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Data Engineering: Fast Spatial Joins Across ~2 Billion Rows on a Single Old GPU

Towards Data Science

Comparing the performance of ORC and Parquet on spatial joins across 2 Billion rows on an old Nvidia GeForce GTX 1060 GPU on a local machine Photo by Clay Banks on Unsplash Over the past few weeks I have been digging a bit deeper into the advances that GPU data processing libraries have made since I last focused on it in 2019.

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Recap of Hadoop News for January 2018

ProjectPro

Apache Hadoop has become the go-to framework within the big data ecosystem for running and managing big data applications on large hardware hadoop clusters in distributed environments.Hortonwork’s Hadoop YARN & MapReduce Development Lead, Vinod Kumar Vavilapalli offered his perspective on the latest release of Hadoop 3.0

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Top 20+ Big Data Certifications and Courses in 2023

Knowledge Hut

Data Analysis : Strong data analysis skills will help you define ways and strategies to transform data and extract useful insights from the data set. Big Data Frameworks : Familiarity with popular Big Data frameworks such as Hadoop, Apache Spark, Apache Flink, or Kafka are the tools used for data processing.

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Emerging Big Data Trends for 2023

ProjectPro

With the use of various SQL-on-Hadoop tools like Hive, Impala, Phoenix, Presto and Drill, query accelerators are bridging the gap between traditional data warehouse systems and the world of big data. 2) Big Data is no longer just Hadoop A common misconception is that Big Data and Hadoop are synonymous.

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Hadoop Salary: A Complete Guide from Beginners to Advance

Knowledge Hut

An expert who uses the Hadoop environment to design, create, and deploy Big Data solutions is known as a Hadoop Developer. They are skilled in working with tools like MapReduce, Hive, and HBase to manage and process huge datasets, and they are proficient in programming languages like Java and Python.

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