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This has been a motivating experience. This has helped me execute Pig Latin and Hive commands to solve data problems. They take special care in regards to answering any questions and doubts I had... Read More
My Interaction was very short but left a positive impression. I enrolled and asked for a refund since I could not find the time. What happened next: They initiated Refund immediately. Their... Read More
A notebook is a code execution environment that allows for creating, sharing code and its execution, visualization and other text information (like markups). It enables an interactive computing in the area of data exploration or analysis. It is logical to a sharable Grunt shell for Pig, or scala shell and PySpark shell for Spark, or beeline for Hive but with visualization, discovery and collaboration.
In this big data Project, we will talk about one of this notebook - Apache Zeppelin. With Zeppelin, we will do a number of data analysis by answering some questions on the crime dataset using Hive, Spark and Pig. We will prepare some chart to better represent our results and finally share our results with the collaborative or sharing feature of the notebook.
On completing this big data project using zeppelin, participants will have known what Zeppelin is, gained the ability to install new interpreters, use Zeppelin for performing data analysis, sharing results with their friends or colleagues. Also, the participant will be informed of other notebooks in the data ecosystem like Jupyter or the databricks cloud notebooks.
This Elasticsearch example deploys the AWS ELK stack to analyse streaming event data. Tools used include Nifi, PySpark, Elasticsearch, Logstash and Kibana for visualisation.
Explore hive usage efficiently in this hadoop hive project using various file formats such as JSON, CSV, ORC, AVRO and compare their relative performances
In this big data project, we will discover songs for those artists that are associated with the different cultures across the globe.