大葉大學圖書館 |

Practical Hive[electronic resource] :a guide to Hadoop's data warehouse system /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	005.745
書名/作者:	Practical Hive : a guide to Hadoop's data warehouse system // by Scott Shaw ... [et al.].
其他作者:	Shaw, Scott.
出版者:	Berkeley, CA : : Apress :, 2016.
面頁冊數:	xxi, 265 p. : : ill. (some col.), digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Data warehousing.
標題:	Computer Science.
標題:	Computer Science, general.
標題:	Data Storage Representation.
標題:	Systems and Data Security.
標題:	Data Structures.
標題:	Database Management.
標題:	Files.
ISBN:	9781484202715
ISBN:	9781484202722
內容註:	Chapter 1: Setting the Stage for Hive: Hadoop -- Chapter 2: Introducing Hive -- Chapter 3: Hive Architecture -- Chapter 4: Hive Tables DDL -- Chapter 5: Data Manipulation Language (DML) -- Chapter 6: Loading Data into Hive -- Chapter 7: Querying Semi-Structured Data -- Chapter 8: Hive Analytics -- Chapter 9: Performance Tuning: Hive -- Chapter 10: Hive Security -- Chapter 11: Future of Hive -- Chapter 12: Appendix A. Building a Big Data Team -- Chapter 13: Appendix B. Hive Functions.
摘要、提要註:	Dive into the world of SQL on Hadoop and get the most out of your Hive data warehouses. This book is your go-to resource for using Hive: authors Scott Shaw, Ankur Gupta, David Kjerrumgaard, and Andreas Francois Vermeulen take you through learning HiveQL, the SQL-like language specific to Hive, to analyze, export, and massage the data stored across your Hadoop environment. From deploying Hive on your hardware or virtual machine and setting up its initial configuration to learning how Hive interacts with Hadoop, MapReduce, Tez and other big data technologies, Practical Hive gives you a detailed treatment of the software. In addition, this book discusses the value of open source software, Hive performance tuning, and how to leverage semi-structured and unstructured data. What You Will Learn Install and configure Hive for new and existing datasets Perform DDL operations Execute efficient DML operations Use tables, partitions, buckets, and user-defined functions Discover performance tuning tips and Hive best practices Who This Book Is For Developers, companies, and professionals who deal with large amounts of data and could use software that can efficiently manage large volumes of input. It is assumed that readers have the ability to work with SQL.
電子資源:	http://dx.doi.org/10.1007/978-1-4842-0271-5

Practical Hive[electronic resource] :a guide to Hadoop's data warehouse system /
Practical Hivea guide to Hadoop's data warehouse system /[electronic resource] :by Scott Shaw ... [et al.]. - Berkeley, CA :Apress :2016. - xxi, 265 p. :ill. (some col.), digital ;24 cm.

Chapter 1: Setting the Stage for Hive: Hadoop -- Chapter 2: Introducing Hive -- Chapter 3: Hive Architecture -- Chapter 4: Hive Tables DDL -- Chapter 5: Data Manipulation Language (DML) -- Chapter 6: Loading Data into Hive -- Chapter 7: Querying Semi-Structured Data -- Chapter 8: Hive Analytics -- Chapter 9: Performance Tuning: Hive -- Chapter 10: Hive Security -- Chapter 11: Future of Hive -- Chapter 12: Appendix A. Building a Big Data Team -- Chapter 13: Appendix B. Hive Functions.

Dive into the world of SQL on Hadoop and get the most out of your Hive data warehouses. This book is your go-to resource for using Hive: authors Scott Shaw, Ankur Gupta, David Kjerrumgaard, and Andreas Francois Vermeulen take you through learning HiveQL, the SQL-like language specific to Hive, to analyze, export, and massage the data stored across your Hadoop environment. From deploying Hive on your hardware or virtual machine and setting up its initial configuration to learning how Hive interacts with Hadoop, MapReduce, Tez and other big data technologies, Practical Hive gives you a detailed treatment of the software. In addition, this book discusses the value of open source software, Hive performance tuning, and how to leverage semi-structured and unstructured data. What You Will Learn Install and configure Hive for new and existing datasets Perform DDL operations Execute efficient DML operations Use tables, partitions, buckets, and user-defined functions Discover performance tuning tips and Hive best practices Who This Book Is For Developers, companies, and professionals who deal with large amounts of data and could use software that can efficiently manage large volumes of input. It is assumed that readers have the ability to work with SQL.

ISBN: 9781484202715

Standard No.: 10.1007/978-1-4842-0271-5doiSubjects--Uniform Titles:

Apache Hadoop.
Subjects--Topical Terms:

184152
Data warehousing.

LC Class. No.: QA76.9.D37

Dewey Class. No.: 005.745

Practical Hive[electronic resource] :a guide to Hadoop's data warehouse system /
LDR:02733nmm a2200313 a 4500 001 465907
003 DE-He213
005 20170209112318.0
006 m d
007 cr nn 008maaau
008 170411s2016 cau s 0 eng d
020 $a 9781484202715 $q (electronic bk.)
020 $a 9781484202722 $q (paper)
024 7 $a 10.1007/978-1-4842-0271-5 $2 doi
035 $a 978-1-4842-0271-5
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D37
072 7 $a UY $2 bicssc
072 7 $a COM014000 $2 bisacsh
082 0 4 $a 005.745 $2 23
090 $a QA76.9.D37 $b P895 2016
245 0 0 $a Practical Hive $h [electronic resource] : $b a guide to Hadoop's data warehouse system / $c by Scott Shaw ... [et al.].
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2016.
300 $a xxi, 265 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a Chapter 1: Setting the Stage for Hive: Hadoop -- Chapter 2: Introducing Hive -- Chapter 3: Hive Architecture -- Chapter 4: Hive Tables DDL -- Chapter 5: Data Manipulation Language (DML) -- Chapter 6: Loading Data into Hive -- Chapter 7: Querying Semi-Structured Data -- Chapter 8: Hive Analytics -- Chapter 9: Performance Tuning: Hive -- Chapter 10: Hive Security -- Chapter 11: Future of Hive -- Chapter 12: Appendix A. Building a Big Data Team -- Chapter 13: Appendix B. Hive Functions.
520 $a Dive into the world of SQL on Hadoop and get the most out of your Hive data warehouses. This book is your go-to resource for using Hive: authors Scott Shaw, Ankur Gupta, David Kjerrumgaard, and Andreas Francois Vermeulen take you through learning HiveQL, the SQL-like language specific to Hive, to analyze, export, and massage the data stored across your Hadoop environment. From deploying Hive on your hardware or virtual machine and setting up its initial configuration to learning how Hive interacts with Hadoop, MapReduce, Tez and other big data technologies, Practical Hive gives you a detailed treatment of the software. In addition, this book discusses the value of open source software, Hive performance tuning, and how to leverage semi-structured and unstructured data. What You Will Learn Install and configure Hive for new and existing datasets Perform DDL operations Execute efficient DML operations Use tables, partitions, buckets, and user-defined functions Discover performance tuning tips and Hive best practices Who This Book Is For Developers, companies, and professionals who deal with large amounts of data and could use software that can efficiently manage large volumes of input. It is assumed that readers have the ability to work with SQL.
630 0 0 $a Apache Hadoop. $3 605813
650 0 $a Data warehousing. $3 184152
650 1 4 $a Computer Science. $3 423143
650 2 4 $a Computer Science, general. $3 463629
650 2 4 $a Data Storage Representation. $3 466922
650 2 4 $a Systems and Data Security. $3 466229
650 2 4 $a Data Structures. $3 467911
650 2 4 $a Database Management. $3 463966
650 2 4 $a Files. $3 511353
700 1 $a Shaw, Scott. $3 590331
710 2 $a SpringerLink (Online service) $3 463450
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-1-4842-0271-5
950 $a Professional and Applied Computing (Springer-12059)

	個人資料
	儲存檢索策略
	薦購
	預約/借閱記錄查詢
	訊息
	評論
	個人書籤

	簡單查詢
	進階查詢

	指定參考書
	新書通報
	新書書單RSS