Hadoop Reviews and details

Social recommendations and mentions

• Unveiling the Apache License 2.0: A Deep Dive into Open Source Freedom

  One of the key attributes of Apache License 2.0 is its flexible nature. Permitting use in both proprietary and open source environments, it has become the go-to choice for innovative projects ranging from the Apache HTTP Server to large-scale initiatives like Apache Spark and Hadoop. This flexibility is not solely legal; it is also philosophical. The license is designed to encourage transparency and maintain a... - Source: dev.to / about 2 months ago

• Apache Hadoop: Pioneering Open Source Innovation in Big Data

  Apache Hadoop is more than just software—it’s a full-fledged ecosystem built on the principles of open collaboration and decentralized governance. Born out of a need to process vast amounts of information efficiently, Hadoop uses a distributed file system and the MapReduce programming model to enable scalable, fault-tolerant computing. Central to its success is a diverse ecosystem that includes influential... - Source: dev.to / about 2 months ago

• Embracing the Future: India's Pioneering Journey in Open Source Development

  Navya: Designed to streamline administrative processes in educational institutions, Navya continues to demonstrate the power of open source in addressing local needs. Additionally, India’s vibrant tech communities are well represented on platforms like GitHub and SourceForge. These platforms host numerous Indian-led projects and serve as collaborative hubs for developers across diverse technology landscapes.... - Source: dev.to / 2 months ago

• Where is Java Used in Industry?

  The rise of big data has seen Java arise as a crucial player in this domain. Tools like Hadoop and Apache Spark are built using Java, enabling businesses to process and analyze massive datasets efficiently. Java’s scalability and performance are critical for big data results that demand high trustability. - Source: dev.to / 5 months ago

• How to Install PySpark on Your Local Machine

  While Spark doesn’t strictly require Hadoop, many users install it for its HDFS (Hadoop Distributed File System) support. To install Hadoop:. - Source: dev.to / 5 months ago

• How I've implemented the Medallion architecture using Apache Spark and Apache Hdoop

  In this project, I'm exploring the Medallion Architecture which is a data design pattern that organizes data into different layers based on structure and/or quality. I'm creating a fictional scenario where a large enterprise that has several branches across the country. Each branch receives purchase orders from an app and deliver the goods to their customers. The enterprise wants to identify the branch that... - Source: dev.to / 11 months ago

• Navigating the Data Jungle. Data Analysis Software: A Comprehensive Guide

  Data analysis software is also widely used in the telecommunications industry to manage network performance, detect fraud, and analyze customer data. Telecommunications companies can use data analysis software to analyze network data in real-time, allowing them to identify and address issues quickly. In addition, data analysis software can help telecommunications companies identify new revenue streams and improve... - Source: dev.to / 11 months ago

• Getting thousands of files of output back from a container

  Did you check out tools like https://hadoop.apache.org/ ? Source: about 2 years ago

• 5 Best Practices For Data Integration To Boost ROI And Efficiency

  There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: about 2 years ago

• Data Engineering and DataOps: A Beginner's Guide to Building Data Solutions and Solving Real-World Challenges

  There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 2 years ago

• Effortlessly Set Up a Hadoop Multi-Node Cluster on Windows Machines with Our Step-by-Step Guide

  A copy of Hadoop installed on each of these machines. You can download Hadoop from the Apache website, or you can use a distribution like Cloudera or Hortonworks. - Source: dev.to / over 2 years ago

• In One Minute : Hadoop

  The Apache™ Hadoop™ project develops open-source software for reliable, scalable, distributed computing. - Source: dev.to / over 2 years ago

• A peek into Location Data Science at Ola

  This requires the use of distributed computation tools such as Spark and Hadoop, Flink and Kafka are used. But for occasional experimentation, Pandas, Geopandas and Dask are some of the commonly used tools. - Source: dev.to / over 2 years ago

• Big Data Processing, EMR with Spark and Hadoop | Python, PySpark

  Apache Hadoop is an open source framework that is used to efficiently store and process large datasets ranging in size from gigabytes to petabytes of data.Wanna dig more dipper? - Source: dev.to / about 3 years ago

• Unknown Python.exe process taking 2% CPU

  Few related projects too it on the side of the page here that might be familiar https://hadoop.apache.org/. Source: over 3 years ago

• How do I make multiple computers run as one?

  The computers that you have appear to use an x86 architecture. Therefore, you could most likely install a Linux distro on each one. Then, you could use something like Apache Hadoop to execute some sort of distributed process across each computer. Source: over 3 years ago

• Spark for beginners - and you

  Hadoop is an ecosystem of tools for big data storage and data analysis. It is older than Spark and writes intermediate results to disk whereas Spark tires to keep data in memory whenever possible, so this is faster in many use cases. - Source: dev.to / over 3 years ago

• Dreaming and Breaking Molds – Establishing Best Practices with Scott Haines

  So Yahoo bought that. I think it was 2013 or 2014. Timelines are hard. But I wanted to go join the Games team and start things back up. But that was also my first kind of experience in actually building recommendation engines or working with lots of data. And I think for me, like that was, I guess...at the time, we were using something called Apache Storm. We had Hadoop, which had been around for a while. And it... - Source: dev.to / over 3 years ago

• Spark is lit once again

  Here at Exacaster Spark applications have been used extensively for years. We started using them on our Hadoop clusters with YARN as an application manager. However, with our recent product, we started moving towards a Cloud-based solution and decided to use Kubernetes for our infrastructure needs. - Source: dev.to / over 3 years ago

• 5 Best Big Data Frameworks You Can Learn in 2021

  Both Fortune 500 and small companies are looking for competent people who can derive useful insight from their huge pile of data and that's where Big Data Framework like Apache Hadoop, Apache Spark, Flink, Storm, and Hive can help. - Source: dev.to / about 4 years ago

• The Data Engineering Interview Study Guide

  Some positions require Hadoop, others SQL. Some roles require understanding statistics, while still others require heavy amounts of system design. - Source: dev.to / about 4 years ago