Modern Java: Stream Gatherers & Scalable Concurrency

Set up a hands-on Maven project for stream gatherer playground, configure JDK 24, add logback in pom.xml, and run Maven sync to download dependencies while organizing sections, packages, and lectures.

Coordinate the integrator and downstream push booleans to control item flow, where true means more items and false stops. Illustrate short-circuiting and lazy streams.

Implement a custom gatherer to simulate the filter operator in Java streams using a predicate to pass even elements downstream. Explore parallel streams and the gatherer interface concepts.

Explore the greedy integrator in Java streams, where greedy extends the integrator interface and uses short-circuiting to stop or propagate downstream results.

Explore stateful custom operators using an object initializer that provides the initial mutable state for sequential gatherers like limit and distinct. Define a combiner to support parallel execution.

Build a simple stateful limit gatherer for streams using an initializer and integrator, a mutable counter, and early stop logic to emit up to the maximum items.

Explore the combiner for parallel streams, where each thread uses its own state initialized by the supplier, then merges states with a binary operator.

Implement a top n gatherer for parallel streams that tracks the top n integers using a priority queue, with options for size and comparator, and a merge strategy via combine.

Use a parallel stream only for large cpu-heavy data; avoid for small data or io tasks due to a limited fork join pool; prefer a sequential stream.

Explore Java 24 stream gatherers, including window fixed and window sliding, showing fixed batches of three items for bulk inserts and sliding windows for anomaly detection.

Create a gatherer utility to expose custom gatherers, enabling a sequential gatherer with internal multithreading via execute concurrent. Configure a virtual thread per task executor, greedy integrator, and finish step.

demonstrates executing concurrent tasks with a gatherer, running 1–10, 1–50, and 1–100 tasks, using limit to return first three results and cancel the rest.

Learn to delay errors in a stream gatherer implementation by storing failures and emitting successful results first, implementing a delay error gatherer that tracks futures and pushes to downstream.

Emit next completed result to the downstream, using a delay error gatherer, collect failures in the error list, and throw a consolidated runtime exception with suppressed errors.

Learn to handle more subtasks with a generic approach that passes the executor service through the by function. Wrap the executor service to hide it and prevent shutdown.

Implement a gatherers util with a generic aggregate concurrent workflow using a subtask executor and by function inputs to run product and rating concurrently.

Explore implementing a timeout pattern in a stream pipeline and examine why a naive integrator fails. The true timeout remains independent of item arrival, exposing issues with declarative approaches.

Set up the geo crawler service as a spring component, inject the geo data client and CT repository, and run a request that streams regions and subregions to print IDs.

Build a geo crawler service that streams subregions to cities using flatMap and concurrent gatherers, retrieves ten cities, and maps each to a city entity.

lower concurrency from the default 1000 to 100 or 50 to fix connection reset errors, testing stability as the host struggles to set up the connection with the external service.