Publications by Matthaios Alexandros Olma

Adaptive partitioning and indexing for in situ query processing

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

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

Taster: Self-Tuning, Elastic and Online Approximate Query Processing

Anastasia Ailamaki, Matthaios Alexandros Olma, Raja Appuswamy, Odysseas Papapetrou

Current Approximate Query Processing (AQP) engines are far from silver-bullet solutions, as they adopt several static design decisions that target specific workloads and deployment scenarios. Offline AQP engines target deployments with large storage budget ...

IEEE2019

Timely and cost-efficient data exploration through adaptive tuning

Matthaios Alexandros Olma

Modern applications accumulate data at an exponentially increasing rate and traditional database systems struggle to keep up. Decision support systems used in industry, rely heavily on data analysis, and require real-time responses irrespective of data siz ...

EPFL2019

BLOCK: Efficient Execution of Spatial Range Queries in Main-Memory

Anastasia Ailamaki, Farhan Tauheed, Thomas Heinis, Matthaios Alexandros Olma

The execution of spatial range queries is at the core of many applications, particularly in the simulation sciences but also in many other domains. Although main memory in desktop and supercomputers alike has grown considerably in recent years, most spatia ...

ACM New York, NY, USA2017

Slalom: Coasting Through Raw Data via Adaptive Partitioning and Indexing

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

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. Hence, recent in-situ query proce ...

VLDB Endowment2017

Alpine: Efficient In-Situ Data Exploration in the Presence of Updates

Anastasia Ailamaki, Matthaios Alexandros Olma, Antonios Anagnostou

The ever growing data collections create the need for brief explorations of the available data to extract relevant information before decision making becomes necessary. In this context of data exploration, current data analysis solutions struggle to quickl ...

ACM New York, NY, USA2017

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