54 citations · 91 across the 12 of their papers we have counts for
12 papers
VIP Hashing -- Adapting to Skew in Popularity of Data on the Fly (extended version)
Aarati Kakaraparthy, Jignesh M. Patel, Brian P. Kroth +1
All data is not equally popular. Often, some portion of data is more frequently accessed than the rest, which causes a skew in popularity of the data items. Adapting to this skew c…
To pipeline or not to pipeline, that is the question
Harshad Deshmukh, Bruhathi Sundarmurthy, Jignesh M. Patel
In designing query processing primitives, a crucial design choice is the method for data transfer between two operators in a query plan. As we were considering this critical design…
Scaling-Up In-Memory Datalog Processing: Observations and Techniques
Zhiwei Fan, Jianqiao Zhu, Zuyu Zhang +3
Recursive query processing has experienced a recent resurgence, as a result of its use in many modern application domains, including data integration, graph analytics, security, pr…
ROSA: R Optimizations with Static Analysis
Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel +1
R is a popular language and programming environment for data scientists. It is increasingly co-packaged with both relational and Hadoop-based data platforms and can often be the mo…
Tuple-oriented Compression for Large-scale Mini-batch Stochastic Gradient Descent
Fengan Li, Lingjiao Chen, Yijing Zeng +4
Data compression is a popular technique for improving the efficiency of data processing workloads such as SQL queries and more recently, machine learning (ML) with classical batch…
Towards Linear Algebra over Normalized Data
Lingjiao Chen, Arun Kumar, Jeffrey Naughton +1
Providing machine learning (ML) over relational data is a mainstream requirement for data analytics systems. While almost all the ML tools require the input data to be presented as…