Learning Apache Drill: Query and Analyze Structured Data

Charles Givre, Paul Rogers

  • 出版商: O'Reilly
  • 出版日期: 2018-12-18
  • 定價: $2,080
  • 售價: 8.0$1,664
  • 語言: 英文
  • 頁數: 332
  • 裝訂: Paperback
  • ISBN: 1492032794
  • ISBN-13: 9781492032793
  • 相關分類: 分散式架構
  • 立即出貨



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


Apache Drill 可以對大規模的數據集進行互動式分析,讓您可以對許多不同的數據源(包括 Hadoop 和 MongoDB 集群、HBase,甚至是本地文件系統)執行 SQL 查詢並快速獲得結果。這本實用指南專為專注於商業或研究應用的分析師和數據科學家提供,他們將學習如何將 Drill 的功能融入到複雜的程序中,包括如何使用 Drill 查詢來替換大規模程序中的某些 MapReduce 操作。

Drill 的貢獻者 Charles Givre 和 Paul Rogers 為 Drill 和其處理包含靈活格式和嵌套數據結構和表格的大文件的能力提供了介紹。您將發現這種能力填補了 Hadoop 生態系統中的一個空白。

- 準備和組織數據以最大化 Drill 的性能
- 對不同數據類型和數量的 Drill 性能設定期望值
- 將 Drill 的無模式架構特性與有模式的 JDBC 和 ODBC 客戶端協調一致