RBloggers|RBloggers-feedburner RAthena 1.7.1 and noctua 1.5.1 package versions have now been released to the CRAN. They both bring along several improvements with the connection to AWS Athena, noticeably the performance speed and several creature comforts. These packages have both been designed to reflect one another,even down to how they connect to AWS Athena. This means that all features going forward will exist in both packages. I will refer to these packages as one, as they basically work in the same way.
RBloggers|RBloggers-feedburner Intro: After developing the package RAthena, I stumbled quite accidentally into the R SDK for AWS paws. As RAthena utilises Python’s SDK boto3 I thought the development of another AWS Athena package couldn’t hurt. As mentioned in my previous blog the paws syntax is very similar to boto3 so alot of my RAthena code was very portable and this gave me my final excuse to develop my next R package.
RBloggers|RBloggers-feedburner Intro: For a long time I have found it difficult to appreciate the benefits of “cloud compute” in my R model builds. This was due to my initial lack of understanding and the setting up of R on cloud compute environments. When I noticed that AWS was bringing out a new product AWS Sagemaker, the possiblities of what it could provide seemed like a dream come true. Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.