BD4211 Big Data Mining and Analytics Laboratory Syllabus:

BD4211 Big Data Mining and Analytics Laboratory Syllabus – Anna University PG Syllabus Regulation 2021

COURSE OBJECTIVES:

 To learn to process big data using Hadoop framework and MapReduce.
 To analyze big data using classification and clustering techniques.
 To realize storage of big data using MongoDB and Hbase.
 To develop big data applications for streaming data using Apache Spark.

LIST OF EXPERIMENTS:

1. Install, configure and run Hadoop and HDFS.
2. Implement word count / frequency programs using MapReduce(MR).
3. Implement an MR program that processes a weather dataset.
4. Implement SVM and clustering techniques using R.
5. Visualize data using any plotting framework.
6. Implement an application that stores big data in Hbase / MongoDB using Hadoop / R.
7. Install, deploy and configure Apache Spark cluster. Run an application using Apache Spark.

TOTAL: 60 PERIODS

LAB REQUIREMENTS FOR A BATCH OF 30 STUDENTS

SOFTWARE

Hadoop, R Package, Hbase, MongoDB, Apache Spark

COURSE OUTCOMES:

Upon completion of this course, the students will be able to
CO1: Process big data using Hadoop framework.
CO2: Implement MapReduce framework for processing big data.
CO3: Perform data analysis using classification and clustering techniques.
CO4: Realize storage of big data using MongoDB , Hbase and Apache Spark
CO5: Perform graphical data analysis