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Based on our record, Google BigQuery seems to be a lot more popular than .NET for Apache Spark. While we know about 35 links to Google BigQuery, we've tracked only 3 mentions of .NET for Apache Spark. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I assume you are talking about this https://dotnet.microsoft.com/en-us/apps/data/spark. Source: almost 2 years ago
Good question! The API and the authoring experience is .NET, but the backend is Apache Spark which is built on the JVM. We use the .NET for Apache Spark to do the parallization. Source: almost 2 years ago
Yes that's correct. SynapseML builds on top of the Apache Spark for .NET project which provides .NET support for the Apache Spark distributed computing framework. Apache Spark is written in Scala (a language on the JVM) but has language bindings in Python, R, .NET and other languages. This release adds full .NET language support for all of the models and learners in the SynapseML library so you can author... Source: almost 2 years ago
Using the Galaxy UI, knowledge workers can systematically review the best results from all configured services including Apache Solr, ChatGPT, Elastic, OpenSearch, PostgreSQL, Google BigQuery, plus generic HTTP/GET/POST with configurations for premium services like Google's Programmable Search Engine, Miro and Northern Light Research. - Source: dev.to / 9 months ago
Data Transformations: This phase involves modifying and integrating tables to generate new tables optimized for analytical use. Consider this example: you want to understand the purchasing behavior of customers aged between 20-30 in your online shop. This means you'll need to join product, customer, and transaction data to create a unified table for analytics. These data preparation tasks (e.g., joining... - Source: dev.to / 10 months ago
Introduction In today's data-driven world, transforming raw data into valuable insights is crucial. This process, however, often involves complex tasks that demand efficiency, scalability, and reliability. Enter dbt Cloud—a powerful tool that simplifies data transformations on Google BigQuery. In this article, we'll take you through a step-by-step guide on how to run BigQuery transformations using dbt Cloud.... - Source: dev.to / 10 months ago
You'll want to evaluate what BigQuery has to offer and see if it makes sense for you to move over. Source: 12 months ago
Watch the introductory videos on BigQuery on the Google Cloud Platform website (https://cloud.google.com/bigquery). Source: 12 months ago
Apache Flume - Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data
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Vertica - Vertica is a grid-based, column-oriented database designed to manage large, fast-growing volumes of...
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Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.