Microsoft Research announced today on its website the preview of Project Daytona, an iterative MapReduce runtime for Windows Azure. Daytona was created by the eXtreme Computing Group and provides an alternative to Apache Hadoop, by using a set of tools for working with big data based on Google’s MapReduce. It is designed to help scientists take advantage of Azure for working with large and unstructured data sets.
Roger Barga explains: “‘Daytona’ has a very simple, easy-to-use programming interface for developers to write machine-learning and data-analytics algorithms. They don’t have to know too much about distributed computing or how they’re going to spread the computation out, and they don’t need to know the specifics of Windows Azure.”
The Daytona team also built an Azure-based analytics service called Excel DataScope which enables developers to simplify the process of working with big data by using an Excel-like interface.
Excel DataScope has the following features:
- Users can upload Excel spreadsheets to the cloud, along with metadata to facilitate discovery, or search for and download spreadsheets of interest.
- Users can sample from extremely large data sets in the cloud and extract a subset of the data into Excel for inspection and manipulation.
- An extensible library of data analytics and machine learning algorithms implemented on Windows Azure allows Excel users to extract insight from their data.
- Users can select an analysis technique or model from our Excel DataScope research ribbon and request remote processing. Our runtime service in Windows Azure will scale out the processing, by using possibly hundreds of CPU cores to perform the analysis.
- Users can select a local application for remote execution in the cloud against cloud scale data with a few mouse clicks, effectively allowing them to move the compute to the data.
- We can create visualizations of the analysis output and we provide the users with an application to analyze the results, pivoting on select attributes.
More on the Azure Research Engagement Click Here.
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