Data structure primitives on persistent memory

Götze, Philipp; Tharanatha, Arun Kumar; Sattler, Kai-Uwe

doi:10.1145/3399666.3399900

Cited by 11 publications

(7 citation statements)

References 5 publications

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“…1a consisting of four columns and six tuples. As datasensitive optimizations, Elf features two different node types: DimensionLists, labeled (1), (2), (5), and (6) as inner nodes that hold sorted column values of several tuples and MonoLists as a special type of DimensionList, labeled (3), (4), (7), (8), (9), and (10), that represent values of a single tuple spanning across several columns. The idea of MonoLists is that whenever there is no branch-out on deeper levels, the linked lists are merged to a single MonoList, thus eliminating pointers and distributed storage.…”

Section: The Elf Storage Layoutmentioning

confidence: 99%

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Selective caching: a persistent memory approach for multi-dimensional index structures

Jibril

Götze

Broneske

et al. 2021

Distrib Parallel Databases

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After the introduction of Persistent Memory in the form of Intel’s Optane DC Persistent Memory on the market in 2019, it has found its way into manifold applications and systems. As Google and other cloud infrastructure providers are starting to incorporate Persistent Memory into their portfolio, it is only logical that cloud applications have to exploit its inherent properties. Persistent Memory can serve as a DRAM substitute, but guarantees persistence at the cost of compromised read/write performance compared to standard DRAM. These properties particularly affect the performance of index structures, since they are subject to frequent updates and queries. However, adapting each and every index structure to exploit the properties of Persistent Memory is tedious. Hence, we require a general technique that hides this access gap, e.g., by using DRAM caching strategies. To exploit Persistent Memory properties for analytical index structures, we propose selective caching. It is based on a mixture of dynamic and static caching of tree nodes in DRAM to reach near-DRAM access speeds for index structures. In this paper, we evaluate selective caching on the OLAP-optimized main-memory index structure Elf, because its memory layout allows for an easy caching. Our experiments show that if configured well, selective caching with a suitable replacement strategy can keep pace with pure DRAM storage of Elf while guaranteeing persistence. These results are also reflected when selective caching is used for parallel workloads.

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Section: The Elf Storage Layoutmentioning

confidence: 99%

“…Since former experiments work on emulated PMem, in [22], the authors re-evaluated the B + -Tree variants on real hardware. In [10,11], the underlying primitives of these trees are also analyzed on real PMem.…”

Section: Related Workmentioning

confidence: 99%

Selective caching: a persistent memory approach for multi-dimensional index structures

Jibril

Götze

Broneske

et al. 2021

Distrib Parallel Databases

Self Cite

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“…Intel's Optane DC Persistent Memory [6], 3D XPoint [4], became the first emerging technology with a commercially available product. A number of performance studies have been conducted to understand its properties in various settings, such as raw read/ write performance [33,34], basic primitives such as page propagation, and logging [25], as well as more complex index-structures [35][36][37] and storage engines [38].…”

Section: Persistent Main Memorymentioning

confidence: 99%

Towards Log-Less, Fine-Granular State Machine Replication

Skrzypzcak

Schintke

2020

Datenbank Spektrum

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State machine replication is used to increase the availability of a service such as a data management system while ensuring consistent access to it. State-of-the-art implementations are based on a command log to gain linear write access to storage and avoid repeated transmissions of large replicas. However, the command log requires non-trivial state management such as allocation and pruning to prevent unbounded growth. By introducing in-place replicated state machines that do not use command logs, the log overhead can be avoided. Instead, replicas agree on a sequence of states, and former states are directly overwritten. This method enables the consistent, fault-tolerant replication of basic data management primitives such as counters, sets, or individual locks with little to no overhead. It matches the properties of fast, byte-addressable, non-volatile memory particularly well, where it is no longer necessary to rely on sequential access for good performance. Our approach is especially well suited for small states and fine-granular distributed data management as it occurs in key-value stores, for example.

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“…Therefore, accesses to the device should be reduced -especially writes -to overcome these limitations. Another observation [8] is that despite the byteaddressability, there is still a relatively large discrepancy between sequential and random accesses.…”

Section: Persistent Memorymentioning

confidence: 99%

“…Following LL1 and LL2, there are several other ways to make even finer use of PMem, such as optimizing the node size, the alignment, as well as the internal node organization and the associated access patterns (cf. [8]). Finally, while this work focused on the storage system itself, query processing mechanisms such as efficient event replay remain an ongoing challenge.…”

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confidence: 99%

Designing an Event Store for a Modern Three-layer Storage Hierarchy

et al. 2020

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Event stores face the difficult challenge of continuously ingesting massive temporal data streams while satisfying demanding query and recovery requirements. Many of today’s systems deal with multiple hardware-based trade-offs. For instance, long-term storage solutions balance keeping data in cheap secondary media (SSDs, HDDs) and performance-oriented main-memory caches. As an alternative, in-memory systems focus on performance, while sacrificing monetary costs, and, to some degree, recovery guarantees. The advent of persistent memory (PMem) led to a multitude of novel research proposals aiming to alleviate those trade-offs in various fields. So far, however, there is no proposal for a PMem-powered specialized event store. Based on ChronicleDB, we will present several complementary approaches for a three-layer architecture featuring main memory, PMem, and secondary storage. We enhance some of ChronicleDB’s components with PMem for better insertion and query performance as well as better recovery guarantees. At the same time, the three-layer architecture aims to keep the overall dollar cost of a system low. The limitations and opportunities of a PMem-enhanced event store serve as important groundwork for comprehensive system design exploiting a modern storage hierarchy.

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Data structure primitives on persistent memory

Cited by 11 publications

References 5 publications

Selective caching: a persistent memory approach for multi-dimensional index structures

Selective caching: a persistent memory approach for multi-dimensional index structures

Towards Log-Less, Fine-Granular State Machine Replication

Designing an Event Store for a Modern Three-layer Storage Hierarchy

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