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In this big data project we build a live workflow for a real project using Apache Airflow which is the new edge workflow management platform. We will go through the use cases of workflow, different tools available to manage workflow, important features of workflow like CLI and UI and how Airflow is differnt. We will install Airflow and run some simple workflows.
In this big data hadoop project, we will download the raw page counts data from wikipedia archieve and we will process them via Hadoop. Then map that processed data to raw SQL data to identify the most lived up pages of a given day. Then we will visualize the proecessed data via Zeppelin Notebooks to identify the daily trends. We will use Qubole to power up Hadoop and Notebooks.
All steps like downloading, copying data to S3, creating tables and processing them via Hadoop would be task in Airflow and we will learn how to craft scheduled workflow in Airflow.
Hive Project- Understand the various types of SCDs and implement these slowly changing dimesnsion in Hadoop Hive and Spark.
Use the dataset on aviation for analytics to simulate a complex real-world big data pipeline based on messaging with AWS Quicksight, Druid, NiFi, Kafka, and Hive.
In this Apache Spark SQL project, we will go through provisioning data for retrieval using Spark SQL.