Improving distance-join query processing with voronoi-diagram based partitioning in spatialhadoop
SpatialHadoop is an extended MapReduce framework supporting global indexing
techniques that partition spatial datasets across several machines and improve spatial query …
techniques that partition spatial datasets across several machines and improve spatial query …
Efficient distance join query processing in distributed spatial data management systems
Due to the ubiquitous use of spatial data applications and the large amounts of such data
these applications use, the processing of large-scale distance joins in distributed systems is …
these applications use, the processing of large-scale distance joins in distributed systems is …
Efficient distributed algorithms for distance join queries in spark-based spatial analytics systems
ABSTRACT Apache Sedona (formerly GeoSpark) is a new in-memory cluster computing
system for processing large-scale spatial data, which extends the core of Apache Spark to …
system for processing large-scale spatial data, which extends the core of Apache Spark to …
Efficient processing of all-k-nearest-neighbor queries in the MapReduce programming framework
Numerous modern applications, from social networking to astronomy, need efficient
answering of queries on spatial data. One such query is the All k Nearest-Neighbor Query …
answering of queries on spatial data. One such query is the All k Nearest-Neighbor Query …
Efficient query processing on large spatial databases: a performance study
Processing of spatial queries has been studied extensively in the literature. In most cases, it
is accomplished by indexing spatial data using spatial access methods. Spatial indexes …
is accomplished by indexing spatial data using spatial access methods. Spatial indexes …
[HTML][HTML] Classic distance join queries using compact data structures
Abstract Distance-based Join Queries (DJQs) have multiple applications in spatial
databases, Geographic Information Systems, and other areas. The K Closest Pairs Query …
databases, Geographic Information Systems, and other areas. The K Closest Pairs Query …
A partitioning gpu-based algorithm for processing the k nearest-neighbor query
The k Nearest-Neighbor (k-NN) query is a common spatial query that appears in several big
data applications. Typically, GPU devices have much larger numbers of processing cores …
data applications. Typically, GPU devices have much larger numbers of processing cores …
Efficient large-scale distance-based join queries in spatialhadoop
Abstract Efficient processing of Distance-Based Join Queries (DBJQs) in spatial databases
is of paramount importance in many application domains. The most representative and …
is of paramount importance in many application domains. The most representative and …
[PDF][PDF] In-memory k Nearest Neighbor GPU-based Query Processing.
The k Nearest Neighbor (k-NN) algorithm is widely used for classification in several
application domains (medicine, economy, entertainment, etc.). Let a group of query points …
application domains (medicine, economy, entertainment, etc.). Let a group of query points …
A comparison of distributed spatial data management systems for processing distance join queries
Due to the ubiquitous use of spatial data applications and the large amounts of spatial data
that these applications generate, the processing of large-scale distance joins in distributed …
that these applications generate, the processing of large-scale distance joins in distributed …