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Author: Kevin Feasel

GPU-Accelerated Analysis on Databricks using PyTorch + Huggingface

Published 2021-11-01 by Kevin Feasel

Srijith Rajamohan walks us through an example of sentiment analysis using the PyTorch and Huggingface libraries on Databricks:

Sentiment analysis is commonly used to analyze the sentiment present within a body of text, which could range from a review, an email or a tweet. Deep learning-based techniques are one of the most popular ways to perform such an analysis. However, these techniques tend to be very computationally intensive and often require the use of GPUs, depending on the architecture and the embeddings used. Huggingface (https://huggingface.co) has put together a framework with the transformers package that makes accessing these embeddings seamless and reproducible. In this work, I illustrate how to perform scalable sentiment analysis by using the Huggingface package within PyTorch and leveraging the ML runtimes and infrastructure on Databricks.

Click through for a description of the process, as well as a link to a notebook you can walk through yourself.

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Data Source Name Not Found with Postgres Driver

Published 2021-11-01 by Kevin Feasel

Rayis Imayev troubleshoots a problem:

A very short blog post, just a reminder to myself, but if you have ever tried to connect to a PostgreSQL database using ODBC interface (I know, it already sounds like a very interesting challenge :- ), then you might have experienced this error message: “ERROR [IM002] [Microsoft][ODBC Driver Manager] Data source name not found and no default driver specified.”

Read on to see the cause of and solution to this problem.

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Showing Count of Selected Items in a Slicer

Published 2021-11-01 by Kevin Feasel

Prathy Kamasani wants to track slicer counts:

In one of the projects, I was working on, I received feedback saying it is hard to understand how many items they have selected in a slicer, and it is not the first time I came across this. It is a valid point, especially when you have quite a few items in a slicer, you use a search bar to look for items, you select a couple, but you were not sure how many were selected.

Read on for a rather clever solution to the problem.

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A Primer on Kafka Streams

Published 2021-10-29 by Kevin Feasel

Bill Bejeck has an introduction to Kafka Streams:

Kafka Streams is an abstraction over Apache Kafka® producers and consumers that lets you forget about low-level details and focus on processing your Kafka data. You could of course write your own code to process your data using the vanilla Kafka clients, but the Kafka Streams equivalent will have far fewer lines, because it’s declarative rather than imperative. As a library, Kafka Streams lets you create a standalone application that can be run anywhere that can connect to a Kafka broker, whether that’s a laptop or a hefty cloud server. You just need to provide it with the host and port name of a broker. Combining Kafka Streams with Confluent Cloud grants you even more processing power with very little code investment.

Click through for a description as well as a whole series of embedded videos.

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Automating Single Table Refresh with Azure Data Factory and Azure Automation

Published 2021-10-29 by Kevin Feasel

Marc Lelijveld wants to refresh a single table:

Back in February, I wrote a blog on how you can trigger a single table to refresh in your Power BI data model. This blog described how you can achieve this goal using a PowerShell script and the ASCmd cmdlets for Analysis Services, which also works for Power BI Premium. In the wrap-up of that blog, I promised to follow-up with a blog on how to achieve the same goal with Azure Data Factory. It took a little bit longer than expected to finalize this post, but here it is!

In this blog, co-authored by my colleague Paulien van Eijk, we will describe how you can automate your single table refresh in the Power BI Service, including all dependencies with downstream dataflows using Azure Data Factory and Azure Automation. All this is based on real life scenarios and a solution build in collaboration between Dave Ruijter, Paulien and me.

Read on for Marc and Paulien’s solution.

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From Kafka to Azure Data Explorer

Published 2021-10-29 by Kevin Feasel

Niels Berglund uses Kafka Connect to link an Apache Kafka topic to Azure Data Explroer:

If you follow my blog, you probably know that I am a huge fan of Apache Kafka and event streaming/stream processing. Recently Azure Data Explorer (ADX) has caught my eye. In fact, in the last few weeks, I did two conference sessions about ADX. A month ago, I published a blog post related to Kafka and ADX: Run Self-Managed Kusto Kafka Connector Serverless in Azure Container Instances.

As the title of that post implies, it looked at the ADX Kafka sink connector and how to run it in Azure. What the post did not look at was how to configure the connector and connect it to ADX. That is what we will do in this post (and maybe in a couple of more posts).

This post serves as a complete tutorial, though Niels does promise future posts on other ingestion methods, so stay tuned.

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An Overview of Azure Logic Apps

Published 2021-10-29 by Kevin Feasel

Elayne Jones takes us through the use case for Azure Logic Apps:

Relying on automated workflows, instead of human intervention, ensures data consistency and availability. Automated workflows are, therefore, an integral piece of a sophisticated Modern Data Platform. Now, thanks to Azure Logic Apps, creating a complex workflow is no longer a daunting technical challenge!

Read on to see how they work, what kinds of connectors are available, and the sorts of things you can build with it.

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