SpotMon: Enabling General Hotspot Monitoring in Key-Value Stores

Key-value stores are essential to online services such as e-commerce. In key-value stores, a hotspot (i.e., frequently accessed items) may cause severe load imbalances, high response latency, and Service Level Agreement (SLA) violations. However, existing works only focus on specific types of hotspots, thus overlooking other types of hotspots and leading to blind spots. In this paper, we propose SpotMon, a system that enables general hotspot monitoring in key-value stores. Specifically, we (1) systematically identify the generality requirements of hotspot monitoring from existing works, (2) formulate general hotspot monitoring as an arbitrary partial spot query problem, (3) measure the hotness of hotspot candidates with a new vector expression, (4) propose hotspot encoding, filtering, decoding, and querying to support general queries without focusing on specific hotspots, (5) leverage the in-network visibility of programmable switches to identify system-wide hotspots. Our extensive experiments indicate that SpotMon provides high accuracy (e.g., F1 score from 0.88 to 1) and enables efficient hotspot mitigations (e.g., up to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$4.03 \times$</tex> MQPS).

Authors

Institutions

Publication Details

Published
2024-10-28
DOI
https://doi.org/10.1109/icnp61940.2024.10858526
Citations
1
Primary Topic
Peer-to-Peer Network Technologies
Type
article
Field-Weighted Citation Impact
0.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SpotMon: Enabling General Hotspot Monitoring in Key-Value Stores

Zhengyan Zhou, Xiang Chen, J. Zu, Zizhao Wang et al.
1 citations
Peer-to-Peer Network Technologies
0.35
article

SpotMon: Enabling General Hotspot Monitoring in Key-Value Stores

Zhengyan Zhou, Xiang Chen, J. Zu, Zizhao Wang, Chunming Wu, Elaine Huang, Dong Zhang, Haifeng Zhou
article en
1 citations

Abstract

Key-value stores are essential to online services such as e-commerce. In key-value stores, a hotspot (i.e., frequently accessed items) may cause severe load imbalances, high response latency, and Service Level Agreement (SLA) violations. However, existing works only focus on specific types of hotspots, thus overlooking other types of hotspots and leading to blind spots. In this paper, we propose SpotMon, a system that enables general hotspot monitoring in key-value stores. Specifically, we (1) systematically identify the generality requirements of hotspot monitoring from existing works, (2) formulate general hotspot monitoring as an arbitrary partial spot query problem, (3) measure the hotness of hotspot candidates with a new vector expression, (4) propose hotspot encoding, filtering, decoding, and querying to support general queries without focusing on specific hotspots, (5) leverage the in-network visibility of programmable switches to identify system-wide hotspots. Our extensive experiments indicate that SpotMon provides high accuracy (e.g., F1 score from 0.88 to 1) and enables efficient hotspot mitigations (e.g., up to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$4.03 \times$</tex> MQPS).

Zhejiang University of Science and Technology (CN), Peng Cheng Laboratory (CN), Zhejiang University (CN)
Decent work and economic growth
Openalex Percentile: Top 34%
Peer-to-Peer Network Technologies
0.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.