Tailwind introduces ALPs and ML-based planning to integrate workload-specific query accelerators into standard RDBMSes, achieving 1.38x average (up to 29x) speedup on TPC-H queries.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.DB 2verdicts
UNVERDICTED 2representative citing papers
HIRE is a hybrid learned index that achieves up to 41.7x higher throughput under mixed workloads and reduces tail latency by up to 98% compared to state-of-the-art learned and traditional indexes.
citing papers explorer
-
Tailwind: A Practical Framework for Query Accelerators
Tailwind introduces ALPs and ML-based planning to integrate workload-specific query accelerators into standard RDBMSes, achieving 1.38x average (up to 29x) speedup on TPC-H queries.
-
HIRE: A Hybrid Learned Index for Robust and Efficient Performance under Mixed Workloads
HIRE is a hybrid learned index that achieves up to 41.7x higher throughput under mixed workloads and reduces tail latency by up to 98% compared to state-of-the-art learned and traditional indexes.