Various transactional systems use out-of-place up-dates such as logging or copy-on-write mechanisms to update data in a failure-atomic manner. Such out-of-place update methods double the I/O traffic due to back-up copies in the database layer and quadruple the I/O traffic due to the file system journaling. In mobile systems, transaction sizes of mobile apps are known to be tiny and transactions run at low concurrency. For such mobile transactions, legacy out-of-place update methods such as WAL are sub-optimal. In this work, we propose a crash consistent in-place update logging method - doubleheader logging (DHL) for SQLite. DHL prevents previous consistent records from being lost by performing a copy-on-write inside the database page and co-locating the metadata-only journal information within the page. This is done, in turn, with minimal sacrifice to page utilization. DHL is similar to when journaling is disabled, in the sense that it incurs almost no additional overhead in terms of both I/O and computation. Our experimental results show that DHL outperforms other logging methods such as out-of-place update write-ahead logging (WAL) and in-place update multi-version B-tree (MVBT).

Emerging byte-addressable non-volatile memory (NVRAM) is expected to replace block device storages as an alternative low-latency persistent storage device. If NVRAM is used as a persistent storage device, a cache line instead of a disk page will be the unit of data transfer, consistency, and durability. In this work, we design and develop clfB-tree —a B-tree structure whose tree node fits in a single cache line. We employ existing write combining store buffer and restricted transactional memory to provide a failure-atomic cache line write operation. Using the failure-atomic cache line write operations, we atomically update a clfB-tree node via a single cache line flush instruction without major changes in hardware. However, there exist many processors that do not provide SW interface for transactional memory. For those processors, our proposed clfB-tree achieves atomicity and consistency via in-place update, which requires maximum four cache line flushes. We evaluate the performance of clfB-tree on an NVRAM emulation board with ARM Cortex A-9 processor and a workstation that has Intel Xeon E7-4809 v3 processor. Our experimental results show clfB-tree outperforms wB-tree and CDDS B-tree by a large margin in terms of both insertion and search performance.

The slotted-page structure is a database page format commonly used for managing variable-length records. In this work, we develop a novel "failure-atomic slotted page structure" for persistent memory that leverages byte addressability and durability of persistent memory to minimize redundant write operations used to maintain consistency in traditional database systems. Failure-atomic slotted paging consists of two key elements: (i) in-place commit per page using hardware transactional memory and (ii) slot header logging that logs the commit mark of each page. The proposed scheme is implemented in SQLite and compared against NVWAL, the current state-of-the-art scheme. Our performance study shows that our failure-atomic slotted paging shows optimal performance for database transactions that insert a single record. For transactions that touch more than one database page, our proposed slot-header logging scheme minimizes the logging overhead by avoiding duplicating pages and logging only the metadata of the dirty pages. Overall, we find that our failure-atomic slotted-page management scheme reduces database logging overhead to 1/6 and improves query response time by up to 33% compared to NVWAL.