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商品描述
How can you get your data from frontend servers to Hadoop in near real time? With this complete reference guide, you’ll learn Flume’s rich set of features for collecting, aggregating, and writing large amounts of streaming data to the Hadoop Distributed File System (HDFS), Apache HBase, SolrCloud, Elastic Search, and other systems.
Using Flume shows operations engineers how to configure, deploy, and monitor a Flume cluster, and teaches developers how to write Flume plugins and custom components for their specific use-cases. You’ll learn about Flume’s design and implementation, as well as various features that make it highly scalable, flexible, and reliable. Code examples and exercises are available on GitHub.
- Learn how Flume provides a steady rate of flow by acting as a buffer between data producers and consumers
- Dive into key Flume components, including sources that accept data and sinks that write and deliver it
- Write custom plugins to customize the way Flume receives, modifies, formats, and writes data
- Explore APIs for sending data to Flume agents from your own applications
- Plan and deploy Flume in a scalable and flexible way—and monitor your cluster once it’s running
商品描述(中文翻譯)
如何將數據從前端伺服器以近乎即時的方式傳送到 Hadoop?透過這本完整的參考指南,您將學習 Flume 的豐富功能,這些功能用於收集、聚合和寫入大量串流數據到 Hadoop 分散式檔案系統 (HDFS)、Apache HBase、SolrCloud、Elastic Search 及其他系統。
《使用 Flume》向操作工程師展示如何配置、部署和監控 Flume 集群,並教導開發人員如何為其特定用例編寫 Flume 插件和自定義組件。您將了解 Flume 的設計和實現,以及使其高度可擴展、靈活和可靠的各種特性。代碼範例和練習可在 GitHub 上獲得。
- 學習 Flume 如何通過作為數據生產者和消費者之間的緩衝區來提供穩定的流量速率
- 深入了解 Flume 的關鍵組件,包括接受數據的來源和寫入及傳遞數據的匯
- 編寫自定義插件以自定義 Flume 接收、修改、格式化和寫入數據的方式
- 探索從您自己的應用程序向 Flume 代理發送數據的 API
- 計劃和以可擴展且靈活的方式部署 Flume,並在其運行後監控您的集群
