Solved end-to-end Spark Streaming Projects

Solved
end-to-end
Spark Streaming Projects

Get ready to use coding projects for solving real-world business problems

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Spark Streaming Projects

 

In this Databricks Azure project, you will use Spark & Parquet file formats to analyse the Yelp reviews dataset. As part of this you will deploy Azure data factory, data pipelines and visualise the analysis.

This Elasticsearch example deploys the AWS ELK stack to analyse streaming event data. Tools used include Nifi, PySpark, Elasticsearch, Logstash and Kibana for visualisation.

Learn to perform 1) Twitter Sentiment Analysis using Spark Streaming, NiFi and Kafka, and 2) Build an Interactive Data Visualization for the analysis using Python Plotly.

In this Spark project, we are going to bring processing to the speed layer of the lambda architecture which opens up capabilities to monitor application real time performance, measure real time comfort with applications and real time alert in case of security

In this hadoop project, you will be using a sample application log file from an application server to a demonstrated scaled-down server log processing pipeline.

In this big data project, we will embark on real-time data collection and aggregation from a simulated real-time system using Spark Streaming.

The goal of this apache kafka project is to process log entries from applications in real-time using Kafka for the streaming architecture in a microservice sense.

The goal of this hadoop project is to apply some data engineering principles to Yelp Dataset in the areas of processing, storage, and retrieval.

Spark Project - Discuss real-time monitoring of taxis in a city. The real-time data streaming will be simulated using Flume. The ingestion will be done using Spark Streaming.

In this spark streaming project, we are going to build the backend of a IT job ad website by streaming data from twitter for analysis in spark.

The goal of this IoT project is to build an argument for generalized streaming architecture for reactive data ingestion based on a microservice architecture. 

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