Publications related to Query plan

LAQy: Efficient and Reusable Query Approximations via Lazy Sampling

Anastasia Ailamaki, Periklis Chrysogelos, Viktor Sanca

Modern analytical engines rely on Approximate Query Processing (AQP) to provide faster response times than the hardware allows for exact query answering. However, existing AQP methods impose steep performance penalties as workload unpredictability increase ...

2023

Using Cloud Functions as Accelerator for Elastic Data Analytics

Anastasia Ailamaki, Haoqiong Bian, Tiannan Sha

Cloud function (CF) services, such as AWS Lambda, have been applied as the new computing infrastructure in implementing analytical query engines. For bursty and sparse workloads, CF-based query engine is more elastic than the traditional query engines runn ...

ACM2023

Aggregation and Exploration of High-Dimensional Data Using the Sudokube Data Cube Engine

Christoph Koch, Peter Lindner, Zhekai Jiang, Sachin Basil John

We present Sudokube, a novel system that supports interactive speed querying on high-dimensional data using partially materialized data cubes. Given a storage budget, it judiciously chooses what projections to precompute and materialize during cube constru ...

Association for Computing Machinery2023

Efficient Massively Parallel Join Optimization for Large Queries

Anastasia Ailamaki, Bikash Chandra, Srinivas Karthik Venkatesh, Riccardo Mancini, Vasileios Mageirakos

Modern data analytical workloads often need to run queries over a large number of tables. An optimal query plan for such queries is crucial for being able to run these queries within acceptable time bounds. However, with queries involving many tables, find ...

2022

Efficient GPU-accelerated Join Optimization for Complex Queries

Anastasia Ailamaki, Bikash Chandra, Srinivas Karthik Venkatesh, Riccardo Mancini, Vasileios Mageirakos

Analytics on modern data analytic and data warehouse systems often need to run large complex queries on increasingly complex database schemas. A lot of progress has been made on executing such complex queries using techniques like scale out query processin ...

IEEE2022

Pixels: An Efficient Column Store for Cloud Data Lakes

Anastasia Ailamaki, Haoqiong Bian

To benefit from the cloud’s higher elasticity and price-efficiency, most modern data-lake engines support S3-like cloud object storage (COS) services as their optional or preferred underlying storage. Meanwhile, the widespread column stores, such as Parque ...

IEEE2022

Scalable Multi-Query Execution using Reinforcement Learning

Anastasia Ailamaki, Panagiotis Sioulas

The growing demand for data-intensive decision support and the migration to multi-tenant infrastructures put databases under the stress of high analytical query load. The requirement for high throughput contradicts the traditional design of query-at-a-time ...

Association for Computing Machinery2021

Edit Based Grading of SQL Queries

Bikash Chandra

Grading student SQL queries manually is a tedious and error-prone process. Earlier work on testing correctness of student SQL queries, such as the XData system, can be used to test the correctness of a student query. However, in case a student query is fou ...

ASSOC COMPUTING MACHINERY2021

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Query plan

LAQy: Efficient and Reusable Query Approximations via Lazy Sampling

Efficient Concurrent Analytical Query Processing using Data and Workload-conscious Sharing

Using Cloud Functions as Accelerator for Elastic Data Analytics

Aggregation and Exploration of High-Dimensional Data Using the Sudokube Data Cube Engine

Efficient Massively Parallel Join Optimization for Large Queries

Efficient GPU-accelerated Join Optimization for Complex Queries

Pixels: An Efficient Column Store for Cloud Data Lakes

Sampling-Based AQP in Modern Analytical Engines

Scalable Multi-Query Execution using Reinforcement Learning

Edit Based Grading of SQL Queries

Graph Chatbot

Chat with Graph Search

Efficient GPU-accelerated Join Optimization for Complex Queries

LAQy: Efficient and Reusable Query Approximations via Lazy Sampling

Efficient Concurrent Analytical Query Processing using Data and Workload-conscious Sharing

Efficient Massively Parallel Join Optimization for Large Queries

Pixels: An Efficient Column Store for Cloud Data Lakes

Scalable Multi-Query Execution using Reinforcement Learning

Edit Based Grading of SQL Queries

Sampling-Based AQP in Modern Analytical Engines

Aggregation and Exploration of High-Dimensional Data Using the Sudokube Data Cube Engine

Using Cloud Functions as Accelerator for Elastic Data Analytics