Publications related to PostgreSQL

Cluster-and-Conquer: When Randomness Meets Graph Locality

K-Nearest-Neighbors (KNN) graphs are central to many emblematic data mining and machine-learning applications. Some of the most efficient KNN graph algorithms are incremental and local: they start from a random graph, which they incrementally improve by tr ...

IEEE COMPUTER SOC2021

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

A Nitride Ring Isolator

Tobias Kippenberg, Anat Siddharth, Junqiu Liu

A silicon nitride optical ring isolator is realized by spatiotemporal modulation using bulk acoustic wave stress-optical transducers. By driving three actuators with fixed relative phases, over 17 dB isolation is achieved. (C) 2020 The Author(s) ...

IEEE2020

Deciding Robustness for Lower SQL Isolation Levels

Christoph Koch, Bas Ketsman

While serializability always guarantees application correctness, lower isolation levels can be chosen to improve transaction throughput at the risk of introducing certain anomalies. A set of transactions is robust against a given isolation level if every p ...

ASSOC COMPUTING MACHINERY2020

Privacy-preserving semi-parallel logistic regression training with fully homomorphic encryption

Juan Ramón Troncoso-Pastoriza

Background Privacy-preserving computations on genomic data, and more generally on medical data, is a critical path technology for innovative, life-saving research to positively and equally impact the global population. It enables medical research algorithm ...

2020

PaRiS: Causally Consistent Transactions with Non-blocking Reads and Partial Replication

Willy Zwaenepoel, Diego Didona, Kristina Spirovska

Geo-replicated data platforms are the backbone of several large-scale online services. Transactional Causal Consistency (TCC) is an attractive consistency level for building such platforms. TCC avoids many anomalies of eventual consistency, eschews the syn ...

IEEE COMPUTER SOC2019

Monitoring distributed fragmented skylines

Odysseas Papapetrou

Distributed skyline computation is important for a wide range of domains, from distributed and web-based systems to ISP-network monitoring and distributed databases. The problem is particularly challenging in dynamic distributed settings, where the goal is ...

2018

Slalom: Coasting Through Raw Data via Adaptive Partitioning and Indexing

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

VLDB Endowment2017

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

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

Christoph Koch, Milos Nikolic, Mohammad Dashti Rahmat Abadi

In the quest for valuable information, modern big data applications continuously monitor streams of data. These applications demand low latency stream processing even when faced with high volume and velocity of incoming changes and the user’s desire to ask ...

2016

PostgreSQL

Cluster-and-Conquer: When Randomness Meets Graph Locality

Adaptive partitioning and indexing for in situ query processing

A Nitride Ring Isolator

Deciding Robustness for Lower SQL Isolation Levels

Privacy-preserving semi-parallel logistic regression training with fully homomorphic encryption

PaRiS: Causally Consistent Transactions with Non-blocking Reads and Partial Replication

Monitoring distributed fragmented skylines

Slalom: Coasting Through Raw Data via Adaptive Partitioning and Indexing

Interleaving with Coroutines: A Practical Approach for Robust Index Joins

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

Graph Chatbot

Chat with Graph Search

Monitoring distributed fragmented skylines

Interleaving with Coroutines: A Practical Approach for Robust Index Joins

Adaptive partitioning and indexing for in situ query processing

Cluster-and-Conquer: When Randomness Meets Graph Locality

Slalom: Coasting Through Raw Data via Adaptive Partitioning and Indexing

A Nitride Ring Isolator

Deciding Robustness for Lower SQL Isolation Levels

Privacy-preserving semi-parallel logistic regression training with fully homomorphic encryption

PaRiS: Causally Consistent Transactions with Non-blocking Reads and Partial Replication

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