In this paper we present HATCH, a novel hash join engine. We follow a new design point which enables us to effectively cache the hash table entries in fast BRAM resources, meanwhile supporting collision resolution in hardware. HATCH enables us to have the best of two worlds: (i) to use the full capacity of the DDR memory to store complete hash tables, and (ii) by employing a cache, to exploit the high access speed of BRAMs. We demonstrate the usefulness of our approach by running hash join operations from 5 TPCH benchmark queries and report speedups up to 2.8x over a pipeline-optimized baseline.The research leading to these results has received funding from the European Unions Seventh Framework Programme (FP7/2007-2013), for Advanced Analy...
The architectural changes introduced with multicore CPUs have triggered a redesign of main-memory jo...
Until recently, the use of graphics processing units (GPUs) for query processing was limited by the ...
With the increasing amount of information stored, there is a need for efficient database algorithms....
In this paper we present HATCH, a novel hash join engine. We follow a new design point which enables...
Extracting valuable information from the rapidly growing field of Big Data faces serious performance...
The multi-way hash join is one of the commonly used and time-consuming database operations. Many alg...
We present new hash tables for joins, and a hash join based on them, that consumes far less memory a...
Previous work [1] has claimed that the best performing implementation of in-memory hash joins is bas...
FPGA-based data processing is becoming increasingly relevant in data centers, as the transformation ...
Hashing is one of the fundamental techniques used to implement query processing operators such as gr...
The hash join algorithm family is one of the leading techniques for equi-join performance evaluation...
In the past decade, the exponential growth in commodity CPUs speed has far outpaced advances in memo...
As one of the most important operations in relational databases, the join is data-intensive and time...
We present an efficient, high-throughput and scalable hardware design for accelerating the merge pha...
Relational database systems provide various services and applications with an efficient means for st...
The architectural changes introduced with multicore CPUs have triggered a redesign of main-memory jo...
Until recently, the use of graphics processing units (GPUs) for query processing was limited by the ...
With the increasing amount of information stored, there is a need for efficient database algorithms....
In this paper we present HATCH, a novel hash join engine. We follow a new design point which enables...
Extracting valuable information from the rapidly growing field of Big Data faces serious performance...
The multi-way hash join is one of the commonly used and time-consuming database operations. Many alg...
We present new hash tables for joins, and a hash join based on them, that consumes far less memory a...
Previous work [1] has claimed that the best performing implementation of in-memory hash joins is bas...
FPGA-based data processing is becoming increasingly relevant in data centers, as the transformation ...
Hashing is one of the fundamental techniques used to implement query processing operators such as gr...
The hash join algorithm family is one of the leading techniques for equi-join performance evaluation...
In the past decade, the exponential growth in commodity CPUs speed has far outpaced advances in memo...
As one of the most important operations in relational databases, the join is data-intensive and time...
We present an efficient, high-throughput and scalable hardware design for accelerating the merge pha...
Relational database systems provide various services and applications with an efficient means for st...
The architectural changes introduced with multicore CPUs have triggered a redesign of main-memory jo...
Until recently, the use of graphics processing units (GPUs) for query processing was limited by the ...
With the increasing amount of information stored, there is a need for efficient database algorithms....