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Two entries in Encyclopedia of Big Data Technologies, Sakr, Sherif, Zomaya, Albert (Eds.), Springer

I. Petrov, T. Vincon, A. Koch, J. Oppermann, S. Hardock, C. Riegger. Active Storage
In Enc. Big Data Technologies Sakr, Zomaya (Eds.) Springer 2018.

I. Petrov, A. Koch, T. Vincon, S. Hardock, C. Riegger. Transaction Processing on NVM
In Enc. Big Data Technologies Sakr, Zomaya (Eds.) Springer 2018.

NoFTL-KV: Tackling Write-Amplification on KV-Stores with Native Storage Management

T. Vincon, S. Hardock C. Riegger, J. Oppermann, A. Koch, I. Petrov.
In Proc. EDBT 2018

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22.12.2017 Paper Accepted at EDBT 2018

T. Vincon, S. Hardock C. Riegger, J. Oppermann, A. Koch, I. Petrov. NoFTL-KV: Tackling Write-Amplification on KV-Stores with Native Storage Management. In Proc. EDBT 2018.

[PDF]

Abstract:

Modern persistent Key/Value stores are designed to meet the demand for high transactional throughput and high data-ingestion rates. Still, they rely on backwards-compatible storage stack and abstractions to ease space management, foster seamless proliferation and system integration. Their dependence on the traditional I/O stack has negative impact on performance, causes unacceptably high write-amplification, and limits the storage longevity.
In the present paper we present NoFTL-KV, an approach that results in a lean I/O stack, integrating physical storage management natively in the Key/Value store. NoFTL-KV eliminates backwards compatibility, allowing the Key/Value store to directly consume the characteristics of modern storage technologies. NoFTL-KV is implemented under RocksDB. The performance evaluation under LinkBench shows that NoFTL-KV improves transactional throughput by 33%, while response times improve up to 2.3x. Furthermore, NoFTL-KV reduces write-amplification 19x and improves storage longevity by imately the same factor.

Multi-Version Indexing and modern Hardware Technologies

A Survey of present Indexing Approaches

C. Riegger, T. Vincon, I. Petrov.
In Proc. iiWAS 2017

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02.10.2017 Paper Accepted at iiWAS 2017

C. Riegger, T. Vincon, I. Petrov. Multi-Version Indexing and modern Hardware Technologies - A Survey of present Indexing Approaches. In Proc. iiWAS 2017.

[PDF]

Abstract:

Characteristics of modern computing and storage technologies fundamentally differ from traditional hardware. There is a need to optimally leverage their performance, endurance and energy consumption characteristics. Therefore, existing architectures and algorithms in modern high performance database management systems have to be redesigned and advanced. Multi Version Concurrency Control (MVCC) approaches in data-base management systems maintain multiple physically independent tuple versions. Snapshot isolation approaches enable high parallelism and concurrency in workloads with almost serializable consistency level. Modern hardware technologies benefit from multi-version approaches. Indexing multi-version data on modern hardware is still an open research area. In this paper, we provide a survey of popular multi-version indexing approaches and an extended scope of high performance single-version approaches. An optimal multi-version index structure brings look-up efficiency of tuple versions, which are visible to transactions, and effort on index maintenance in balance for different workloads on modern hardware technologies.

Write-Optimized Indexing with Partitioned B-Trees

C. Riegger, T. Vincon, I. Petrov.
In Proc. iiWAS 2017

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02.10.2017 Paper Accepted at iiWAS 2017

C. Riegger, T. Vincon, I. Petrov. Write-Optimized Indexing with Partitioned B-Trees. In Proc. iiWAS 2017.

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Abstract:

Database management systems (DBMS) are critical performance component in large scale applications under modern update-intensive workloads. Additional access paths accelerate look-up performance in DBMS for frequently queried attributes, but the required maintenance slows down update performance. The ubiquitous B + -Tree is a commonly used key-indexed access path that is able to support many required functionalities with logarithmic access time to requested records. Modern processing and storage technologies and their characteristics require reconsideration of matured indexing approaches for today’s workloads. Partitioned B-Trees (PBT) leverage characteristics of modern hardware technologies and complex memory hierarchies as well as high update rates and changes in workloads by maintaining partitions within one single B + -Tree. This paper includes an experimental evaluation of PBTs optimized write pattern and performance improvements. With PBT transactional throughput under TPC-C increases 30%; PBT results in beneficial sequential write patterns even in presence of updates and maintenance operations.

SIAS-Chains: Snapshot Isolation Append Storage Chains

R. Gottstein, I. Petrov, S. Hardock, A. Buchmann
In Proc. ADMS@VLDB 2017

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27.8.2017 Paper Accepted at ADMS@VLDB 2017

R. Gottstein, I. Petrov, S. Hardock, A. Buchmann. SIAS-Chains: Snapshot Isolation Append Storage Chains. In Proc. ADMS@VLDB 2017.

[PDF]

Abstract:

Asymmetric read/write storage technologies such as Flash are becoming a dominant trend in modern database systems.They introduce hardware characteristics and properties which are fundamentally different from those of traditional storage technologies such as HDDs.

Multi-Versioning Database Management Systems (MV-DBMSs) and Log-based Storage Managers (LbSMs) are concepts that can effectively address the properties of these storage technologies but are designed for the characteristics of legacy hardware. A critical component of MV-DBMSs is the invalidation model. Transactional timestamps are assigned to the old and the new version, resulting in two independent (physical) update operations. Those entail multiple random writes as well as in-place updates, sub-optimal for new storage technologies both in terms of performance and endurance. Traditional page-append LbSM approaches alleviate random writes and immediate in-place updates, hence reducing the negative impact of Flash read/write asymmetry. Nevertheless, they entail significant mapping overhead, leading to write amplification.

In this work we present the Snapshot Isolation Append Storage Chains (SIAS-Chains) that employs a combination of multi-versioning with append storage management in tuple granularity and novel singly-linked (chain-like) version organization.

SIAS-Chains features simplified buffer management, multi-version indexing and introduces read/write optimizations to data placement on modern storage media. SIAS-Chains algorithmically avoids small in-place updates, caused by in-place invalidation and converts them into appends. Every modification operation is executed as an append and recently inserted tuple versions are co-located. SIAS-Chains is implemented in PostgreSQL and evaluated on modern Flash SSDs with standard update-intensive workload. The performance evaluation under PostgreSQL shows: (i) higher transactional throughput - up to 30 percent; (ii) significantly lower response times - up to 7 times lower; (iii) significant write reduction - up to 97 percent reduction; (iv) reduced space consumption and (v) higher tolerable workload.

Paper Accepted at ICDE 2017

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Selective In-Place Appends for Real: Reducing Erases on Wear-prone DBMS Storage

S. Hardock, I. Petrov, R. Gottstein, A. Buchmann.
In Proc. ICDE 2017 [PDF] [Video]

Abstract: In the present paper we demonstrate the novel technique to apply the recently proposed approach of In-Place Appends – overwrites on Flash without a prior erase operation. IPA can be applied selectively: only to DB-objects that have frequent and relatively small updates. To do so we couple IPA to the concept of NoFTL regions, allowing the DBA to place update-intensive DB-objects into special IPA-enabled regions. The decision about region configuration can be (semi-)automated by an advisor analyzing DB-log files in the background.

We showcase a Shore-MT based prototype of the above approach, operating on real Flash hardware. During the demon- stration we allow the users to interact with the system and gain hands-on experience under different demonstration scenarios.