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    Big Data Engineering — Best Practices Allgemein

    Big Data Engineering — Best Practices

    This is part 1 of a series on data engineering in a big data environment.…
    KupferschmidtAdmin
    KupferschmidtAdmin16. Oktober 2020
    Running Jupyter with Spark in Docker Allgemein

    Running Jupyter with Spark in Docker

    most attendees of dimajix Spark workshops seem to like the hands-on approach I am offering…
    KupferschmidtAdmin
    KupferschmidtAdmin2. Oktober 2017
    Jupyter Notebooks with PySpark in AWS Allgemein

    Jupyter Notebooks with PySpark in AWS

    Amazon Elastic MapReduce (EMR) is something wonderful if you need compute capacity on demand. I…
    KupferschmidtAdmin
    KupferschmidtAdmin22. Mai 2017
    Running Spark and Hadoop with S3 Allgemein

    Running Spark and Hadoop with S3

    Traditionally HDFS was the primary storage for Hadoop (and therefore also for Apache Spark). Naturally…
    KupferschmidtAdmin
    KupferschmidtAdmin5. Mai 2017
    Running PySpark on Anaconda in PyCharm Allgemein

    Running PySpark on Anaconda in PyCharm

    Working with PySpark Currently Apache Spark with its bindings PySpark and SparkR is the processing…
    KupferschmidtAdmin
    KupferschmidtAdmin15. April 2017
    Building Druid for Cloudera 5.4.x Allgemein

    Building Druid for Cloudera 5.4.x

    So the other day I wanted to investigate into using Druid as a reporting backend…
    dominik_adm1n
    dominik_adm1n23. März 2016

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    • Big Data Engineering — Best Practices
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    • Running Spark and Hadoop with S3
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    ✨ Enabling Data Value Since 2005. ✨
    • Expertise
      • Architektur für Big Data und Data Science
      • Data Engineering
      • Data Science & Machine Learning
      • Apache Spark & PySpark
      • Apache Hadoop
      • Data Mesh
      • Open Source
    • Akademie
      • Offene Trainings
      • Big Data
      • Apache Hadoop
      • Data Engineering mit Apache Spark & PySpark
      • Data Science mit PySpark
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