Geospark: A cluster computing framework for processing large-scale spatial data

J Yu, J Wu, M Sarwat - … of the 23rd SIGSPATIAL international conference …, 2015‏ - dl.acm.org
This paper introduces GeoSpark an in-memory cluster computing framework for processing
large-scale spatial data. GeoSpark consists of three layers: Apache Spark Layer, Spatial …

Spatial data management in apache spark: the geospark perspective and beyond

J Yu, Z Zhang, M Sarwat - GeoInformatica, 2019‏ - Springer
The paper presents the details of designing and develo** GeoSpark, which extends the
core engine of Apache Spark and SparkSQL to support spatial data types, indexes, and …

Efficient parallel kNN joins for large data in MapReduce

C Zhang, F Li, J Jestes - … of the 15th international conference on …, 2012‏ - dl.acm.org
In data mining applications and spatial and multimedia databases, a useful tool is the k NN
join, which is to produce the k nearest neighbors (NN), from a dataset S, of every point in a …

Spatial join techniques

EH Jacox, H Samet - ACM Transactions on Database Systems (TODS), 2007‏ - dl.acm.org
A variety of techniques for performing a spatial join are reviewed. Instead of just
summarizing the literature and presenting each technique in its entirety, distinct components …

Sjmr: Parallelizing spatial join with mapreduce on clusters

S Zhang, J Han, Z Liu, K Wang… - 2009 IEEE International …, 2009‏ - ieeexplore.ieee.org
MapReduce is a widely used parallel programming model and computing platform. With
MapReduce, it is very easy to develop scalable parallel programs to process data-intensive …

[کتاب][B] High-performance parallel database processing and grid databases

D Taniar, CHC Leung, W Rahayu, S Goel - 2008‏ - books.google.com
The latest techniques and principles of parallel and grid database processing The growth in
grid databases, coupled with the utility of parallel query processing, presents an important …

Hash-merge join: A non-blocking join algorithm for producing fast and early join results

MF Mokbel, M Lu, WG Aref - Proceedings. 20th International …, 2004‏ - ieeexplore.ieee.org
We introduce the hash-merge join algorithm (HMJ, for short); a new nonblocking join
algorithm that deals with data items from remote sources via unpredictable, slow, or bursty …

Progressive merge join: A generic and non-blocking sort-based join algorithm

JP Dittrich, B Seeger, DS Taylor, P Widmayer - VLDB'02: Proceedings of …, 2002‏ - Elsevier
Publisher Summary This chapter presents a generic technique called progressive merge
join (PMJ) that eliminates the blocking behavior of sort-based join algorithms. The basic idea …

A demonstration of GeoSpark: A cluster computing framework for processing big spatial data

J Yu, J Wu, M Sarwat - 2016 IEEE 32nd International …, 2016‏ - ieeexplore.ieee.org
This paper demonstrates GEOSPARK a cluster computing framework for develo** and
processing large-scale spatial data analytics programs. GEOSPARK consists of three main …

TOUCH: in-memory spatial join by hierarchical data-oriented partitioning

S Nobari, F Tauheed, T Heinis, P Karras… - Proceedings of the …, 2013‏ - dl.acm.org
Efficient spatial joins are pivotal for many applications and particularly important for
geographical information systems or for the simulation sciences where scientists work with …