Concept
Query language
Related publications (143)
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 ...
ACM2023Efficient Concurrent Analytical Query Processing using Data and Workload-conscious Sharing
Analytical workloads are evolving as the number of users surges and applications that submit queries in batches become popular. However, traditional analytical databases that optimize-then-execute each query individually struggle to provide timely response ...
EPFL2023Knowledge-Aware Cross-Modal Text-Image Retrieval for Remote Sensing Images
Devis Tuia, Christel Marie Tartini-Chappuis, Li Mi, Siran Li
Image-based retrieval in large Earth observation archives is difficult, because one needs to navigate across thousands of candidate matches only with the proposition image as a guide. By using text as a query language, the retrieval system gains in usabili ...
2022The power of adaptivity in source identification with time queries on the path
Patrick Thiran, Gergely Odor, Victor Cyril L Lecomte
We study the problem of identifying the source of a stochastic diffusion process spreading on a graph based on the arrival times of the diffusion at a few queried nodes. In a graph , an unknown source node is drawn uniformly at random, ...
2022Efficient and Effective Multi-Modal Queries Through Heterogeneous Network Embedding
Karl Aberer, Thanh Trung Huynh, Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Chi Thang Duong
The heterogeneity of today's Web sources requires information retrieval (IR) systems to handle multi-modal queries. Such queries define a user's information needs by different data modalities, such as keywords, hashtags, user profiles, and other media. Rec ...
IEEE COMPUTER SOC2022Efficient 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 ...
IEEE2022Efficient 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 ...
2022Sampling-Based AQP in Modern Analytical Engines
Anastasia Ailamaki, Viktor Sanca
As the data volume grows, reducing the query execution times remains an elusive goal. While approximate query processing (AQP) techniques present a principled method to trade off accuracy for faster queries in analytics, the sample creation is often consid ...
ACM2022Propagation on Multi-relational Graphs for Node Regression
Recent years have witnessed a rise in real-world data captured with rich structural information that can be conveniently depicted by multi-relational graphs. While inference of continuous node features across a simple graph is rather under-studied by the c ...
2021Edit Based Grading of SQL Queries
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