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Day: April 15, 2022

Retrieving Twitter Engagements in R

Bryan Shalloway continues looking at Twitter data:

This is a follow-up to a short post I wrote on R Access to Twitter’s v2 API. In this post I’ll walk through a few more examples of pulling data from twitter using a mix of Twitter’s v2 API as well as the {rtweet} package.

I’ll pull all Twitter users that I (brshallo) have recently been engaged by (e.g. they like my tweet) or engaged with (e.g. I like their tweet). I’ll lean towards using {rtweet} but will use {httr} in cases where it’s more convenient to use Twitter’s v2 API.

Click through for more information, including several R scripts.

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Downloading Power BI Reports with Powershell

Jon Fletcher needs to get some PBIX files:

In this blog post I will be sharing a PowerShell script that allows multiple Power BI reports to be downloaded at once.

In the Power BI service, there is no way of downloading multiple Power BI reports at once. Therefore, users must download files one by one which is slow, time consuming and inefficient. Thankfully, there are ways around this, one of which is using PowerShell.

Read on for the script and some additional notes.

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Streaming Data into Synapse Dedicated SQL Pool

Lionel Penuchot loads some data:

This article reviews a common pattern of streaming data (i.e. real-time message ingestion) in Synapse dedicated pool. It opens a discussion on the simple standard way to implement this, as well as the challenges and drawbacks. It then presents an alternate solution which enables optimal performance and greatly reduces maintenance tasks when using clustered column store indexes. This is aimed at developers, DBAs, architects, and anyone who works with streams of data that are captured in real-time.

I’d probably avoid the MERGE statement in there because of how many problems there are with it. That said, this is a useful pattern for trickle-loading columnstore tables.

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Making Redis Do Your Bidding

Arun Sirpal looks at some of the command language for Azure Redis:

Now that we have created our Redis Cache lets connect to it. You can use the most common tool redis cli.exe or as I am going to do, use the Azure Portal to use the console directly, this isn’t probably the best way but it’s the easiest for this blog. 2 key points here:

Read on for those points, as well as examples of commands you can run.

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