Senior Data Scientist, Mawdoo3 Ltd
Data Scientist, Credit Suisse
Head of Data science, OutFund
Big Data Engineer, Beyond Limits
In this big data project, you will learn how to process data using Spark and Hive as well as perform queries on Hive tables.
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Business Overview:
In this project, we will perform data processing and analysis on Yelp dataset using Spark and Hive. For this project, we will use Amazon EMR which is an alternative to the Hadoop cluster in AWS and S3 where our data is stored.
Yelp is a community review site and an American multinational firm based in San Francisco, California. It publishes crowd-sourced reviews of local businesses as well as the online reservation service Yelp Reservations. Yelp has made a portion of their data available in order to launch a new activity called the Yelp Dataset Challenge, which allows anyone to do research or analysis to find what insights are buried in their data. Due to the bulk of the data, this project only selects a subset of Yelp data. User and Review dataset is considered for this session.
Tech Stack:
Language: Spark, Scala.
Services: Amazon EMR, Hive, HDFS, AWS S3
Approach:
Create a S3 bucket and upload files
Create a keypair in EC2
Create an EMR cluster with master and slave nodes along with Spark, Hive components
Basic Dataframe operations like Read and write to tables and hdfs locations
Hive Integration from spark
Normalizing data using RDD operations
Normalizing data using Dataframe operation
Note: You can download dataset from this link.
Architecture Diagram:
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