Writing correct and efficient parallel programs is hard. A lack of overview leads to errors in control- and dataflow, e.g., race conditions, which are hard to find due to their nondeterministic nature. In this paper, we present a graphical programming model for parallel stream processing applications, which improves the overview by visualizing high level dataflow together with explicit and concise annotations for concurrency-related dependency information. The key idea of our approach is twofold: First, we present a powerful graphical task editor together with annotations that enable the designer to define stream properties, task dependencies, and routing information. These annotations facilitate fine-granular and correct parallelization. Second, we propose seamless integration with the safe parallel programming language Rust by providing automated code structure generation from the graphical representation, design patterns for common parallel programming constructs like filters, and a scheduling and runtime environment. We demonstrate the applicability of our approach with a network-based processing system as it is typically found in advanced firewalls.