Episode
Data ingestion, stream processing and sentiment analysis pipeline using Twitter data example
Follow the conversation between Lena and Suz and learn about setting up a data ingestion and processing system consisting of event producer, reliable event aggregation and consumer using Twitter client, Event Hubs and Spark on Azure Databricks as an example. Lena and Suz are also discussing alternative options for stream processing, and how it can be used for various scenarios, including IoT, and how to apply machine learning to streaming data by showing an example of sentiment analysis on tweets coming in real-time.
Useful links:
https://lenadroid.github.io/posts/connecting-spark-and-eventhubs.html
https://lenadroid.github.io/posts/offset-enqueuetime-spark-eventhubs.html
https://lenadroid.github.io/posts/sentiment-analysis-streaming-data.html
Follow the conversation between Lena and Suz and learn about setting up a data ingestion and processing system consisting of event producer, reliable event aggregation and consumer using Twitter client, Event Hubs and Spark on Azure Databricks as an example. Lena and Suz are also discussing alternative options for stream processing, and how it can be used for various scenarios, including IoT, and how to apply machine learning to streaming data by showing an example of sentiment analysis on tweets coming in real-time.
Useful links:
https://lenadroid.github.io/posts/connecting-spark-and-eventhubs.html
https://lenadroid.github.io/posts/offset-enqueuetime-spark-eventhubs.html
https://lenadroid.github.io/posts/sentiment-analysis-streaming-data.html
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