PySpark Big Data Engineering
Master Apache Spark computing engine using Python. This program covers Resilient Distributed Datasets (RDDs), Spark DataFrames, lazy evaluation patterns, data transformations, windowing functions, Spark SQL optimizations, and streaming data concepts.
Program Highlights
Target Audience
Software Engineers, Database Developers, and Data Analysts moving into Big Data roles.
Prerequisites
Good foundation in Python programming and basic SQL database constructs.
Job Roles & Careers
PySpark Developer, Big Data Engineer, ETL Developer.
Salary Outlook
₹7 LPA - ₹16 LPA
Detailed Course Syllabus
- Big Data challenges & introduction to Distributed Computing
- Apache Spark Architecture: Driver, Executer, SparkContext, SparkSession
- Lazy evaluation, Directed Acyclic Graph (DAG), actions and transformations
- Creating DataFrames from CSV, JSON, Parquet files
- Selecting, filtering, ordering, renaming columns
- Handling Null values, User Defined Functions (UDFs) optimization
- GroupBy, agg, and pivoting functions
- Distributed Joins: Broadcast joins vs Shuffle Hash joins
- Window functions (ranking, lead/lag, rolling averages)
- Managing Partitions (coalesce vs repartition)
- Caching and Persisting data (Memory, Disk storage options)
- Inspecting Spark UI for Bottlenecks, Spills, and Skews
- Registering Temp Views & writing SQL syntax
- Reading/writing from/to PostgreSQL, MySQL, and HDFS
Batches & Timings
Weekday Batch
Monday - Friday (8:00 AM - 10:00 AM)
Weekend Batch
Saturday & Sunday (1:00 PM - 5:00 PM)
Career Benefits & Outcomes
Writing and optimization scripts for gigabyte to terabyte-scale datasets
Techniques to eliminate partition skew and shuffle overheads
Working with Spark SQL and integrating with external databases
Live project reviews by senior Big Data Architects
CV optimization for top tier multinational analytics companies
Quick Summary
- Duration: 2 Months
- Format: Classroom & Online
- Placement Support: 100% Assistance
- Batch: Weekday / Weekend
- Live Projects: Tera-scale Projects
Quick Enquiry
Have questions? Ask our academic counselors.