Sequential data access with Oracle and Hadoop: a performance comparison

Baranowski, Zbigniew; Canali, Luca; Grancher, Eric

doi:10.1088/1742-6596/513/4/042001

Cited by 4 publications

(4 citation statements)

References 5 publications

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“…Thus it is important that it is robust and delivers the required performance [6] has proven that it is horizontally scalable. The rest of this paper elaborates on the internal design of the Core Storage and potential improvements that can bring the use of alternative approaches available in the Hadoop ecosystem for storing and accessing the data.…”

Section: Current Architecturementioning

confidence: 99%

A study of data representation in Hadoop to optimize data storage and search performance for the ATLAS EventIndex

Baranowski

Canali

Toebbicke

et al. 2017

J. Phys.: Conf. Ser.

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Section: Current Architecturementioning

confidence: 99%

A study of data representation in Hadoop to optimize data storage and search performance for the ATLAS EventIndex

Baranowski

Canali

Toebbicke

et al. 2017

J. Phys.: Conf. Ser.

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“…The Hadoop cluster is a suitable foundation for numerous reasons: the "shared nothing" architecture allows to scale the throughput of the analytics workflows, since the data are accessed and processed locally [7]. The Hadoop Distributed File System (HDFS) serves as a flexible storage layer.…”

Section: Big Data Infrastructurementioning

confidence: 99%

Big data analytics for the Future Circular Collider reliability and availability studies

Begy

Apollonio

Niemi

et al. 2017

J. Phys.: Conf. Ser.

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Abstract. Responding to the European Strategy for Particle Physics update 2013, the Future Circular Collider study explores scenarios of circular frontier colliders for the post-LHC era. One branch of the study assesses industrial approaches to model and simulate the reliability and availability of the entire particle collider complex based on the continuous monitoring of CERN's accelerator complex operation. The modelling is based on an in-depth study of the CERN injector chain and LHC, and is carried out as a cooperative effort with the HL-LHC project. The work so far has revealed that a major challenge is obtaining accelerator monitoring and operational data with sufficient quality, to automate the data quality annotation and calculation of reliability distribution functions for systems, subsystems and components where needed. A flexible data management and analytics environment that permits integrating the heterogeneous data sources, the domain-specific data quality management algorithms and the reliability modelling and simulation suite is a key enabler to complete this accelerator operation study. This paper describes the Big Data infrastructure and analytics ecosystem that has been put in operation at CERN, serving as the foundation on which reliability and availability analysis and simulations can be built. This contribution focuses on data infrastructure and data management aspects and presents case studies chosen for its validation.

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“…Apache Hadoop 1 is an open source industry-standard solution for big data storing and processing. It consists of many components that can cooperate with each other building a distributed multi-purpose platform.…”

Section: Introductionmentioning

confidence: 99%

“…At CERN, Hadoop has become a common replacement for database-like systems that collect terabytes of data, and for workloads that are hard to scale with traditional relational database systems. [1]. Growing demand for highly scalable data warehouses has led in 2013 to start up a Hadoop service provided by the IT department at CERN.…”

Section: Introductionmentioning

confidence: 99%

Evolution of the Hadoop Platform and Ecosystem for High Energy Physics

et al. 2019

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The interest in using scalable data processing solutions based on Apache Hadoop ecosystem is constantly growing in the High Energy Physics (HEP) community. This drives the need for increased reliability and availability of the central Hadoop service and underlying infrastructure provided to the community by the CERN IT department. This paper reports on the overall status of the Hadoop platform and related Hadoop and Spark service at CERN, detailing recent enhancements and features introduced in many areas including the service configuration, availability, alerting, monitoring and data protection, in order to meet the new requirements posed by the users’ community.

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Sequential data access with Oracle and Hadoop: a performance comparison

Cited by 4 publications

References 5 publications

A study of data representation in Hadoop to optimize data storage and search performance for the ATLAS EventIndex

A study of data representation in Hadoop to optimize data storage and search performance for the ATLAS EventIndex

Big data analytics for the Future Circular Collider reliability and availability studies

Evolution of the Hadoop Platform and Ecosystem for High Energy Physics

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