The case for learned index structures
Indexes are models: a\btree-Index can be seen as a model to map a key to the position of a
record within a sorted array, a Hash-Index as a model to map a key to a position of a record …
record within a sorted array, a Hash-Index as a model to map a key to a position of a record …
A blockchain-based integrated document management framework for construction applications
Document management systems in AEC projects manage important project documents such
as schedules, RFIs, and change orders. Hence, security concerns in document management …
as schedules, RFIs, and change orders. Hence, security concerns in document management …
Fusing similarity models with markov chains for sparse sequential recommendation
Predicting personalized sequential behavior is a key task for recommender systems. In order
to predict user actions such as the next product to purchase, movie to watch, or place to visit …
to predict user actions such as the next product to purchase, movie to watch, or place to visit …
ALEX: an updatable adaptive learned index
Recent work on" learned indexes" has changed the way we look at the decades-old field of
DBMS indexing. The key idea is that indexes can be thought of as" models" that predict the …
DBMS indexing. The key idea is that indexes can be thought of as" models" that predict the …
Recipe: Converting concurrent dram indexes to persistent-memory indexes
We present Recipe, a principled approach for converting concurrent DRAM indexes into
crash-consistent indexes for persistent memory (PM). The main insight behind Recipe is that …
crash-consistent indexes for persistent memory (PM). The main insight behind Recipe is that …
Data locality in high performance computing, big data, and converged systems: An analysis of the cutting edge and a future system architecture
Big data has revolutionized science and technology leading to the transformation of our
societies. High-performance computing (HPC) provides the necessary computational power …
societies. High-performance computing (HPC) provides the necessary computational power …
In-memory big data management and processing: A survey
Growing main memory capacity has fueled the development of in-memory big data
management and processing. By eliminating disk I/O bottleneck, it is now possible to support …
management and processing. By eliminating disk I/O bottleneck, it is now possible to support …
RadixSpline: a single-pass learned index
Recent research has shown that learned models can outperform state-of-the-art index
structures in size and lookup performance. While this is a very promising result, existing …
structures in size and lookup performance. While this is a very promising result, existing …
Simba: Efficient in-memory spatial analytics
Large spatial data becomes ubiquitous. As a result, it is critical to provide fast, scalable, and
high-throughput spatial queries and analytics for numerous applications in location-based …
high-throughput spatial queries and analytics for numerous applications in location-based …
PACTree: A high performance persistent range index using PAC guidelines
Non-Volatile Memory (NVM), which provides relatively fast and byte-addressable
persistence, is now commercially available. However, we cannot equate a real NVM with a …
persistence, is now commercially available. However, we cannot equate a real NVM with a …