Using RxOdbcData with Oracle Wallet

In Microsoft R Server you can use RxOdbcData class to connect to an ODBC DataSource, for example a table in an Oracle database. At times some of our customer’s have a requirement to hide the credentials for their Oracle database (username and password) in the connection string they specify when writing an R script in…

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Using RStudio Server with Microsoft R Server Parcel for Cloudera

In previous releases of Microsoft R Server, parcel installation required downloading two pre-built parcel files. The 9.1 release improves upon this experience by providing a parcel generator script generate_mrs_parcel.sh to generate a single MRS-9.1.0-*.parcel file. Here are the complete instructions to install MRS Parcel in Cloudera Cluster. In this article we will look into how to…


New Features in 9.1: Microsoft R Server with sparklyr Interoperability

Introduction With the launch of Microsoft R Server 9.1, many optimizations and new features were delivered to our users. One key feature is interoperability between Microsoft R Server and sparklyr. sparklyr, a package by RStudio, is an R interface to Apache Spark. It allows users to utilize Spark as the backend for dplyr, one of…


Role Based Access Control With MRS 9.1.0

In the latest release of Microsoft R Server 9.1 we can configure role based access control (RBAC) for users who can publish, modify and delete the web services. There are three roles in MRS 9.1 and each role has defined set of permissions for what they can do and what they cannot do. Owner: users…


REST Calls using PostMan for R server O16N

The Microsoft R Server operationalization REST APIs are exposed by R Server’s operationalization server, a standards-based server technology capable of scaling to meet the needs of enterprise-grade deployments. With the operationalization feature configured, the full statistics, analytics and visualization capabilities of R can now be directly leveraged inside Web, desktop and mobile applications. Core Operationalization…


Classify Yelp restaurant reviews’ food origin with MicrosoftML

Yelp restaurant reviews are one of the most useful resources people use to pick restaurants. Reviews themselves not only carry sentiment towards the dining experience but also contain “meta-information” about the restaurant. For example, looking at a review that says We can tell that this is a Japanese restaurant since it mentions omakase and sushi. Natural language processing and machine…

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Microsoft R Server – Using Hive data source in Spark compute context

Before Microsoft R Server 9.0 release, if you needed to perform analytics on your Hive or Parquet data you had to first manually export to some supported format (e.g., csv) and then use something like RxTextData to perform analytics after potentially uploading the text data to HDFS. With Microsoft R Server 9.0 release, Spark compute…

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Microsoft R Server Operationalization Examples

Today, more and more businesses are adopting advanced analytics for mission critical decision making in areas such as fraud detection, healthcare and manufacturing. Typically, the data scientists first build out the predictive models and only then can businesses deploy those models in a production environment and consume them for predictive actions Here are few examples…


Data Transformation in Function rxDataStep

Microsoft R Server supports four cases of R transformations, such as transformFunc, transforms (lists of transform statements), rowSelection (a logical expression) and in-line expressions in formulas. In this article, let’s focus on how to use “transforms” and “transformFunc” to do variable transformation. For all the following example, we use a RxSqlServerData source from the test database…

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Predicting NYC Taxi Tips using MicrosoftML

MicrosoftML is a new package for Microsoft R Server that adds state-of-the-art algorithms and data transforms to Microsoft R Server functionality. MicrosoftML includes these algorithms: Fast linear learner, with support for L1 and L2 regularization. Fast boosted decision tree. Fast random forest. Logistic regression, with support for L1 and L2 regularization. GPU-accelerated Deep Neural Networks…