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The journey to Elasticsearch – Tech Talk with Neodata Group

Tech Talk with Neodata Group: The journey to Elasticsearch In this first episode of our first Tech Talk, we hosted Neodata Group to talk about their journey to Elasticsearch, the
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Spark 3.0: First hands-on approach with Adaptive Query Execution (Part 3)

Spark 3.0: First hands-on approach with Adaptive Query Execution (Part 3) In the previous articles (1)(2), we started analyzing the individual features of Adaptive Query Execution introduced on Spark 3.0.
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Agile Lab ospite di InnoTech, l’Hub di The European House Ambrosetti per parlare di Machine Learning e Big Data in ambito assicurativo

Agile Lab ospite di InnoTech, l’Hub di The European House Ambrosetti per parlare di Machine Learning e Big Data in ambito assicurativo Alberto Firpo, Co-Founder & CEO di Agile Lab,
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Real-time Analytics in applicazioni mission-critical: il caso Vodafone Automotive

  Real-time Analytics in applicazioni mission-critical: il caso Vodafone Automotive In occasione del Convegno conclusivo dell’ottava edizione dell’Osservatorio Big Data & Analytics del Politecnico di Milano, Alberto Firpo, CEO &
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Spark 3.0: First hands-on approach with Adaptive Query Execution (Part 2)

In the previous article, we started analyzing the individual features of Adaptive Query Execution introduced on Spark 3.0. In particular, the first feature analyzed was “dynamically coalescing shuffle partitions”. Let’s get
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Spark 3.0: First hands-on approach with Adaptive Query Execution (Part 1)

Apache Spark is a distributed data processing framework that is suitable for any Big Data context thanks to its features. Despite being a relatively recent product (the first open-source BSD license was
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