TY - GEN
T1 - Coverage-Based Caching in Cloud Data Lakes
AU - Weintraub, Grisha
AU - Gudes, Ehud
AU - Dolev, Shlomi
N1 - Publisher Copyright: © 2024 Copyright held by the owner/author(s).
PY - 2024/9/16
Y1 - 2024/9/16
N2 - Cloud data lakes are a modern approach to handling large volumes of data. They separate the compute and storage layers, making them highly scalable and cost-effective. However, query performance in cloud data lakes could be faster, and various efforts have been made to enhance it in recent years. We introduce our approach to this problem, which is based on a novel caching technique where instead of caching actual data, we cache metadata called a coverage set.
AB - Cloud data lakes are a modern approach to handling large volumes of data. They separate the compute and storage layers, making them highly scalable and cost-effective. However, query performance in cloud data lakes could be faster, and various efforts have been made to enhance it in recent years. We introduce our approach to this problem, which is based on a novel caching technique where instead of caching actual data, we cache metadata called a coverage set.
KW - caching
KW - cloud storage
KW - data lakes
UR - https://www.scopus.com/pages/publications/85206794992
U2 - 10.1145/3688351.3689165
DO - 10.1145/3688351.3689165
M3 - Conference contribution
T3 - Proceedings of the 17th ACM International Systems and Storage Conference, SYSTOR 2024
SP - 193
BT - Proceedings of the 17th ACM International Systems and Storage Conference, SYSTOR 2024
T2 - 17th ACM International Systems and Storage Conference, SYSTOR 2024
Y2 - 23 September 2024 through 24 September 2024
ER -