraints. To allow for more complex workloads, such as …
Klink: Progress-aware scheduling for streaming data systems
O Farhat, K Daudjee, L Querzoni - Proceedings of the 2021 International …, 2021 - dl.acm.org
Modern stream processing engines (SPEs) process large volumes of events propagated at
high velocity through multiple queries. To improve performance, existing SPEs generally aim …
high velocity through multiple queries. To improve performance, existing SPEs generally aim …
High-performance row pattern recognition using joins
The SQL standard introduced MATCH_RECOGNIZE in 2016 for row pattern recognition.
Since then, MATCH_RECOGNIZE has been supported by several leading relation systems …
Since then, MATCH_RECOGNIZE has been supported by several leading relation systems …