Parallel replication across formats for scaling out mixed OLTP/OLAP workloads in main-memory databases

Parallel replication across formats for scaling out mixed OLTP/OLAP workloads in main-memory... Modern in-memory database systems are facing the need of efficiently supporting mixed workloads of OLTP and OLAP. A conventional approach to this requirement is to rely on ETL-style, application-driven data replication between two very different OLTP and OLAP systems, sacrificing real-time reporting on operational data. An alternative approach is to run OLTP and OLAP workloads in a single machine, which eventually limits the maximum scalability. In order to tackle this challenging problem, we propose a novel database replication architecture called HANA Asynchronous Parallel Table Replication (ATR). ATR supports OLTP workloads in one primary machine, while it supports heavy OLAP workloads in replicas. Here, row store formats can be used for OLTP transactions at the primary, while column store formats are used for OLAP analytical queries at the replicas. ATR is designed to support elastic scalability of OLAP query performance, while it minimizes the overhead for transaction processing at the primary and minimizes CPU consumption for replayed transactions at the replicas. ATR employs a novel optimistic lock-free parallel log replay scheme which exploits characteristics of multi-version concurrency control (MVCC) to enable real-time reporting by minimizing the propagation delay between the primary and replicas. It supports adaptive query routing depending on its predefined acceptable staleness range. Through extensive experiments with a concrete implementation available in a commercial product, we demonstrate that ATR achieves sub-second visibility delay even for update-intensive workloads, providing scalable OLAP performance without notable overhead to the primary. In addition, with extension of ATR to eager parallel replication, we demonstrate how the parallel log replay and its log-less replica recovery mechanisms improve run-time transaction performance under eager replication. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The VLDB Journal Springer Journals

Parallel replication across formats for scaling out mixed OLTP/OLAP workloads in main-memory databases

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer-Verlag GmbH Germany, part of Springer Nature
Subject
Computer Science; Database Management
ISSN
1066-8888
eISSN
0949-877X
D.O.I.
10.1007/s00778-018-0503-z
Publisher site
See Article on Publisher Site

Abstract

Modern in-memory database systems are facing the need of efficiently supporting mixed workloads of OLTP and OLAP. A conventional approach to this requirement is to rely on ETL-style, application-driven data replication between two very different OLTP and OLAP systems, sacrificing real-time reporting on operational data. An alternative approach is to run OLTP and OLAP workloads in a single machine, which eventually limits the maximum scalability. In order to tackle this challenging problem, we propose a novel database replication architecture called HANA Asynchronous Parallel Table Replication (ATR). ATR supports OLTP workloads in one primary machine, while it supports heavy OLAP workloads in replicas. Here, row store formats can be used for OLTP transactions at the primary, while column store formats are used for OLAP analytical queries at the replicas. ATR is designed to support elastic scalability of OLAP query performance, while it minimizes the overhead for transaction processing at the primary and minimizes CPU consumption for replayed transactions at the replicas. ATR employs a novel optimistic lock-free parallel log replay scheme which exploits characteristics of multi-version concurrency control (MVCC) to enable real-time reporting by minimizing the propagation delay between the primary and replicas. It supports adaptive query routing depending on its predefined acceptable staleness range. Through extensive experiments with a concrete implementation available in a commercial product, we demonstrate that ATR achieves sub-second visibility delay even for update-intensive workloads, providing scalable OLAP performance without notable overhead to the primary. In addition, with extension of ATR to eager parallel replication, we demonstrate how the parallel log replay and its log-less replica recovery mechanisms improve run-time transaction performance under eager replication.

Journal

The VLDB JournalSpringer Journals

Published: Apr 16, 2018

References

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