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KI-Glossar

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Distributed Computing

Computing paradigm where processing is distributed across multiple interconnected nodes to handle massive volumes of streaming data in parallel.

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Windowing Operations

Temporal or quantity-based grouping technique for stream elements to apply aggregate calculations in distributed learning systems.

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Load Balancing

Dynamic distribution of workload among computing nodes to optimize resource utilization and prevent bottlenecks.

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Message Queuing

Asynchronous communication mechanism enabling ordered message transfer between producers and consumers in distributed streaming architectures.

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Node Synchronization

Temporal and state coordination between computing nodes to maintain consistency in a distributed stream processing environment.

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Throughput Optimization

Maximization of data volume processed per time unit in distributed systems, a critical trade-off with latency in streaming applications.

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Stream Partitioning Strategy

Method for distributing data streams among computing nodes based on keys, time intervals, or hashing algorithms for optimal balancing.

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Consistent Hashing

Distribution algorithm that minimizes data remapping when adding or removing nodes in distributed stream processing systems.

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Scalability Patterns

Architectures and strategies enabling horizontal scaling of streaming processing systems to handle increasing data volumes.

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