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相關主題
商品描述
Apache Drill enables interactive analysis of massively large datasets, allowing you to execute SQL queries against data in many different data sources—including Hadoop and MongoDB clusters, HBase, or even your local file system—and get results quickly. With this practical guide, analysts and data scientists focused on business or research applications will learn how to incorporate Drill capabilities into complex programs, including how to use Drill queries to replace some MapReduce operations in a large-scale program.
Drill committers Charles Givre and Paul Rogers provide an introduction to Drill and its ability to handle large files containing data in flexible formats with nested data structures and tables. You’ll discover how this capability fills a gap in the Hadoop ecosystem.
Additional topics show you how to:
- Prepare and organize data to maximize Drill performance
- Set expectations for Drill performance on different data types and volumes
- Reconcile Drill’s schema-free features with schema-full JDBC and ODBC clients
商品描述(中文翻譯)
Apache Drill 使得對於大規模數據集的互動分析成為可能，允許您對來自多種數據來源的數據執行 SQL 查詢——包括 Hadoop 和 MongoDB 集群、HBase，甚至是您的本地檔案系統——並快速獲得結果。這本實用指南將幫助專注於商業或研究應用的分析師和數據科學家學習如何將 Drill 的功能整合到複雜的程式中，包括如何使用 Drill 查詢來替代大型程式中的某些 MapReduce 操作。
Drill 的提交者 Charles Givre 和 Paul Rogers 將介紹 Drill 及其處理包含靈活格式的數據的大文件的能力，這些數據具有嵌套數據結構和表格。您將發現這一能力如何填補 Hadoop 生態系統中的一個空白。
其他主題將向您展示如何：
- 準備和組織數據以最大化 Drill 的性能
- 設定對不同數據類型和數量的 Drill 性能預期
- 將 Drill 的無模式特性與有模式的 JDBC 和 ODBC 客戶端進行調和
