16 posts · page 1 of 1
Learn Kafka Streams for real-time data processing including KStream, KTable, windowed aggregations, joins, exactly-once semantics, and state stores with Java examples.
Master the JavaScript Streams API to process large files, network responses, and data pipelines incrementally without loading everything into memory.
Go beyond basic filtering and mapping with advanced Stream API patterns including custom collectors, parallel streams, and stateful operations.
Go beyond basic Java Stream collectors. Learn groupingBy compositions, teeing, custom Collector implementations, and performance considerations.
Process data incrementally with the JavaScript Streams API -- ReadableStream, WritableStream, TransformStream, and practical patterns for large data handling.
Understand how Node.js streams work and how to handle backpressure correctly to avoid memory leaks and data loss.
Master Java Streams for functional-style data processing. Covers stream creation, map, filter, reduce, collectors, parallel streams, and performance considerations.
Master Node.js streams for efficient data processing. Covers readable, writable, transform, and duplex streams with real-world examples.
Learn how Java lambda expressions work, when to use them, and how they interact with functional interfaces and the Streams API.
Master java.util.stream.Collectors with practical examples covering grouping, partitioning, downstream collectors, and building your own custom collector.
A practical tour of the Java Streams API: how it works, when to use it, lazy evaluation, collectors, parallel streams, and the pitfalls that trip up newcomers.
Master async iterators in Node.js for streaming files, paginated APIs, and backpressure-aware data processing.
Read and write files in modern Node using fs/promises, and learn when to switch to streams for memory-friendly processing of large data.
How Node.js streams really work, why backpressure matters, and how to compose readable, writable, and transform streams without blowing up memory.
Solve Find Median from Data Stream with two heaps. Learn the balance invariant, why it gives O(log n) inserts and O(1) median, and the common pitfalls.
Transform collections with lambdas and the Stream API. Map, filter, reduce, collectors, parallel streams, and the pitfalls of lazy pipelines.