Enhancing Apache Spark and Parquet Efficiency: A Deep Dive into Column Indexes and Bloom Filters
In the ever-evolving landscape of big data, Apache Spark and Apache Parquet continue to introduce game-changing features.
Parquet
Parquet
Diving into Spark and Parquet Workloads, by Example
Topic: In this post you can find a few simple examples illustrating im
Performance comparison of different file formats and storage engines in the Hadoop ecosystem
TOPIC
This post reports performance tests for a few popular data formats and storage engines available in the Hadoop ecosystem: Apache Avro, Apache Parquet, Apache HBase and Apache Kudu. This exercise evaluates space efficiency, ingestion performance, analytic scans and random data lookup for a workload of interest at CERN Hadoop service.
INTRO
Disclaimer
The views expressed in this blog are those of the authors and cannot be regarded as representing CERN’s official position.
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Christian Antognini, Karl Arao, Martin Bach, Mark Bobak, Wolfgang Breitling, Doug Burns, Kevin Closson, Cloudera blog, Wim Coekaerts, Bertrand Drouvot, Enkitec blog, Pete Finnigan, Richard Foote, Randolf Geist, Marco Gralike, Brendan Gregg, Kyle Hailey, Tim Hall, Uwe Hesse, Frits Hoogland, Hortonworks blog, Integrity Oracle Security, Tom Kyte, Adam Leventhal, Jonathan Lewis, Cary Millsap, James Morle, Karen Morton, Arup Nanda, Mogens Nørgaard, Oracle The Data Warehouse insider, Oracle Enterprise Manager, Oracle Linux blog, Oracle Multitenant, Oracle Optimizer blog, Oracle R technologies, Oracle Upgrade blog, Oracle Virtualization blog, Kerry Osborne, Tanel Poder, Planet PostgreSQL, Kellyn Pot'Vin, Pythian blog, Greg Rahn, Mark Rittman, Riyaj Shamsudeen, Chen Shapira, Carlos Sierra, Szymon Skorupinski