TIGER: Training Inductive Graph Neural Network for Large-scale Knowledge Graph Reasoning
Knowledge Graph (KG) Reasoning plays a vital role in various applications by predicting
missing facts from existing knowledge. Inductive KG reasoning approaches based on Graph …
missing facts from existing knowledge. Inductive KG reasoning approaches based on Graph …
Oasis: An Optimal Disjoint Segmented Learned Range Filter
The learning-enhanced data structure has inspired the development of the range filter,
bringing significantly better false positive rate (FPR) than traditional non-learned range …
bringing significantly better false positive rate (FPR) than traditional non-learned range …
Structural Designs Meet Optimality: Exploring Optimized LSM-tree Structures in A Colossal Configuration Space
Mainstream LSM-tree-based key-value stores face challenges in optimizing performance for
point lookup, range lookup, and update operations concurrently due to their constrained …
point lookup, range lookup, and update operations concurrently due to their constrained …
GRF: A Global Range Filter for LSM-Trees with Shape Encoding
Log-structured merge-trees (LSM-trees) are widely used in key-value stores because of its
excellent write performance. To reduce LSM-tree's read amplification due to overlapping …
excellent write performance. To reduce LSM-tree's read amplification due to overlapping …
CAMAL: Optimizing LSM-trees via Active Learning
We use machine learning to optimize LSM-tree structure, aiming to reduce the cost of
processing various read/write operations. We introduce a new approach CAMAL, which …
processing various read/write operations. We introduce a new approach CAMAL, which …
Can Modern LLMs Tune and Configure LSM-based Key-Value Stores?
Log-Structured-Merge tree-based Key-Value Stores (LSM-KVSs) are important data storage
building blocks in modern IT infrastructure. However, tuning their performance involves …
building blocks in modern IT infrastructure. However, tuning their performance involves …
Advocating for Key-Value Stores with Workload Pattern Aware Dynamic Compaction
In real life, the ratio of write and read operations of key-value (KV) store workloads usually
changes over time. In this paper, we present a Dynamic wOrkload Pattern Aware LSM …
changes over time. In this paper, we present a Dynamic wOrkload Pattern Aware LSM …
Zero-Indexing Internet Search Augmented Generation for Large Language Models
G He, Z Dai, J Zhu, B Zhao, C Li, Y Peng… - arXiv preprint arXiv …, 2024 - arxiv.org
Retrieval augmented generation has emerged as an effective method to enhance large
language model performance. This approach typically relies on an internal retrieval module …
language model performance. This approach typically relies on an internal retrieval module …
Benchmarking Learned and LSM Indexes for Data Sortedness
Database systems use indexes on frequently accessed attributes to accelerate query and
transaction processing. This requires paying the cost of maintaining and updating those …
transaction processing. This requires paying the cost of maintaining and updating those …
Dynamically tuning LSM tree based databases
S Sharma - 2024 - search.proquest.com
Abstract Log-Structured Merge (LSM) trees are a popular choice of data structure for key-
value database systems due to their high ingestion rate and fast reads. They achieve this by …
value database systems due to their high ingestion rate and fast reads. They achieve this by …