Spark in Action
暫譯: 《Spark 實戰》
Petar Zecevic, Marko Bonaci
- 出版商: Manning
- 出版日期: 2016-11-26
- 定價: $1,650
- 售價: 6.0 折 $990
- 語言: 英文
- 頁數: 472
- 裝訂: Paperback
- ISBN: 1617292605
- ISBN-13: 9781617292606
-
相關分類:
Spark
-
其他版本:
Spark in Action ,2/e (Paperback)
買這商品的人也買了...
-
$620$490 -
$380$342 -
$1,214Learning Scala: Practical Functional Programming for the JVM (Paperback)
-
$1,808The Art of SEO: Mastering Search Engine Optimization, 3/e (Paperback)
-
$305圖解機器學習
-
$1,568Spark: Big Data Cluster Computing in Production (Paperback)
-
$2,470$2,347 -
$580$458 -
$540$427 -
$1,197Fast Data Processing with Spark 2 - Third Edition
-
$2,030$1,929 -
$403機器學習導論 (An Introduction to Machine Learning)
-
$590$502 -
$1,575Expert Hadoop Administration: Managing, Tuning, and Securing Spark, YARN, and HDFS (paperback)
-
$680$578 -
$590$460 -
$580$493 -
$500$395 -
$1,660$1,577 -
$2,800Algorithms for Data Science
-
$2,000$1,900 -
$540$459 -
$798Deep Learning with Hadoop (Paperback)
-
$1,400High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark (Paperback)
-
$2,400$2,280
相關主題
商品描述
Summary
Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. Fully updated for Spark 2.0.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the Technology
Big data systems distribute datasets across clusters of machines, making it a challenge to efficiently query, stream, and interpret them. Spark can help. It is a processing system designed specifically for distributed data. It provides easy-to-use interfaces, along with the performance you need for production-quality analytics and machine learning. Spark 2 also adds improved programming APIs, better performance, and countless other upgrades.
About the Book
Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. You'll get comfortable with the Spark CLI as you work through a few introductory examples. Then, you'll start programming Spark using its core APIs. Along the way, you'll work with structured data using Spark SQL, process near-real-time streaming data, apply machine learning algorithms, and munge graph data using Spark GraphX. For a zero-effort startup, you can download the preconfigured virtual machine ready for you to try the book's code.
What's Inside
- Updated for Spark 2.0
- Real-life case studies
- Spark DevOps with Docker
- Examples in Scala, and online in Java and Python
About the Reader
Written for experienced programmers with some background in big data or machine learning.
About the Authors
Petar Zečević and Marko Bonaći are seasoned developers heavily involved in the Spark community.
Table of Contents
PART 1 - FIRST STEPS
PART 2 - MEET THE SPARK FAMILY
PART 3 - SPARK OPS
PART 4 - BRINGING IT TOGETHER
- Introduction to Apache Spark
- Spark fundamentals
- Writing Spark applications
- The Spark API in depth
- Sparkling queries with Spark SQL
- Ingesting data with Spark Streaming
- Getting smart with MLlib
- ML: classification and clustering
- Connecting the dots with GraphX
- Running Spark
- Running on a Spark standalone cluster
- Running on YARN and Mesos
- Case study: real-time dashboard
- Deep learning on Spark with H2O
商品描述(中文翻譯)
**摘要**
《Spark in Action》教你使用 Spark 有效處理批次和串流數據所需的理論和技能。此書已全面更新至 Spark 2.0。
購買印刷版書籍可免費獲得 Manning Publications 提供的 PDF、Kindle 和 ePub 格式的電子書。
**關於技術**
大數據系統將數據集分佈在多台機器的集群中,這使得高效查詢、串流和解釋數據成為一個挑戰。Spark 可以幫助解決這個問題。它是一個專為分佈式數據設計的處理系統,提供易於使用的介面,以及生產級分析和機器學習所需的性能。Spark 2 還增加了改進的編程 API、更好的性能和無數其他升級。
**關於本書**
《Spark in Action》教你使用 Spark 有效處理批次和串流數據所需的理論和技能。在幾個入門範例中,你將熟悉 Spark CLI。接著,你將開始使用其核心 API 編寫 Spark 程式。在這個過程中,你將使用 Spark SQL 處理結構化數據、處理近實時的串流數據、應用機器學習算法,並使用 Spark GraphX 處理圖形數據。為了簡化啟動過程,你可以下載預配置的虛擬機,隨時嘗試書中的代碼。
**內容概覽**
- 更新至 Spark 2.0
- 實際案例研究
- 使用 Docker 的 Spark DevOps
- Scala 範例,並在線提供 Java 和 Python 範例
**讀者對象**
本書適合具有一定大數據或機器學習背景的經驗豐富的程式設計師。
**作者介紹**
**Petar Zečević** 和 **Marko Bonaći** 是活躍於 Spark 社群的資深開發者。
**目錄**
**第一部分 - 初步步驟**
**第二部分 - 認識 Spark 家族**
**第三部分 - Spark 操作**
**第四部分 - 整合**
1. Apache Spark 介紹
2. Spark 基礎
3. 編寫 Spark 應用程式
4. 深入了解 Spark API
5. 使用 Spark SQL 進行查詢
6. 使用 Spark Streaming 進行數據攝取
7. 使用 MLlib 進行智能分析
8. 機器學習:分類和聚類
9. 使用 GraphX 連接數據點
10. 運行 Spark
11. 在 Spark 獨立集群上運行
12. 在 YARN 和 Mesos 上運行
13. 案例研究:實時儀表板
14. 使用 H2O 在 Spark 上進行深度學習