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Month: October 2019

Deploying a Container Instance in Azure

Anibal Kolker takes us through container deployment in Azure:

As derived from the title, the objective of this post is to help you deploy a container instance inside Azure.

However, we’ll extend the typical scenario and make a slightly more extensive use of networking capabilities, by placing the container group inside a private subnet.

Note: For this example, and for simplicity only, we’ll use NGINX as our container of choice. Of course, you’re welcome to try with any other image.

There are a few pieces in play, but Anibal does a good job putting it all together.

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A New Notebook Tool: Polynote

Jeremy Smith, et al, announce a new product:

We are pleased to announce the open-source launch of Polynote: a new, polyglot notebook with first-class Scala support, Apache Spark integration, multi-language interoperability including Scala, Python, and SQL, as-you-type autocomplete, and more.

Polynote provides data scientists and machine learning researchers with a notebook environment that allows them the freedom to seamlessly integrate our JVM-based ML platform — which makes heavy use of Scala — with the Python ecosystem’s popular machine learning and visualization libraries. It has seen substantial adoption among Netflix’s personalization and recommendation teams, and it is now being integrated with the rest of our research platform.

There are some nice pieces to it, especially around language interop.

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Head-to-Head Comparisons with Power BI

Rob Collie walks us through building a visual which provides head-to-head comparison using Power BI:

Yes, I know that NONE of the infographics above is a scientifically “good” comparison tool.  Too noisy, too flashy, not clean…  but every now and then you DO need to cater to your audience.  Engagement is the first step in the comprehension funnel, and in this particular example, yep, I’m trying to capture the eyeballs of an audience that likes this sort of thing.  The style of #4 is a decent compromise in this case.  Know your audience.

Rob takes us through an interesting journey. I don’t think I’d want to use that style too often, but to be fair, Rob talks about that in the snippet I clipped.

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Key Performance Indicator Transparency

Treb Gatte explains how to build trust in KPIs:

Many Power BI reports and dashboards have simple, color-based indicators, commonly referred to as Key Performance Indicators or KPIs. These indicators provide a way to communicate the current condition of a monitored metric.

These KPIs require the data consumer to:
– Trust the data used to calculate it
– Understand the rule used to derive the indicator
– Understand the calculation used to set the value

Read on for good questions and a recommended design. Trust is critical, as people won’t look at dashboards whose data they don’t trust.

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Storing Container Images in GitHub Package Registry

Andrew Pruski shows how we can use GitHub Package Registry to store private container images:

The GitHub Package Registry is available for beta testing and allows us to store container images in it, basically giving us the same functionality as the Docker Hub.

However the Docker Hub only allows for one private repository per free account whereas the Github package registry is completely private! Let’s run through a simple demo to create a registry and upload an image.

It’s pretty easy to set up, so check it out.

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Worker Migration in SQL Server 2019

Dong Cao explains an interesting improvement to SQL Server 2019’s internals:

Worker migration (AKA “worker stealing”) allows an idle SOS scheduler to migrate a worker from the runnable queue of another scheduler on the same NUMA node and immediately resume the task of the migrated worker. This enhancement provides more balanced CPU usage and reduces the amount of time long-running tasks spend in the runnable queue.
A long-running task that is enabled for worker migration is no longer bound to a fixed scheduler. Instead, it will frequently move across schedulers within the same NUMA node which naturally results in less loaded schedulers. Together with the existing load factor mechanism, worker migration provides SQL Server with an enriched solution for balanced CPU usage.

Click through to understand where this is particularly useful and what the performance implications are.

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Seeing Filter Results with DAX Measures

Gilbert Quevauvilliers wants to see the specific values involved in a Power BI filter:

I was working with a customer trying to get them to better understand DAX and one if the things that is difficult to understand is how the filtering works in DAX.

The challenge I have found is that when using filters in a DAX measure I cannot visually see what is happening within the DAX Filter.

Below I will show you how I can see the values in the FILTER

Click through to see how.

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rBokeh Tips for Missing Arguments

Matthias Nistler walks through troubleshooting rBokeh missing argument errors:

This approach is my go-to solution to change a rBokeh plot for which there is an argument missing in rBokeh that is available in python.
– Create the plot.
– Inspect the structure (str(plot)) of the rBokeh object.
– Search for the python’s argument name.
– Overwrite the value with the desired option as derived from python’s bokeh.

Given how nice the bokeh package looks, I really want rBokeh to work well. Hopefully this experience improves over time.

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JDBC Resource Pools and Kerberos

Guy Shilo has a tip for us around JDBC connectivity when your Hadoop cluster is configured for Kerberos:

This is a quick tip about connecting to Hive or Impala via JDBC.

Accessing hive or impala using their JDBC driver is very convenient. Client programs s like beeline or Jetbrains DataGrip use it as the main way of accessing Hive/Impala and many people also use it in their own written programs.

Things get a little trickier when the cluster is kerberized. In this case you should add few extra parameters to the JDBC connect string.

Read on to see what to do.

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