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How to Win a Hot Dog Eating Contest: Distributed Incremental View Maintenance with Batch Updates

Related publications (32)

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

Panagiotis Sioulas

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 ...

EPFL2023

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

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

Proximity Operators of Discrete Information Divergences

Mireille El Gheche, Giovanni Chierchia

While phi-divergences have been extensively studied in convex analysis, their use in optimization problems often remains challenging. In this regard, one of the main shortcomings of existing methods is that the minimization of phi-divergences is usually pe ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Jumping the ORDER BY Barrier in Large-Scale Pattern Matching

Daniel Lupei

Event-series pattern matching is a major component of large-scale data analytics pipelines enabling a wide range of system diagnostics tasks. A precursor to pattern matching is an expensive ``shuffle the world'' stage wherein data are ordered by time and s ...

2017

Interleaving with Coroutines: A Practical Approach for Robust Index Joins

Anastasia Ailamaki, Georgios Psaropoulos

Index join performance is determined by the efficiency of the lookup operation on the involved index. Although database indexes are highly optimized to leverage processor caches, main memory accesses inevitably increase lookup runtime when the index outsiz ...

VLDB Endowment Inc.2017

Efficient Incremental Data Analysis

Milos Nikolic

Many data-intensive applications require real-time analytics over streaming data. In a growing number of domains -- sensor network monitoring, social web applications, clickstream analysis, high-frequency algorithmic trading, and fraud detections to name a ...

EPFL2016

From Massive Parallelization to Quantum Computing: Seven Novel Approaches to Query Optimization

Immanuel Trummer

The goal of query optimization is to map a declarative query (describing data to generate) to a query plan (describing how to generate the data) with optimal execution cost. Query optimization is required to support declarative query interfaces. It is a co ...

EPFL2016

Parallelizing Query Optimization on Shared-Nothing Architectures

Christoph Koch, Immanuel Trummer

Data processing systems offer an ever increasing degree of parallelism on the levels of cores, CPUs, and processing nodes. Query optimization must exploit high degrees of parallelism in order not to gradually become the bottleneck of query evaluation. We s ...

Assoc Computing Machinery2016