Elimination (a,b)-trees with fast, durable updates

TL;DR

This paper introduces the OCC-ABtree and Elim-ABtree, two concurrent (a,b)-trees optimized for update-heavy workloads, with Elim-ABtree employing a novel publishing elimination technique to significantly improve performance and durability.

Contribution

The paper presents a new concurrent (a,b)-tree with a novel publishing elimination optimization, achieving superior performance and durability on update-heavy workloads.

Findings

OCC-ABtree outperforms competitors by up to 2x on uniform workloads.

Elim-ABtree achieves up to 2.5x performance improvement on skewed workloads.

Durable versions are nearly as fast as in-memory implementations.

Abstract

Many concurrent dictionary implementations are designed and optimized for read-mostly workloads with uniformly distributed keys, and often perform poorly on update-heavy workloads. In this work, we first present a concurrent (a,b)-tree, the OCC-ABtree, which outperforms its fastest competitor by up to 2x on uniform update-heavy workloads, and is competitive on other workloads. We then turn our attention to skewed update-heavy workloads (which feature many inserts/deletes on the same key) and introduce the Elim-ABtree, which uses a new optimization called publishing elimination. In publishing elimination, concurrent inserts and deletes to a key are reordered to eliminate them. This reduces the number of writes in the data structure. The Elim-ABtree achieves up to 2.5x the performance of its fastest competitor (including the OCC-ABtree). The OCC-ABtree and Elim-ABtree are linearizable. We also introduce durable linearizable versions (for systems with Intel Optane DCPMM non-volatile main memory) that are nearly as fast.