"C藏经阁：结构化流处理的简易、可扩展、容错方案"。

"Cangjingge is an innovative stream processing platform that offers easy, scalable, and fault-tolerant capabilities for handling structured data streams. Developed by the team at Databricks, which initiated the Spark project at UC Berkeley in 2009, Cangjingge is part of their Unified Analytics Platform with the mission of making big data simple. Stream processing poses numerous challenges, including dealing with diverse data formats such as JSON, Avro, and binary, as well as handling data that is dirty, late, or out-of-order. These complexities make building robust stream processing applications a daunting task for many organizations. Enter Cangjingge, a solution presented by Michael Armbrust and Tathagata Das at Spark Summit 2017 in San Francisco. This platform offers easy-to-use tools for processing structured data streams, allowing users to seamlessly scale their applications as needed and maintain fault tolerance throughout the process. With Cangjingge, organizations can overcome the challenges of stream processing and efficiently analyze their data in real-time. By providing a structured streaming interface, this platform simplifies the development and deployment of stream processing applications, making it accessible to a wider range of users. In conclusion, Cangjingge is a game-changing platform that brings ease, scalability, and fault tolerance to stream processing, revolutionizing the way organizations handle their structured data streams. With its innovative approach and powerful capabilities, Cangjingge is set to pave the way for a new era of data analytics and processing."