Angular version 4.3 has been released. This is a minor release following our announced adoption of Semantic Versioning, meaning that it contains no breaking changes and that it is a drop-in replacement for 4.x.x.What’s new?
- We are introducing HttpClient, a smaller, easier to use, and more powerful library for making HTTP Requests. Learn more about it from our docs
- New router life cycle events for Guards and Resolvers. Four new events: GuardsCheckStart, GuardsCheckEnd, ResolveStart, ResolveEnd join the existing set of life cycle event such as NavigationStart
- Conditionally disable animations via a new attribute, [@.disabled]
- Support for the emulated /deep/ CSS Selector (the Shadow-Piercing descendant combinator aka >>>) has been deprecated to match browser implementations and Chrome’s intent to remove. ::ng-deep has been added to provide a temporary workaround for developers currently using this feature.For the complete list of features and bugfixes please see the changelog.
Kirill Gavrylyuk stops by Azure Friday to talk Cosmos DB with Scott Hanselman.
Watch this quick overview of the industry’s first globally distributed multi-model database service followed by a demo of moving an existing MongoDB app to Cosmos DB with a single config change.
For more information, see: https://azure.microsoft.com/en-us/services/cosmos-db/
Azure Cosmos DB is a globally distributed multi-model database with support for multiple APIs. This is a link to an article which describes how to use REST to query resources using the Azure Cosmos DB API – https://docs.microsoft.com/en-us/rest/api/documentdb/querying-documentdb-resources-using-the-rest-api
All Cosmos DB resources (with the exception of account resources) can be queried using Azure Cosmos DB SQL language. See Query with Azure Cosmos DB SQL for additional details on syntax – http://azure.microsoft.com/documentation/articles/documentdb-sql-query
For a full sample using .NET visit https://github.com/Azure/azure-documentdb-dotnet/tree/master/samples/rest-from-.net
Configuring Power BI Gateway Data Sources For Files And Folders
by Chris Webb
… “building a lot of Power BI reports from csv and Excel files, and to make sure that scheduled refresh works I have been setting up data sources in an On Premises Data Gateway (what used to be called the Enterprise Gateway). I had assumed that if I was connecting to file-based data sources in my Power BI dataset then, in the gateway, I would need to set up one data source for each file that I’m connecting to – which is a bit of a pain. In fact it turns out that you can set up a gateway data source for the folder that the files are in instead” … https://blog.crossjoin.co.uk/2017/07/14/configuring-power-bi-gateway-data-sources-for-files-and-folders/
Recently I’ve been building a lot of Power BI reports from csv and Excel files, and to make sure that scheduled refresh works I have been setting up data sources in an On Premises Data Gateway (what used to be called the Enterprise Gateway). I had assumed that if I was connecting to file-based data sources in my Power BI dataset then, in the gateway, I would need to set up one data source for each file that I’m connecting to – which is a bit of a pain. In fact it turns out that you can set up a gateway data source for the folder that the files are in instead.
Let me give you an example. Imagine that you have three Excel files in a folder called C:Sales Data:
Now imagine that you have three queries in Power BI that get data from these three files:
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24 Hours of PASS features free educational webinars delivered over 24 hours. Topics covered in this edition include Performance Tuning, SQL Server 2017, Linux, DevOps, Azure, PowerShell, SSRS, Power BI and much more. Browse all sessions @ http://www.pass.org/24hours/2017/summitpreview/Schedule.aspx
“Microsoft has released Seeing AI — a smartphone app that uses computer vision to describe the world for the visually impaired. With the app downloaded, the users can point their phone’s camera at a person and it’ll say who they are and how they’re feeling. They can also point it at a product and it’ll tell them what it is. All of this is done using artificial intelligence that runs locally on their phone”…
R is the latest language added to Apache Spark, and the SparkR API is slightly different from PySpark. SparkR’s evolving interface to Apache Spark offers a wide range of APIs and capabilities to Data Scientists and Statisticians. With the release of Spark 2.0, and subsequent releases, the R API officially supports executing user code on distributed data. This is done primarily through a family of apply() functions.
In this Data Science Central webinar, we will explore the following:
• Provide an overview of this new functionality in SparkR
• Show how to use this API with some changes to regular code with apply()
• Focus on how to correctly use this API to parallelize existing R packages
• Consider performance and examine correctness when using the apply() family of functions in SparkR
Hossein Falaki, Software Engineer — Databricks Inc.
Hosted by: Bill Vorhies, Editorial Director — Data Science Central
Title: Parallelize R Code Using Apache® Spark™
Date: Tuesday, August 15th, 2017
Time: 9:00 AM – 10:00 AM PDT
These two articles for Node.js and Java are tutorials that explores how to use Microsoft Azure Cosmos DB to store and access data from a Node.js Express or Java web application hosted on Azure Websites.
“Before Excel and other data-linked spreadsheets, business reports needed to be hand-crafted by IT experts, and changes were arbitrated slowly via change control. Power BI was designed to take the liberation that Excel pioneered to the max, by allowing ‘power’ users to not only to create Power BI desktop reports, graphics and visualizations in Power BI App, but then link and publish these to the Power BI app. These in turn can be given row level security and have their underlying data kept up-t…”
The Azure Cosmos DB Emulator provides a local development environment that emulates the Azure Cosmos DB service. Using this you can develop and test your application locally, without the need for an Azure subscription or incurring any costs. Once development is complete and you are ready, you can switch across to using an Azure Cosmos DB account in the cloud.
This is a handy article which covers the following tasks:
- Installing the Emulator
- Running the Emulator on Docker for Windows
- Authenticating requests
- Using the Data Explorer in the Emulator
- Exporting SSL certificates
- Calling the Emulator from the command line
- Collecting trace files
There are some limitations to the Emulator, when compared to the highly scalable cloud version, below is an outline of some of the differences…
|Azure Cosmos DB Emulator||Azure Cosmos DB Cloud Service|
|Supports only a single fixed account and a well-known master key. Key regeneration is not possible.||Supports multiple accounts and different master keys. You can regenerate keys any time from Azure Portal|
|Non scalable.||Highly scalable|
|Does not support larger data sets.||Support for large data sets|
|Does not simulate consistency levels.||Different Consistency levels available|
|Does not simulate multi-region replication.||Configurable as part of the platform, as needed basis|
|Does not support quota override feature.||Supports document size limit increases, increased partitioned collection storage etc.|
|Will not support most recent changes to Cosmos DB platform.||Most recent platform updates are available|