Publications associées à Traitement transactionnel en ligne

Efficient 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 ...

EPFL2023

Robustness Against Read Committed: A Free Transactional Lunch

Christoph Koch, Bas Ketsman

Transaction processing is a central part of most database applications. While serializability remains the gold standard for desirable transactional semantics, many database systems offer improved transaction throughput at the expense of introducing potenti ...

ASSOC COMPUTING MACHINERY2022

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

Micro-architectural Analysis of Database Workloads

Utku Sirin

Database workloads have significantly evolved in the past twenty years. Traditional database systems that are mainly used to serve Online Transactional Processing (OLTP) workloads evolved into specialized database systems that are optimized for particular ...

EPFL2021

Performance Characterization of HTAP Workloads

Anastasia Ailamaki, Utku Sirin, Sandhya Dwarkadas

Hybrid Transactional and Analytical Processing (HTAP) systems have become popular in the past decade. HTAP systems allow running transactional and analytical processing workloads on the same data and hardware. As a result, they suffer from workload interfe ...

IEEE COMPUTER SOC2021

Robustness against Read Committed for Transaction Templates

Christoph Koch, Bas Ketsman

The isolation level Multiversion Read Committed (RC), offered by many database systems, is known to trade consistency for increased transaction throughput. Sometimes, transaction workloads can be safely executed under RC obtaining the perfect isolation of ...

ASSOC COMPUTING MACHINERY2021

A system design for elastically scaling transaction processing engines in virtualized servers

Anastasia Ailamaki, Raja Appuswamy, Angelos Christos Anadiotis, Hillel Avni

Online Transaction Processing (OLTP) deployments are migrating from on-premise to cloud settings in order to exploit the elasticity of cloud infrastructure which allows them to adapt to workload variations. However, cloud adaptation comes at the cost of re ...

ASSOC COMPUTING MACHINERY2020

Adaptive partitioning and indexing for in situ query processing

Anastasia Ailamaki, Manolis Karpathiotakis, Ioannis Alagiannis, Manoussos Gavriil Athanassoulis, Matthaios Alexandros Olma

The constant flux of data and queries alike has been pushing the boundaries of data analysis systems. The increasing size of raw data files has made data loading an expensive operation that delays the data-to-insight time. To alleviate the loading cost, in ...

SPRINGER2020

Decentralized Industrial IoT Data Management Based on Blockchain and IPFS

Dimitrios Kyritsis, Jinzhi Lu, Xiaochen Zheng

The wide application of Internet of Things (IoT) has fostered the development of Industry 4.0. In manufacturing domain, Industrial IoT (IIoT) are key components of the Factories of the Future (FoF). The big IIoT data are the foundation of implementing data ...

SPRINGER INTERNATIONAL PUBLISHING AG2020

Micro-architectural Analysis of OLAP: Limitations and Opportunities

Anastasia Ailamaki, Utku Sirin

Understanding micro-architectural behavior is important for efficiently using hardware resources. Recent work has shown that in-memory online transaction processing (OLTP) systems severely underutilize their core micro-architecture resources [29]. Whereas, ...

ASSOC COMPUTING MACHINERY2020

Adaptive HTAP through Elastic Resource Scheduling

Anastasia Ailamaki, Syed Mohammad Aunn Raza, Periklis Chrysogelos, Angelos Christos Anadiotis

Modern Hybrid Transactional/Analytical Processing (HTAP) systems use an integrated data processing engine that performs analytics on fresh data, which are ingested from a transactional engine. HTAP systems typically consider data freshness at design time, ...

2020

Adaptive HTAP through Elastic Resource Scheduling

Anastasia Ailamaki, Syed Mohammad Aunn Raza, Periklis Chrysogelos, Angelos Christos Anadiotis

Modern Hybrid Transactional/Analytical Processing (HTAP) systems use an integrated data processing engine that performs analytics on fresh data, which are ingested from a transactional engine. HTAP systems typically consider data freshness at design time, ...

ASSOC COMPUTING MACHINERY2020

Efficient Online Processing for Advanced Analytics

Mohamed Elsayed Mohamed Ahmed El Seidy

With the advent of emerging technologies and the Internet of Things, the importance of online data analytics has become more pronounced. Businesses and companies are adopting approaches that provide responsive analytics to stay competitive in the global ma ...

EPFL2017

Program Analysis and Compilation Techniques for Speeding up Transactional Database Workloads

Mohammad Dashti Rahmat Abadi

There is a trend towards increased specialization of data management software for performance reasons. The improved performance not only leads to a more efficient usage of the underlying hardware and cuts the operation costs of the system, but also is a ga ...

EPFL2017

Compilation Techniques for Incremental Collection Processing

Daniel Lupei

Many map-reduce frameworks as well as NoSQL systems rely on collection programming as their interface of choice due to its rich semantics along with an easily parallelizable set of primitives. Unfortunately, the potential of collection programming is not ...

EPFL2017

Scaling Up Concurrent Analytical Workloads on Multi-Core Servers

Iraklis Psaroudakis

Today, an ever-increasing number of researchers, businesses, and data scientists collect and analyze massive amounts of data in database systems. The database system needs to process the resulting highly concurrent analytical workloads by exploiting modern ...

EPFL2016

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

Characterization of the Impact of Hardware Islands on OLTP

Anastasia Ailamaki, Miguel Sérgio De Oliveira Branco, Pinar Tözün, Danica Porobic, Ippokratis Pandis

Modern hardware is abundantly parallel and increasingly heterogeneous. The numerous processing cores have non-uniform access latencies to the main memory and processor caches, which causes variability in the communication costs. Unfortunately, database sys ...

Springer Verlag2016

Micro-architectural Analysis of In-memory OLTP

Anastasia Ailamaki, Pinar Tözün, Danica Porobic, Utku Sirin

Micro-architectural behavior of traditional disk-based online transaction processing (OLTP) systems has been investigated extensively over the past couple of decades. Results show that traditional OLTP mostly under-utilize the available micro-architectural ...

2016

Reactive and Proactive Sharing Across Concurrent Analytical Queries

Anastasia Ailamaki, Manoussos Gavriil Athanassoulis, Iraklis Psaroudakis, Matthaios Alexandros Olma

Today an ever increasing amount of data is collected and analyzed by researchers, businesses, and scientists in data warehouses (DW). In addition to the data size, the number of users and applications querying data grows exponentially. The increasing concu ...

2014