On producing join results early
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Hash-Merge Join: A Non-blocking Join Algorithm for Producing Fast and Early Join Results
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
IEEE Transactions on Knowledge and Data Engineering
RPJ: producing fast join results on streams through rate-based optimization
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
A disk-based join with probabilistic guarantees
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
NSJ: an efficient non-blocking spatial join algorithm
GIS '06 Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems
ACM Transactions on Database Systems (TODS)
ACM Transactions on Database Systems (TODS)
Ad-hoc distributed spatial joins on mobile devices
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Behavioral simulations in MapReduce
Proceedings of the VLDB Endowment
Speeding up large-scale point-in-polygon test based spatial join on GPUs
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data
TOUCH: in-memory spatial join by hierarchical data-oriented partitioning
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Driver input selection for main-memory multi-way joins
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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Interest in incremental and adaptive query processing has led to the investigation of equijoin evaluation algorithms that are non-blocking. This investigation has yielded a number of algorithms, including the symmetric hash join, the XJoin, the Ripple Join, and their variants. However, to our knowledge no one has proposed a non-blocking spatial join algorithm. In this paper, we propose a parallel non-blocking spatial join algorithm that uses duplicate avoidance rather than duplicate elimination. Results from a prototype implementation in a commercial parallel object-relational DBMS show that it generates answer tuples steadily even in the presence of memory overflow, and that its rate of producing answer tuples scales with the number of processors. Also, when allowed to run to completion, its performance is comparable with the state-of-the-art blocking parallel spatial join algorithm.