Non-volatile memory technologies (NVM) introduce a novel class of devices that combine characteristics of both storage and main memory. Like storage, NVM is not only persistent, but also denser and cheaper than DRAM. Like DRAM, NVM is byte-addressable and has lower access latency. In recent years, NVM has gained a lot of attention both in academia and in the data management industry, with views ranging from skepticism to over excitement. Some critics claim that NVM is not cheap enough to replace flash-based SSDs nor is it fast enough to replace DRAM, while others see it simply as a storage device. Supporters of NVM have observed that its low latency and byte-addressability requires radical changes and a complete rewrite of storage management architectures.
This thesis takes a moderate stance between these two views. We consider that, while NVM might not replace flash-based SSD or DRAM in the near future, it has the potential to reduce the gap between them. Furthermore, treating NVM as a regular storage media does not fully leverage its byte-addressability and low latency. On the other hand, completely redesigning systems to be NVM-centric is impractical. Proposals that attempt to leverage NVM to simplify storage management result in completely new architectures that face the same challenges that are already well-understood and addressed by the traditional architectures. Therefore, we take three common storage management architectures as a starting point, and propose incremental changes to enable them to better leverage NVM. First, in the context of log-structured merge-trees, we investigate the impact of storing data in NVM, and devise methods to enable small granularity accesses and NVM-aware caching policies. Second, in the context of B+Trees, we propose to extend the buffer pool and describe a technique based on the concept of optimistic consistency to handle corrupted pages in NVM. Third, we employ NVM to enable larger capacity and reduced costs in a index+log key-value store, and combine it with other techniques to build a system that achieves low tail latency. This thesis aims to describe and evaluate these techniques in order to enable storage management architectures to leverage NVM and achieve increased performance and lower costs, without major architectural changes.:1 Introduction
1.1 Non-Volatile Memory
1.2 Challenges
1.3 Non-Volatile Memory & Database Systems
1.4 Contributions and Outline
2 Background
2.1 Non-Volatile Memory
2.1.1 Types of NVM
2.1.2 Access Modes
2.1.3 Byte-addressability and Persistency
2.1.4 Performance
2.2 Related Work
2.3 Case Study: Persistent Tree Structures
2.3.1 Persistent Trees
2.3.2 Evaluation
3 Log-Structured Merge-Trees
3.1 LSM and NVM
3.2 LSM Architecture
3.2.1 LevelDB
3.3 Persistent Memory Environment
3.4 2Q Cache Policy for NVM
3.5 Evaluation
3.5.1 Write Performance
3.5.2 Read Performance
3.5.3 Mixed Workloads
3.6 Additional Case Study: RocksDB
3.6.1 Evaluation
4 B+Trees
4.1 B+Tree and NVM
4.1.1 Category #1: Buffer Extension
4.1.2 Category #2: DRAM Buffered Access
4.1.3 Category #3: Persistent Trees
4.2 Persistent Buffer Pool with Optimistic Consistency
4.2.1 Architecture and Assumptions
4.2.2 Embracing Corruption
4.3 Detecting Corruption
4.3.1 Embracing Corruption
4.4 Repairing Corruptions
4.5 Performance Evaluation and Expectations
4.5.1 Checksums Overhead
4.5.2 Runtime and Recovery
4.6 Discussion
5 Index+Log Key-Value Stores
5.1 The Case for Tail Latency
5.2 Goals and Overview
5.3 Execution Model
5.3.1 Reactive Systems and Actor Model
5.3.2 Message-Passing Communication
5.3.3 Cooperative Multitasking
5.4 Log-Structured Storage
5.5 Networking
5.6 Implementation Details
5.6.1 NVM Allocation on RStore
5.6.2 Log-Structured Storage and Indexing
5.6.3 Garbage Collection
5.6.4 Logging and Recovery
5.7 Systems Operations
5.8 Evaluation
5.8.1 Methodology
5.8.2 Environment
5.8.3 Other Systems
5.8.4 Throughput Scalability
5.8.5 Tail Latency
5.8.6 Scans
5.8.7 Memory Consumption
5.9 Related Work
6 Conclusion
Bibliography
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