1 citations · 3 across the 6 of their papers we have counts for
4 papers · 1 filter
PyTond: Efficient Python Data Science on the Shoulders of Databases
Hesam Shahrokhi, Amirali Kaboli, Mahdi Ghorbani +1
Python data science libraries such as Pandas and NumPy have recently gained immense popularity. Although these libraries are feature-rich and easy to use, their scalability limitat…
Fine-Tuning Data Structures for Analytical Query Processing
Amir Shaikhha, Marios Kelepeshis, Mahdi Ghorbani
We introduce a framework for automatically choosing data structures to support efficient computation of analytical workloads. Our contributions are twofold. First, we introduce a n…
Building Efficient Query Engines in a High-Level Language
Amir Shaikhha, Yannis Klonatos, Christoph Koch
Abstraction without regret refers to the vision of using high-level programming languages for systems development without experiencing a negative impact on performance. A database…
Push vs. Pull-Based Loop Fusion in Query Engines
Amir Shaikhha, Mohammad Dashti, Christoph Koch
Database query engines use pull-based or push-based approaches to avoid the materialization of data across query operators. In this paper, we study these two types of query engines…