Explain the process of designing a distributed system for real-time data processing.
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real-time processing, scalability, fault tolerance, and efficiency. Discuss using a message queue (like Kafka or RabbitMQ) for handling real-time data ingestion, and tools like Apache Flink or Spark Streaming for processing. Emphasize how you would ensure scalability (e.g., autoscaling) and fault tolerance (e.g., data replication and retries).
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