Based on our record, Git seems to be a lot more popular than Amazon EMR. While we know about 232 links to Git, we've tracked only 10 mentions of Amazon EMR. 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.
Git is a distributed version control system that has become a standard tool in modern development practices. - Source: dev.to / 1 day ago
Git is the backbone for version control in our software development team. It allows us to track changes, revert to previous states, and efficiently manage multiple versions of project code. This tool is essential not only for its core functionality but also for supporting collaborative workflows among distributed team members. - Source: dev.to / 2 days ago
Before diving into the commands, ensure Git is installed on your machine. You can download it from the official Git website. - Source: dev.to / 6 days ago
Official Git Documentation: https://git-scm.com/ - The definitive source for all things Git, with in-depth explanations, commands, and tutorials. Interactive Git Training: https://learngitbranching.js.org/ - A hands-on platform to learn Git fundamentals and experiment with branching and merging in a simulated environment. Git SCM Blog: https://git-scm.com/ - Stay updated on the latest Git developments, news, and... - Source: dev.to / 15 days ago
Git: Version 2.28.0 or higher. Download from git-scm.com. - Source: dev.to / 18 days ago
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: over 1 year ago
I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 2 years ago
This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: about 2 years ago
Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago
Check out https://aws.amazon.com/emr/. Source: about 2 years ago
GitHub - Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Mercurial SCM - Mercurial is a free, distributed source control management tool.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
GitHub Desktop - GitHub Desktop is a seamless way to contribute to projects on GitHub and GitHub Enterprise.
Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost