Tag: Python
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Ingest Azure Event Hub Telemetry Data with Apache PySpark Structured Streaming on Databricks.
Overview. Ingesting, storing and processing millions of telemetry data from a plethora of remote IoT devices and Sensors has become common place. One of the primary Cloud services used to process streaming telemetry events at scale is Azure Event Hub. Most documented implementations of Azure Databricks Ingestion from Azure Event Hub Data are based on…
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Incrementally Process Data Lake Files Using Azure Databricks Autoloader and Spark Structured Streaming API.
Use Case. In this post, I will share my experience evaluating an Azure Databricks feature that hugely simplified a batch-based Data ingestion and processing ETL pipeline. Implementing an ETL pipeline to incrementally process only new files as they land in a Data Lake in near real time (periodically, every few minutes/hours) can be complicated. Since…
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Data Preparation of PySpark Dataframes in Azure Databricks Cluster using Databricks Connect.
In my limited experience with processing big data workloads on the Azure Databricks platform powered by Apache Spark, it has become obvious that a significant part of the tasks are targeted towards Data Quality. Data quality in this context mostly refers to having data that is free of errors, inconsistencies, redundancies, poor formatting and other…
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Automate Azure Databricks Job Execution using Custom Python Functions.
Introduction Thanks to a recent Azure Databricks project, I’ve gained insight into some of the configuration components, issues and key elements of the platform. Let’s take a look at this project to give you some insight into successfully developing, testing, and deploying artifacts and executing models. One note: This post is not meant to be…
Chinny Chukwudozie, Cloud Solutions. 