Most join algorithms can be extended to reduce wasted work when several tuples contain the same value of the join attribute. We show that separating detection of duplicates from their exploitation improves modularity and makes it easier to implement whole families ofhierarchy-exploitingjoin algorithms that avoid duplication. The technique is also used to provide an execution technique for star-like patterns of joins around a central relation. It appears to dominate Ingreslike substitution for the central relation, in both performance and ease of including in a conventional optimizer. Its performance dominates a cascade of conventional binary joins, and performance estimates are more accurate
An intention of MapReduce Sets for Replicated Join expressions analysis has to suggest criteria how ...
ABSTRACT Computing an equi-join followed by a duplicate eliminating projection is conventionally don...
Join is the most important operator in relational databases, and remains the most expensive one desp...
Most join algorithms can be extended to reduce wasted work when several tuples contain the same valu...
Evaluating the relational join is one of the central algorithmic and most well-studied problems in d...
Query optimizers that explore a search space exhaustively using transformation rules usually apply a...
Two new algorithms, "Jive-join" and "Slam-join," are proposed for computing the ...
We study algorithms for computing the equijoin of two relations in B system with a standard architec...
Parallel join algorithms have received much attention in recent years, due to the rapid development ...
In this paper, a novel multi join algorithm to join multiple relations will be introduced. The novel...
We present a simple conceptual framework to think about computing the relational join. Using this fr...
Set similarity join is an essential operation in data integration and big data analytics, that finds...
The Partitioned Based Spatial-Merge Join (PBSM) of Patel and DeWitt and the Size Separation Spatial ...
AbstractJoin is the most important and expensive operation in relational databases. The parallel joi...
Evaluating the relational join is one of the central algorithmic and most well-studied problems in d...
An intention of MapReduce Sets for Replicated Join expressions analysis has to suggest criteria how ...
ABSTRACT Computing an equi-join followed by a duplicate eliminating projection is conventionally don...
Join is the most important operator in relational databases, and remains the most expensive one desp...
Most join algorithms can be extended to reduce wasted work when several tuples contain the same valu...
Evaluating the relational join is one of the central algorithmic and most well-studied problems in d...
Query optimizers that explore a search space exhaustively using transformation rules usually apply a...
Two new algorithms, "Jive-join" and "Slam-join," are proposed for computing the ...
We study algorithms for computing the equijoin of two relations in B system with a standard architec...
Parallel join algorithms have received much attention in recent years, due to the rapid development ...
In this paper, a novel multi join algorithm to join multiple relations will be introduced. The novel...
We present a simple conceptual framework to think about computing the relational join. Using this fr...
Set similarity join is an essential operation in data integration and big data analytics, that finds...
The Partitioned Based Spatial-Merge Join (PBSM) of Patel and DeWitt and the Size Separation Spatial ...
AbstractJoin is the most important and expensive operation in relational databases. The parallel joi...
Evaluating the relational join is one of the central algorithmic and most well-studied problems in d...
An intention of MapReduce Sets for Replicated Join expressions analysis has to suggest criteria how ...
ABSTRACT Computing an equi-join followed by a duplicate eliminating projection is conventionally don...
Join is the most important operator in relational databases, and remains the most expensive one desp...