Workload-aware aggregate maintenance in columnar in-memory databases

Müller, Stephan; Butzmann, Lars; Klauck, Stefan; Plattner, Hasso

doi:10.1109/bigdata.2013.6691699

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…A wide variety of techniques was proposed to optimize the execution of aggregate range queries in DBMSes. A whole class of proposals deal with materialized views (see for example [28,23,27,53,40]). These techniques require the DBMS to keep the results of certain queries stored and up-to-date.…”

Section: State Of the Artmentioning

confidence: 99%

Overlay Indexes: Efficiently Supporting Aggregate Range Queries and Authenticated Data Structures in Off-the-Shelf Databases

Pennino

Pizzonia

Papi³

2019

IEEE Access

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Commercial off-the-shelf DataBase Management Systems (DBMSes) are highly optimized to process a wide range of queries by means of carefully designed indexing and query planning. However, many aggregate range queries are usually performed by DBMSes using sequential scans, and certain needs, like storing Authenticated Data Structures (ADS), are not supported at all. Theoretically, these needs could be efficiently fulfilled adopting specific kinds of indexing, which however are normally ruled-out in DBMSes design.We introduce the concept of overlay index : an index that is meant to be stored in a standard database, alongside regular data and managed by regular software, to complement DBMS capabilities. We show a data structure, that we call DB-tree, that realizes an overlay index to support a wide range of custom aggregate range queries as well as ADSes, efficiently. All DB-trees operations can be performed by executing a small number of queries to the DBMS, that can be issued in parallel in one or two query rounds, and involves a logarithmic amount of data. We experimentally evaluate the efficiency of DB-trees showing that our approach is effective, especially if data updates are limited.

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Section: State Of the Artmentioning

confidence: 99%

Overlay Indexes: Efficiently Supporting Aggregate Range Queries and Authenticated Data Structures in Off-the-Shelf Databases

Pennino

Pizzonia

Papi³

2019

IEEE Access

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“…As enterprise workloads are not characterized by constant insert ratios, the best performing maintenance strategy changes. We have addressed this issue by implementing a framework that monitors the current workload for a configurable number of queries called window, calculates the predicted performance of applicable materialized aggregate maintenance strategies based on their cost model and the monitored insert-ratio, and switches according to the following algorithms [43]:…”

Section: B Joinsmentioning

confidence: 99%

Aggregates caching for enterprise applications

Müller

2014

2014 IEEE 30th International Conference on Data Engineering Workshops

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Modern enterprise applications generate a mixed workload comprised of short-running transactional queries and long-running analytical queries containing expensive aggregations. Based on the fact that columnar in-memory databases are capable of handling these mixed workloads, we evaluate how existing materialized view maintenance strategies can accelerate the execution of aggregate queries. We contribute by introducing a novel materialized view maintenance approach that leverages the main-delta architecture of columnar storage, outperforming existing strategies for a wide range of workloads. As an optimization, we further propose an approach that adapts the aggregate maintenance strategy based upon the currently monitored workload characteristics.

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“…(1c) Design guidelines for in-memory apps lack impact for practice: We examined 20 publications about IS models outlining guidelines for in-memory technology in general ( Figure 1, third column). However, these references focus on technical details such as cloud computing [69] or dashboard implementation [70] and other [71,72]. [62] provide a matrix consisting of four use cases for operational analytics and the BI/DWH environment as well as [68] which lays out six patterns of inmemory technology.…”

Section: Gap Analysis (1a)mentioning

confidence: 99%

App Design for Use -- A Manager Perspective for In-Memory Technology

Goeken¹,

Mayer

Bork

et al. 2014

2014 IEEE 16th Conference on Business Informatics

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Information systems (IS) intended to help managers are known as management support systems (MSS). The present situation is favorable for a redesign that applies in-memory apps. Such apps promise to support managers with benefits ranging from reducing time for MSS data entry and analysis to new topics of analysis. Based on findings from a literature review and results from a workshop with an expert focus group validated with one-on-one manager interviews, we propose six guidelines for an app design that contributes to greater MSS acceptance: (1) A tile design for the entry-page. (2) A manager news ticker as starting point for self-service analysis. (3) An intuitive navigation known and appreciated from consumer IS. (4) A collaboration tool to foster joint managerial problem solving. (5) Exception reporting which includes personal exception limits and a push function. (6) In-memory apps should be evaluated by their capability to perform new types of analysis.

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Workload-aware aggregate maintenance in columnar in-memory databases

Cited by 5 publications

References 16 publications

Overlay Indexes: Efficiently Supporting Aggregate Range Queries and Authenticated Data Structures in Off-the-Shelf Databases

Overlay Indexes: Efficiently Supporting Aggregate Range Queries and Authenticated Data Structures in Off-the-Shelf Databases

Aggregates caching for enterprise applications

App Design for Use -- A Manager Perspective for In-Memory Technology

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