Think in Streams #1 – Java Stream API Learned Through Practice
*Think in Streams #1 – Java Stream API Learned Through Practice*
Java Streams didn’t really click for me when I read documentation or watched theory-heavy tutorials.
They started making sense only when I **solved real problems using Streams**.
In this first video of the *Think in Streams* series, I briefly explain what Java Streams are and then jump straight into *8 hands-on problems* using an Employee dataset. The focus is on building Stream pipelines step by step and understanding how intermediate operations work together.
🚀 Topics covered in this session:
`filter()`
`map()` and *filter + map combinations*
`distinct()`
`cnt()`
`sorted()`
`limit()` and `skip()`
`toList()` as a terminal operation
This video is ideal if:
Java Streams feel confusing or abstract
You learn better by *solving problems*
You want practical Stream examples for interviews or real projects
You want to start thinking in a *functional style*
🔗 *GitHub Repository (All Code Used in the Video)*
[https://github.com/tech-recipes/think...](https://github.com/tech-recipes/think...)
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⏱️ *Chapters*
00:00 – Why Streams Didn’t Click Initially
00:42 – What Are Java Streams ? (Quick Overview)
01:48 – Problem Solving with Streams (8 Problems)
04:03 – Problem 1 - filter()
07:35 – Problem 2 - map()
11:19 – Problem 3 - distinct()
13:52 – Problem 4 - sorted() and limit()
18:24 – Problem 5 - limit() and skip()
21:04 – Problem 6 - sorted() and limit()
24:09 – Problem 7 - map() and distict()
26:15 – Problem 8 - filter() and count()
28:04 – Summary & Next Steps
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📘 *What You’ll Learn*
How to approach Stream problems logically
How intermediate operations flow in a pieline
How to translate business requirements into Stream code
How to avoid common beginner mistakes with Streams
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👍 *Support the Series*
If this video helps you, consider liking 👍 and subscribing 🔔.
Comment below if you want the next session on `flatMap`, `reduce`, and matching operations.
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