Journal
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
Volume 26, Issue 10, Pages 2368-2381Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TKDE.2014.5
Keywords
Phase change memory (PCM); non-volatile storage; B-p-tree; predictive model
Categories
Funding
- National Natural Science Foundation of China [61272090, 61373024]
- National Grand Fundamental Research 973 Program of China [2011CB302206]
- Beijing Higher Education Young Elite Teacher Project [YETP0105]
- Tsinghua University [20111081073]
- Tsinghua-Tencent Joint Laboratory for Internet Innovation Technology
- NExT Research Center - MDA, Singapore [WBS:R-252-300-001-490]
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Phase change memory (PCM) has been considered an attractive alternative to flash memory and DRAM. It has promising features, including non-volatile storage, byte addressability, fast read and write operations, and supports random accesses. However, there are challenges in designing algorithms for PCM-based memory systems, such as longer write latency and higher energy consumption compared to DRAM. In this paper, we propose a new predictive B+-tree index, called the B-p-tree, which is tailored for database systems that make use of PCM. Our B-p-tree reduces data movements caused by tree node splits and merges that arise from insertions and deletions. This is achieved by pre-allocating space on PCM for near future data. To ensure the space are allocated where they are needed, we propose a novel predictive model to ascertain future data distribution based on the current data. In addition, as in [4], when keys are inserted into a leaf node, they are packed but need not be in sorted order. We have implemented the B-p-tree in PostgreSQL and evaluated it in an emulated environment. Our experimental results show that the B-p-tree significantly reduces the number of writes, therefore making it write and energy efficient and suitable for a PCM-like hardware environment.
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