This document discusses fast data intelligence in the Internet of Things using real-time data analytics with Apache Spark Streaming and MLlib. It describes how the IoT is generating more streaming data from multiple sources, requiring new techniques for fast and scalable processing. Common patterns like the Lambda architecture and reactive principles are outlined. Tools like Apache Kafka, Apache Cassandra, and Apache Spark are presented for building architectures to handle streaming data flows and perform tasks like machine learning. Key takeaways are that reactive and scalable systems are needed to process IoT data streams, and open source tools can help achieve this.