Revisiting the design of LSM-tree Based OLTP storage engine with persistent memory

The recent byte-addressable and large-capacity commercialized persistent memory (PM) is promising to drive database as a service (DBaaS) into unchartered territories. This paper investigates how to leverage PMs to revisit the conventional LSM-tree based OLTP storage engines designed for DRAM-SSD hierarchy for DBaaS instances. Specifically we (1) propose a light-weight PM allocator named Hal-loc customized for LSM-tree, (2) build a high-performance Semi-persistent Memtable utilizing the persistent in-memory writes of PM, (3) design a concurrent commit algorithm named Reorder Ring to aschieve log-free transaction processing for OLTP workloads and (4) present a Global Index as the new globally sorted persistent level with non-blocking in-memory compaction. The design of Reorder Ring and Semi-persistent Memtable achieves fast writes without synchronized logging overheads and achieves near instant recovery time. Moreover, the design of Semi-persistent Memtable and Global Index with in-memory compaction enables the byte-addressable persistent levels in PM, which significantly reduces the read and write amplification as well as the background compaction overheads. The overall evaluation shows that the performance of our proposal over PM-SSD hierarchy outperforms the baseline by up to 3.8x in YCSB benchmark and by 2x in TPC-C benchmark.

Cuttlefish: Fast, parallel, and low-memory compaction of de Bruijn graphs from large-scale genome collections

MotivationThe construction of the compacted de Bruijn graph from a large collection of reference genomes is a task of increasing interest in genomic analyses. For example, compacted colored reference de Bruijn graphs are increasingly used as sequence indices for the purposes of alignment of short and long reads. Also, as we sequence and assemble a greater diversity of individual genomes, the compacted colored de Bruijn graph can be used as the basis for methods aiming to perform comparative genomic analyses on these genomes. While algorithms have been developed to construct the compacted colored de Bruijn graph from reference sequences, there is still room for improvement, especially in the memory and the runtime performance as the number and the scale of the genomes over which the de Bruijn graph is built grow.ResultsWe introduce a new algorithm, implemented in the tool Cuttlefish, to construct the colored compacted de Bruijn graph from a collection of one or more genome references. Cuttlefish introduces a novel modeling scheme of the de Bruijn graph vertices as finite-state automata, and constrains the state-space for the automata to enable tracking of their transitioning states with very low memory usage. Cuttlefish is also fast and highly parallelizable. Experimental results demonstrate that the algorithm scales much better than existing approaches, especially as the number and scale of the input references grow. For example, on a typical shared-memory machine, Cuttlefish constructed the compacted graph for 100 human genomes in less than 7 hours, using ~29 GB of memory; no other tested tool successfully completed this task on the testing hardware. We also applied Cuttlefish on 11 diverse conifer plant genomes, and the compacted graph was constructed in under 11 hours, using ~84 GB of memory, while the only other tested tool able to complete this compaction on our hardware took more than 16 hours and ~289 GB of memory.AvailabilityCuttlefish is written in C++14, and is available under an open source license at https://github.com/COMBINE-lab/[email protected]

Fast In-Memory Key–Value Cache System with RDMA

The quick advances of Cloud and the advent of Fog computing impose more and more critical demand for computing and data transfer of low latency onto the underlying distributed computing infrastructure. Remote direct memory access (RDMA) technology has been widely applied for its low latency of remote data access. However, RDMA gives rise to a host of challenges in accelerating in-memory key–value stores, such as direct remote memory writes, making the remote system more vulnerable. This study presents an in-memory key–value system based on RDMA, named Craftscached, which enables: (1) buffering remote memory writes into a communication cache memory to eliminate direct remote memory writes to the data memory area; (2) dividing the communication cache memory into RDMA-writable and RDMA-readable memory zones to reduce the possibility of data corruption due to stray memory writes and caching data into an RDMA-readable memory zone to improve the remote memory read performance; and (3) adopting remote out-of-place direct memory write to achieve high performance of remote read and write. Experimental results in comparison with Memcached indicate that Craftscached provides a far better performance: (1) in the case of read-intensive workloads, the data access of Craftscached is about 7–43[Formula: see text] and 18–72.4% better than those of TCP/IP-based and RDMA-based Memcached, respectively; (2) the memory utilization of small objects is more efficient with only about 3.8% memory compaction overhead.