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ALEX: An Updatable Adaptive Learned Index

Database administrators construct secondary indexes on data tables to accelerate query processing in relational database management systems (RDBMSs). These indexes are built on top of the most frequently queried columns according to the data …

Turbocharging Geospatial Visualization Dashboards via a Materialized Sampling Cube Approach

—In this paper, we present a middleware framework that runs on top of a SQL data system with the purpose of increasing the interactivity of geospatial visualization dashboards. The proposed system adopts a sampling cube approach that stores …

Building Microscopic Road Network Traffic Simulators in Apache Spark

Road network traffic data has been widely studied by researchers and practitioners in different areas such as urban planning, traffic prediction and spatial-temporal databases. For instance, researchers use such data to evaluate the impact of road …

Designing Succinct Secondary Indexing Mechanism by Exploiting Column Correlations

Database administrators construct secondary indexes on data tables to accelerate query processing in relational database management systems (RDBMSs). These indexes are built on top of the most frequently queried columns according to the data …

GeoSparkViz: a scalable geospatial data visualization framework in the Apache Spark ecosystem

Data Visualization allows users to summarize, analyze and reason about data. A map visualization tool frst loads the designated geospatial data, processes the data and then applies the map visualization efect. Guaranteeing detailed and accurate …

Indexing the Pickup and Drop-Off Locations of NYC Taxi Trips in PostgreSQL - Lessons from the Road

In this paper, we present our experience in indexing the dropoff and pick-up locations of taxi trips in New York City. The paper presents a comprehensive experimental analysis of classic and state-ofthe-art spatial database indexing schemes. The …

Two Birds, One Stone: A Fast, yet Lightweight, Indexing Scheme for Modern Database Systems

Classic database indexes (e.g., B+-Tree), though speed up queries, suffer from two main drawbacks: (1) An index usually yields 5% to 15% additional storage overhead which results in non-ignorable dollar cost in big data scenarios especially when …