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Author: Kevin Feasel

RTVS 1.0

Shahrokh Mortazavi announces that R Tools for Visual Studio 1.0 is officially out:

RTVS builds on Visual Studio, which means you get numerous features for free: from using multiple languages to word-class Editing and Debugging to over 7,000 extensions for every need:

  • A polyglot IDE – VS supports R, Python, C++, C#, Node.js, SQL, etc. projects simultaneously.

  • Editor – complete editing experience for R scripts and functions, including detachable/tabbed windows, syntax highlighting, and much more.

  • IntelliSense – (aka auto-completion) available in both the editor and the Interactive R window.

  • R Interactive Window – work with the R console directly from within Visual Studio.

  • History window – view, search, select previous commands and send to the Interactive window.

  • Variable Explorer – drill into your R data structures and examine their values.

  • Plotting – see all of your R plots in a Visual Studio tool window.

  • Debugging – breakpoints, stepping, watch windows, call stacks and more.

  • R Markdown – R Markdown/knitr support with export to Word and HTML.

  • Git – source code control via Git and GitHub.

  • Extensions – over 7,000 Extensions covering a wide spectrum from Data to Languages to Productivity.

  • Help – use ? and ?? to view R documentation within Visual Studio.

I’ve been using it for a little while and it’s pretty snazzy for integrating with SQL Server R Services.  R Studio is still more feature-rich, but RTVS is definitely catching up.

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Datashader

John Mount is a bit jazzed when it comes to a new package:

I recently got back from Strata West 2017 (where I ran a very well received workshop on R and Spark). One thing that really stood out for me at the exhibition hall was Bokeh plus datashader from Continuum Analytics.

I had the privilege of having Peter Wang himself demonstrate datashaderfor me and answer a few of my questions.

I am so excited about datashader capabilities I literally will not wait for the functionality to be exposed in R through rbokeh. I am going to leave my usual knitr/rmarkdown world and dust off Jupyter Notebook just to use datashader plotting. This is worth trying, even for diehard R users.

For the moment, it looks like datashader is only available for Python, but it’s coming to R.

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SQL Server On VMware Guide

David Klee announces an update to VMware’s SQL Server best practices guide:

I am proud to announce that we contributed to the latest revision of the Microsoft SQL Server on VMware best practices guide, freely available at this address. This document outlines some of the common VM-level tweaks and adjustments that are made when running enterprise SQL Server VMs on VMware platforms. This guide is considered a must-read if you manage these sorts of SQL Servers, which cannot be treated as general purpose virtual machines.

This guide was recently updated for vSphere 6.5, and we consider it an absolute must for your enterprise management library!

If you manage SQL Server instances on VMware, it’s definitely worth the read.

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CHECKDB For Read-Only Databases?

Erik Darling answers a reader’s question:

So, can you run DBCC CHECKDB on a read only database? Should you run DBCC CHECKDB on a read only database?

tl;dr: YES AND YES!

Here’s why:
Many forms of corruption that I’ve seen have come from storage. Sure, there have been bugs that were to blame, but yeah. Most of the time, it’s the storage going all yucky.

Erik also explains some gotchas, so read the whole thing.

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Consuming Live Data Vs On-Prem Gateway

Gogula Aryalingam explains the difference between two Power BI features:

The question: “Why does it say ‘Consume live data sources with full interactivity’ as one feature while the other feature says ‘Access on-premise data using the Data Connectivity Gateways’, while it is obvious that if you need to connect to an on-premise data source to consume live data it has to be through a gateway?”

Okay, this is how I would explain this:

Read on for the explanation.

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Recovery Without Write-Ahead Logging

Kendra Little thinks about scenarios in which SQL Server is not able to do write-ahead logging (like with memory-optimized objects):

A few episodes ago, I talked about how learning about Write Ahead Logging was a light bulb moment for me, and helped me learn tons of concepts about backups and recovery. This week, we talk about when SQL Server turns things upside down and doesn’t use write ahead logging: and what it has to do for recovery in these special cases.

Watch this week’s 24 minute video. Subscribe to my YouTube channel, or check out the audio podcast to listen anywhere, anytime. Links from this episode are below the video.

Click through for the video.

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Scala + Hadoop + HDInsight

Emmanouil Gkatziouras shows that you can run a Hadoop job written in Scala on Azure’s HDInsight:

Previously, we set up a Scala application in order to execute a simple word count on Hadoop.

What comes next is uploading our application to HDInsight. So, we shall proceed in creating a Hadoop cluster on HDInsight.

Read the whole thing, but the upshot is that Scala apps build jar files just like Java would, so there’s nothing special about running them.

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Azure Elastic Pools

Derik Hammer explains what Azure SQL Database Elastic Pools do:

Azure SQL Database Elastic Pools are a mechanism for grouping your Azure SQL Databases together into a shared resource pool. Imagine for a moment that you had a physical server on premise. On that server, you have a single SQL Server instance and a single database. This example is similar to how Azure SQL Database works. You have a fixed amount of resources and you pay for those resources, even when you are not using them.

An Elastic Pool is analogous to that same server and instance, instead you add several databases to the instance. The databases will share the same resource pool which can be cheaper than paying for separate sets of resources, as long as your databases’ peak usage times do not align with each other.

Read on to see how you can potentially save money on databases using an elastic pool instead of spinning up the databases independently.

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Azure Managed Disks

Dave Bermingham explains what Azure Managed Disks are and why you might want to use them:

What’s Managed Disks you ask? Well, just on February 8th Corey Sanders announced the GA of Managed Disks. You can read all about Managed Disks here. https://azure.microsoft.com/en-us/services/managed-disks/

The reason why Managed Disks would have helped in this outage is that by leveraging an Availability Set combined with Managed Disks you ensure that each of the instances in your Availability Set are connected to a different “Storage scale unit”. So in this particular case, only one of your cluster nodes would have failed, leaving the remaining nodes to take over the workload.

Prior to Managed Disks being available (anything deployed before 2/8/2016), there was no way to ensure that the storage attached to your servers resided on different Storage scale units. Sure, you could use different storage accounts for each instances, but in reality that did not guarantee that those Storage Accounts provisioned storage on different Storage scale units.

Read on for more details.

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