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Geospark: A cluster computing framework for processing large-scale spatial data
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 …
large-scale spatial data. GeoSpark consists of three layers: Apache Spark Layer, Spatial …
Spatial data management in apache spark: the geospark perspective and beyond
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 …
core engine of Apache Spark and SparkSQL to support spatial data types, indexes, and …
Efficient parallel kNN joins for large data in MapReduce
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 …
join, which is to produce the k nearest neighbors (NN), from a dataset S, of every point in a …
Spatial join techniques
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 …
summarizing the literature and presenting each technique in its entirety, distinct components …
Sjmr: Parallelizing spatial join with mapreduce on clusters
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 …
MapReduce, it is very easy to develop scalable parallel programs to process data-intensive …
[کتاب][B] High-performance parallel database processing and grid databases
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 …
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
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 …
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
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 …
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
This paper demonstrates GEOSPARK a cluster computing framework for develo** and
processing large-scale spatial data analytics programs. GEOSPARK consists of three main …
processing large-scale spatial data analytics programs. GEOSPARK consists of three main …
TOUCH: in-memory spatial join by hierarchical data-oriented partitioning
Efficient spatial joins are pivotal for many applications and particularly important for
geographical information systems or for the simulation sciences where scientists work with …
geographical information systems or for the simulation sciences where scientists work with …