BCAM062 Stream Processing and Analytics Syllabus
AKTU B.Tech · 3rd Year · Unit-wise syllabus (effective 2024-25)
BCAM062 Stream Processing and Analytics (also written as KCAM062) is a subject in the 3rd year of the AKTU B.Tech programme, prescribed by Dr. A.P.J. Abdul Kalam Technical University. The syllabus is divided into 5 units: Fundamentals of Stream Processing and Stream-Processing Model and Practical Component, Practical Component, Practical Component, Practical Component, Practical Component. The complete unit-wise topic list, course outcomes and reference books are given below, taken from the official AKTU syllabus effective from 2024-25.
BCAM062 Subject Details
| Subject Code | BCAM062 / KCAM062 |
|---|---|
| Subject Name | Stream Processing and Analytics |
| University | Dr. A.P.J. Abdul Kalam Technical University (AKTU) |
| Course | B.Tech (Bachelor of Technology) |
| Year / Semester | 3rd Year |
| Total Units | 5 |
| Scheme Effective From | 2024-25 |
| Last Verified | 2026-08-19 |
BCAM062 Stream Processing and Analytics Unit-Wise Syllabus
Official AKTU syllabus (effective 2024-25) — 5 units.
Unit 1: Fundamentals of Stream Processing · Stream-Processing Model · Practical Component
Fundamentals of Stream Processing: What Is Stream Processing? Examples of Stream Processing- Scaling Up Data Processing- Distributed Stream Processing- Introducing Apache Spark. Stream-Processing Model: Sources and Sinks- Immutable Streams Defined from One Another- Transformations and Aggregations- Window Aggregations – Stateless and Stateful Processing- The Effect of Time. Practical Component: a. Installing and configuring Apache Spark b. Installing and configuring the Scala IDE c. Installing and configuring JDK
Unit 2: Practical Component
Components of a Data Platform- Architectural Models- The Use of a Batch-Processing Component in a Streaming Application- Referential Streaming Architectures- Streaming Versus Batch Algorithms. Apache Spark as a Stream-Processing Engine: Spark’s Memory Usage- Understanding Latency- Throughput- Oriented Processing- Fast Implementation of Data Analysis. Practical Component: a. Write your own Spark Streaming program, to count the number of words in text data received from data server listening on a TCP socket b. Write a simple Spark Streaming program that prints a sample of the tweets it receives from Twitter every second.
Unit 3: Practical Component
Spark’s Distributed Processing Model: Running Apache Spark with a Cluster Manager- Spark’s Own Cluster Manager – Resilience and Fault Tolerance in a Distributed System- Data Delivery Semantics- Microbatching and One-Element-at-a-Time – Bringing Microbatch and One-Record-at a- Time Closer Together- Dynamic Batch Interval- Structured Streaming Processing Model. Spark’s Resilience Model: Resilient Distributed Datasets in Spark – Spark Components – Spark’s Fault- Tolerance Guarantees. Practical Component: a. Create Spark RDD using parallelize with sparkContext.parallelize() method and using Spark shell b. Write a scripts in Spark to Read all text files from a directory into a single RDD c. Write a spark program to load a CSV file into Spark RDD using a Scala d. Write a Spark Streaming program for adding 1 to the stream of integers in a reliable, fault tolerant manner, and then visualize them.
Unit 4: Practical Component
Introducing Structured Streaming- The Structured Streaming Programming Model – Structured Streaming in Action – Structured Streaming Sources – Structured Streaming Sinks – Event Time– Based Stream Processing. Practical Component: a. Develop a streaming application by- Connecting to a Stream, Preparing the Data in the Stream, Performing Operations on Streaming Dataset, creating a Query, Starting the Stream Processing and Exploring the data. b. Create a Structured streaming job by Initializing Spark, acquiring streaming data from sources, declaring the operations we want to apply to the streaming data and outputting the resulting data using Sinks. c. Create a small but complete Internet of Things (IoT)-inspired streaming program. d. Define the schema in Structured Streaming to handle the data at different levels. e. Create custom sinks to write data to systems not supported by the default implementations
Unit 5: Practical Component
Introducing Spark Streaming – The Spark Streaming Programming Model – The Spark Streaming Execution Model – Spark Streaming Sources – Spark Streaming Sinks – Time-Based Stream Processing- Working with Spark SQL – Checkpointing – Monitoring Spark Streaming- Performance Tuning. Practical Component: (i) Develop any Spark Streaming application and do the following : a) Create a Spark Streaming Context, b) Define one or several Dstreams from data sources or other Dstreams c) Define one or more output operations to materialize the results of these
BCAM062 Course Outcomes
- At the end of course, the student will be able to: K1, K2
- CO 1 Explain the need for stream processing K2, K3
- CO 2 Comprehend the architectures of stream processing. K1, K2
- CO 3 Explain and run Distributed Processing and Resilience Model
- CO 4 Design effective streaming solutions using Structured Streaming K5, K6
- CO 5 Design effective streaming solutions using Spark Streaming K5, K6
- 3-0-0
- DETAILED SYLLABUS
BCAM062 Reference Books
- Gerard Maas and Francois Garillot , “Stream Processing with Apache Spark: Mastering Structured
- Henrique C. M. Andrade, Buǧra Gedik and Deepak S. Turaga, “Fundamentals of Stream Processing:
- Bryon Ellis, “Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data”, Wiley, 1st
- Anindita Basak, Krishna Venkataraman, Ryan Murphy, Manpreet Singh, “Stream Analytics with
Frequently Asked Questions about BCAM062
What is the syllabus of BCAM062 Stream Processing and Analytics?
The AKTU BCAM062 Stream Processing and Analytics syllabus is divided into 5 units: Fundamentals of Stream Processing and Stream-Processing Model and Practical Component; Practical Component; Practical Component; Practical Component; Practical Component. The complete topic list for each unit is published on this page, taken from the official Dr. A.P.J. Abdul Kalam Technical University syllabus effective from 2024-25.
How many units are there in BCAM062?
BCAM062 Stream Processing and Analytics has 5 units in the AKTU syllabus.
Is BCAM062 the same subject as KCAM062?
Yes. AKTU renumbered its B.Tech subject codes from the 2022-23 session onwards, so the same subject appears as BCAM062 and KCAM062 depending on the scheme year. The syllabus content is the same.
Where can I download BCAM062 previous year question papers?
AKTU B.Tech previous year question papers for every semester are available to download free on Ryzenstudy, with no login or registration required.
Is this the official AKTU syllabus for BCAM062?
Yes. Every topic on this page is taken from the official Dr. A.P.J. Abdul Kalam Technical University syllabus document (AKTU B.Tech 3rd Year Artificial Intelligence & Data Science Syllabus), effective from 2024-25. A direct link to the original AKTU PDF is provided at the top of this page. Last verified on 2026-08-19.
Related AKTU Syllabus
Source: Dr. A.P.J. Abdul Kalam Technical University official syllabus — AKTU B.Tech 3rd Year Artificial Intelligence & Data Science Syllabus, effective from 2024-25. Ryzenstudy is not affiliated with AKTU. Content last verified on 2026-08-19.