Squall is a scalable online query engine that runs complex analytics in a cluster using skew-resilient, adaptive operators. Squall builds on state-of-the-art partitioning schemes and local algorithms, including some of our own. This paper presents the overview of Squall, including some novel join operators. The paper also presents lessons learned over the five years of working on this system, and outlines the plan for the proposed system demonstration
textabstractWe describe a system that incrementally translates SPARQL queries to Pig Latin and execu...
Big data analytics often involves complex join queries over two or more tables. Such join process...
Conventional data warehouses employ the query-at-a-time model, which maps each query to a distinct p...
Squall is a scalable online query engine that runs complex analytics in a cluster using skew-resilie...
With the advent of emerging technologies and the Internet of Things, the importance of online data a...
Current cluster computing frameworks suffer from load imbalance and limited parallelism due to skewe...
We describe a system that incrementally translates SPARQL queries to Pig Latin and executes them on ...
: We provide a new family of join algorithms, called ripple joins, for online processing of complex,...
In the last decade, the world wide web has grown from being a platform where users passively viewed ...
This thesis targets the growing area of interactive data analytics engines. It builds upon a system ...
The ever increasing diversity of data analytics and AI applications has had a tremendous impact on t...
We present a new family of join algorithms, called ripple joins, for online processing of multi-tabl...
International audienceThe current cloud landscape is getting populated with many applications that a...
This paper introduces Quill (stands for a quadrillion tuples per day ), a li...
Distributed interactive analytics engines (Druid, Redshift, Pinot) need to achieve low query latenc...
textabstractWe describe a system that incrementally translates SPARQL queries to Pig Latin and execu...
Big data analytics often involves complex join queries over two or more tables. Such join process...
Conventional data warehouses employ the query-at-a-time model, which maps each query to a distinct p...
Squall is a scalable online query engine that runs complex analytics in a cluster using skew-resilie...
With the advent of emerging technologies and the Internet of Things, the importance of online data a...
Current cluster computing frameworks suffer from load imbalance and limited parallelism due to skewe...
We describe a system that incrementally translates SPARQL queries to Pig Latin and executes them on ...
: We provide a new family of join algorithms, called ripple joins, for online processing of complex,...
In the last decade, the world wide web has grown from being a platform where users passively viewed ...
This thesis targets the growing area of interactive data analytics engines. It builds upon a system ...
The ever increasing diversity of data analytics and AI applications has had a tremendous impact on t...
We present a new family of join algorithms, called ripple joins, for online processing of multi-tabl...
International audienceThe current cloud landscape is getting populated with many applications that a...
This paper introduces Quill (stands for a quadrillion tuples per day ), a li...
Distributed interactive analytics engines (Druid, Redshift, Pinot) need to achieve low query latenc...
textabstractWe describe a system that incrementally translates SPARQL queries to Pig Latin and execu...
Big data analytics often involves complex join queries over two or more tables. Such join process...
Conventional data warehouses employ the query-at-a-time model, which maps each query to a distinct p...