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If big data is your thing, you use R, and you’re headed to Strata + Hadoop World in San Jose March 13 & 14th, you can experience in person how easy and practical it is to analyze big data with R and Spark.

In a beginner level talk by RStudio’s Edgar Ruiz and an intermediate level  workshop by Win-Vector’s John Mount, we cover the spectrum: What R is, what Spark is, how Sparklyr works, and what is required to set up and tune a Spark cluster. You’ll also learn practical applications including: how to quickly set up a local Spark instance, store big data in Spark and then connect to the data with R, use R to apply machine-learning algorithms to big data stored in Spark, and filter and aggregate big data stored in Spark and then import the results into R for analysis and visualization.

2:40pm–3:20pm Wednesday, March 15, 2017
Sparklyr: An R interface for Apache Spark
Edgar Ruiz (RStudio)
Primary topic: Spark & beyond
Location: LL21 C/D
Level: Beginner
Secondary topics: R

1:30pm–5:00pm Tuesday, March 14, 2017
Modeling big data with R, sparklyr, and Apache Spark
John Mount (Win-Vector LLC)
Primary topic: Data science & advanced analytics
Location: LL21 C/D
Level: Intermediate
Secondary topics: R

While you’re  at the conference be sure to look us up in the Innovator’s Pavilion – booth number P8 during the Expo Hall hours. We’ll have the latest books from RStudio authors, t-shirts to win, demonstrations of RStudio Connect and RStudio Server Pro and, of course, stickers and cheatsheets. Share with us what you’re doing with RStudio and get your product and company questions answered by RStudio employees.

See you in San Jose! (https://conferences.oreilly.com/strata/strata-ca)

We’re excited to announce the latest release of RStudio Connect: version 1.4.2. This release includes a number of notable features including an overhauled interface for parameterized R Markdown reports.

Enhanced Parameterized R Markdown Reports

Enhanced Parameterized R Markdown Reports

The most notable feature in this release is the ability to publish parameterized R Markdown reports that are easier for anyone to customize. If you’re unfamiliar, parameterized R Markdown reports allow you to inject input parameters into your R Markdown document to alter what analysis the report performs. The parameters of your R Markdown report are now visible on the left-hand sidebar, allowing users to easily tweak the inputs to the document and quickly view the output in the browser.

Users even have the opportunity to create private versions of the report which they can schedule to run again, email, or save and revisit in the browser. Of course, you can continue to use the wide variety of output formats (notebooks, dashboards, books, and others) while using parameterized R Markdown.

In addition to the parameterized report overhaul, there are some other notable features included in this release.

  • Content private by default – Content is set to private (“Just Me”) by default. Users can still change the visibility of their content before publishing, as before.
  • Execute R as the authenticated viewer – You can now choose to have some applications execute their underlying R process as the authenticated viewer currently looking at the app. This allows applications to access any data or resource that the associated user has access to on the server. Requires PAM authentication. More details here.

Other important features include:

  • Show progress indicator when updating a report.
  • Users can now filter content to include only items that they can edit or view.
  • Users now only count against the named user license limit after they log in for the first time.
  • Added support for global “System Messages” that can display an HTML message to your users on the landing pages. Details here.
  • Updated packrat to gain more transparency on package build errors.
  • Updated the list of SSL ciphers to correspond with modern best-practices.

If you haven’t yet had a chance to download and try RStudio Connect we encourage you to do so. RStudio Connect is the best way to share all the work that you do in R (Shiny apps, R Markdown documents, plots, dashboards, etc.) with collaborators, colleagues, or customers.

You can find more details or download a 45 day evaluation of the product at https://www.rstudio.com/products/connect/. Additional resources can be found below.

We’re thrilled to officially introduce the newest product in RStudio’s product lineup: RStudio Connect.

You can download a free 45-day trial of it here.

RStudio Connect is a new publishing platform for all the work your teams do in R. It provides a single destination for your Shiny applications, R Markdown documents, interactive HTML widgets, static plots, and more.

RStudio Connect Settings

RStudio Connect isn’t just for R users. Now anyone can interact with custom built analytical data products developed by R users without having to program in R themselves. Team members can receive updated reports built on the same models/forecasts which can be configured to be rebuilt and distributed on a scheduled basis. RStudio Connect is designed to bring the power of data science to your entire enterprise.

RStudio Connect empowers analysts to share and manage the content they’ve created in R. Users of the RStudio IDE can publish content to RStudio Connect with the click of a button and immediately be able to manage that content from a user-friendly web application: setting access controls and performance settings and viewing the logs of the associated R processes on the server.

Deploying content from the RStudio IDE into RStudio Connect

RStudio Connect is on-premises software that you can install on a server behind your firewall ensuring that your data and R applications never have to leave your organization’s control. We integrate with many enterprise authentication platform including LDAP/Active Directory, Google OAuth, PAM, and proxied authentication. We also provide an option to use an internal username/password system complete with user self-sign-up.

RStudio Connect Admin Metrics

RStudio Connect has been in Beta for almost a year. We’ve had hundreds of customers validate and help us improve the software in that time. In November, we made RStudio Connect generally available without significant fanfare and began to work with Beta participants and existing RStudio customers eager to move it into their production environments. We are pleased that innovative early customers, like AdRoll, have already successfully introduced RStudio Connect into their data science process.

“At AdRoll, we have used the open source version of Shiny Server for years to great success but deploying apps always served as a barrier for new users. With RStudio Connect’s push button deployment from the RStudio IDE, the number of shiny devs has grown tremendously both in engineering and across teams completely new to shiny like finance and marketing. It’s been really powerful for those just getting started to be able to go from developing locally to sharing apps with others in just seconds.”

– Bryan Galvin, Senior Data Scientist, AdRoll

We invite you to take a look at RStudio Connect today, too!

You can find more details or download a 45 day evaluation of the product at https://www.rstudio.com/products/connect/. Additional resources can be found below.

RStudio is excited to announce the general availability (GA) of shinyapps.io.

Shinyapps.io is an easy to use, secure, and scalable hosted service already being used by thousands of professionals and students to deploy Shiny applications on the web. Effective today, shinyapps.io has completed beta testing and is generally available as a commercial service for anyone.

As regular readers of our blog know, Shiny is a popular free and open source R package from RStudio that simplifies the creation of interactive web applications, dashboards, and reports. Until today, Shiny Server and Shiny Server Pro were the most popular ways to share shiny apps. Now, there is a commercially supported alternative for individuals and groups who don’t have the time or resources to install and manage their own servers.

We want to thank the nearly 8,000 people who created at least one shiny app and deployed it on shinyapps.io during its extensive alpha and beta testing phases! The service was improved for everyone because of your willingness to give us feedback and bear with us as we continuously added to its capabilities.

For R users developing shiny applications that haven’t yet created a shinyapps.io account, we hope you’ll give it a try soon!  We did our best to keep the pricing simple and predictable with Free, Basic, Standard, and Professional plans. Each paid plan has features and functionality that we think will appeal to different users and can be purchased with a credit card by month or year. You can learn more about shinyapps.io pricing plans and product features on our website.

We hope to see your shiny app on shinyapps.io soon!

Registration is now open for the next Master R Development workshop led by Hadley Wickham, author of over 30 R packages and the Advanced R book. The workshop will be held on January 19 and 20th in the San Francisco bay area.

The workshop is a two day course on advanced R practices and package development. You’ll learn the three main paradigms of R programming: functional programming, object oriented programming and metaprogramming, as well as how to make R packages, the key to well-documented, well-tested and easily-distributed R code.

To learn more, or register visit rstudio-sfbay.eventbrite.com.

We are happy to announce the availability of v1.1 of RStudio Shiny Server Pro, our commercial server for deploying Shiny applications.  In this release we took your feedback and made it easier for you to integrate Shiny Server Pro into your production environments.  With Shiny Server Pro v1.1 you now can:

  • Control access to your applications with Google Authentication (OAuth2).
  • Create sessions and authenticate with PAM (auth_pam and pam_sessions_profile).
  • Set the version of R that is used per application and/or per user
  • Customize page templates for directory listings and error pages.
  • Monitor service health and get additional metrics with a new health check endpoint.
  • Provide custom environment variables to a Shiny process using Bash profiles
  • Configure apps to run using the authenticated user’s account with custom environment variables from Bash or PAM
  • Launch Shiny apps with a prefix command such as ‘nice’ allowing you to prioritize compute resources per application or  per user

If you haven’t tried Shiny Server Pro yet, download a copy here.