Pixels: An Efficient Column Store for Cloud Data Lakes

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.

Non-Volatile Memory (NVM) is an emerging type of memory device that provides fast, byte-addressable, and high-capacity durable storage. NVM sits on the memory bus and allows durable data structures designs similar to the in-memory equivalent ones. Expensiv ...

Analytical engines rely on in-memory caching to avoid disk accesses and provide timely responses by keeping the most frequently accessed data in memory. Purely frequency- & time-based caching decisions, however, are a proxy of the expected query execution ...

Nowadays, transmission system operators require higher degree of observability in real-time to gain situational awareness and improve the decision-making process to guarantee a safe and reliable operation. Digitalization of energy systems allows utilities ...

Despite the rise in services generating learning analytics, there is a lack of standard models and guidelines for data integration and aggregation to inform the design choices of applications supporting learning analytics. We propose a bottom-up, user-driv ...

Despite the importance of learning analytics in digital education, there is limited support for researchers in education to generate, access, and share experimental data while complying with ethical and privacy legislation. We propose a set of related tool ...

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 ...

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 ...

Data cleaning has become an indispensable part of data analysis due to the increasing amount of dirty data. Data scientists spend most of their time preparing dirty data before it can be used for data analysis. Existing solutions that attempt to automate t ...

Timely insights lead to business growth and scientific breakthroughs but require analytical engines that cope with the ever-increasing data processing needs. Analytical engines relied on rapid CPU improvements, yet the end of Dennard scaling stopped the fr ...

Jet injection devices have been studied and developed for transdermal drug delivery to avoid the use of needles. Such contact-less devices provide several advantages such as better dose control, lateral and depth localisation, lower collateral damage than ...

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 ...

An attempt is made to translate five generic key performance indicators (KPIs) into a continuous real-time cost function in a batch order-based manufacturing environment. The challenge of controlling and optimizing resource utilization, production efficien ...

The adoption of process analytical technologies by the biopharmaceutical industry can reduce the cost of therapeutic drugs and facilitate investigation of new bioprocesses. Control of critical process parameters to retain critical product quality attribute ...

As a unified data repository, data lake plays a vital role in enterprise data management and analysis. It composes the raw files into tables that are processed in-situ by various computation engines and applications. Therefore, the read performance of the ...

Data lakes are complex ecosystems where heterogeneity prevails. Raw data of diverse formats are stored and processed, while long and expensive ETL processes are avoided. Apart from data heterogeneity, data lakes also entail hardware heterogeneity. Typical ...

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 ...

Pixels: An Efficient Column Store for Cloud Data Lakes

Chat with Graph Search

Software Support for Non-Volatile Memory (NVM) Programming

HPCache: Memory-Efficient OLAP Through Proportional Caching

State-of-the-art of data collection, analytics, and future needs of transmission utilities worldwide to account for the continuous growth of sensing data

An Integrated Approach to Learning Analytics

An End-to-End Data Pipeline for Managing Learning Analytics

Efficient GPU-accelerated Join Optimization for Complex Queries

Efficient Massively Parallel Join Optimization for Large Queries

Holistic, Efficient, and Real-time Cleaning of Heterogeneous Data

Efficient Analytical Query Processing on CPU-GPU Hardware Platforms

Laser-induced liquid micro-jets for drug delivery

Scalable Multi-Query Execution using Reinforcement Learning

Cost-Based Decision Support System: A Dynamic Cost Estimation of Key Performance Indicators in Manufacturing

Proof-of-concept analytical instrument for label-free optical deconvolution of protein species in a mixture

Columnar Storage Optimization and Caching for Data Lakes

Storage Management in Smart Data Lake

Sampling-Based AQP in Modern Analytical Engines