Tag: Big Data
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ATLAS DCS Analysis with Apache Spark and Jupyter Notebooks
ATLAS DCS Analysis with Apache Spark and Jupyter Notebooks The ATLAS Detector Control System (DCS) at CERN is essential for ensuring optimal detector performance. Each year, the system generates tens of billions of time-stamped sensor readings, presenting considerable challenges for large-scale data analysis. Although these data are stored in Oracle databases that excel in real-time
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Evaluation of Erasure Coding in Hadoop 3
Evaluation of Erasure Coding in Hadoop 3 Authored By: Nazerke Seidan, Emil Kleszcz, Zbigniew Baranowski Published By: CERN IT-DB-SAS In this post, we will dive into the evaluation of the Erasure Coding feature of Hadoop 3 that I worked on this summer as a CERN Openlab intern. The evaluation has been performed on one of
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Machine Learning Pipelines for High Energy Physics Using Apache Spark with BigDL and Analytics Zoo
Machine Learning Pipelines for High Energy Physics Using Apache Spark with BigDL and Analytics Zoo Topic: This post describes a data pipeline for a machine learning task of interest in high energy physics: building a particle classifier to improve event selection at the particle detectors. The pipeline is built using tools from the “Big Data
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Using Tiered Storage in Alluxio
Using Tiered Storage in Alluxio Introduction Alluxio is an open source memory speed virtual distributed storage system. A brief overview of Alluxio has been covered in a previous blog. This post will cover one of the most powerful features of Alluxio, which is its tiered storage capabilities. Tiered storage allows the Alluxio volume to be
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Experiences of Using Alluxio with Spark
Experiences of Using Alluxio with Spark Introduction Alluxio refers to itself as an “Open Source Memory Speed Virtual Distributed Storage” platform. It sits between the storage and processing framework layers in the distributed computing ecosystem and claims to heavily improve performance when multiple jobs are reading/writing from/to the same data. This post will cover some