With Apache Spark Streaming, you can have multiple kinds of windows; depending on your use case, you can select either a tumbling window, a sliding window, or a static window to determine how much data you want to process at a single point of time.
Apache Spark Streaming offers near real-time analytics, allowing developers to build APIs for code-streaming pipelines. It is highly stable, open-source, and integrates with Anaconda and Miniconda for machine learning. While supporting multiple window types and enhancing decision-making, it faces challenges like complex setup, resource intensity, and memory management. Recommended for five-second latency use cases, it requires improvements in cost optimization and handling diverse data types like COBOL and JSON.
