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Robert Binna

dblp:74/10151 · DBLP profile ↗
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2ranked-venue papers
2as first author
1since 2021 · last 2022
0000-0003-1062-8419ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 2 · 2 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
2 papers
Indexing and storage engines · 96% Query processing and optimization · 4%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Indexing and storage engines
in-memory index
0.922022
Height Optimized Tries · ACM Trans. Database Syst. 2022
HOT: A Height Optimized Trie Index for Main-Memory Database Systems · SIGMOD Conference 2018
Indexing and storage engines › string indexing
trie index
0.922022
Height Optimized Tries · ACM Trans. Database Syst. 2022
HOT: A Height Optimized Trie Index for Main-Memory Database Systems · SIGMOD Conference 2018
Indexing and storage engines › in-memory index
cache-efficient index
0.612022
Height Optimized Tries · ACM Trans. Database Syst. 2022

Methods — techniques the papers use, named apart from their topics

SIMD · 0.9lightweight compression · 0.6cache-conscious layout · 0.3
YearPublicationVenuePosition
2022 Height Optimized Tries
abstract
We present the Height Optimized Trie (HOT), a fast and space-efficient in-memory index structure. The core algorithmic idea of HOT is to dynamically vary the number of bits considered at each node, which enables a consistently high fanout and thereby good cache efficiency. For a fixed maximum node fanout, the overall tree height is minimal and its structure is deterministically defined. Multiple carefully engineered node implementations using SIMD instructions or lightweight compression schemes provide compactness and fast search and optimize HOT structures for different usage scenarios. Our experiments, which use a wide variety of workloads and data sets, show that HOT outperforms other state-of-the-art index structures for string keys both in terms of search performance and memory footprint, while being competitive for integer keys.
Robert Binna, Eva Zangerle, Martin Pichl, Günther Specht, Viktor Leis
ACM Trans. Database Syst.1
2018 HOT: A Height Optimized Trie Index for Main-Memory Database Systems
abstract
We present the Height Optimized Trie (HOT), a fast and space-efficient in-memory index structure. The core algorithmic idea of HOT is to dynamically vary the number of bits considered at each node, which enables a consistently high fanout and thereby good cache efficiency. The layout of each node is carefully engineered for compactness and fast search using SIMD instructions. Our experimental results, which use a wide variety of workloads and data sets, show that HOT outperforms other state-of-the-art index structures for string keys both in terms of search performance and memory footprint, while being competitive for integer keys. We believe that these properties make HOT highly useful as a general-purpose index structure for main-memory databases.
Robert Binna, Eva Zangerle, Martin Pichl, Günther Specht, Viktor Leis
SIGMOD Conference1