國立虎尾科技大學 |

Practical Hadoop Ecosystem = A Definitive Guide to Hadoop-Related Frameworks and Tools /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Practical Hadoop Ecosystem/ by Deepak Vohra.
Reminder of title:	A Definitive Guide to Hadoop-Related Frameworks and Tools /
Author:	Vohra, Deepak.
Description:	XX, 421 p. 311 illus., 293 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Big data. -
Online resource:	https://doi.org/10.1007/978-1-4842-2199-0
ISBN:	9781484221990

Practical Hadoop Ecosystem = A Definitive Guide to Hadoop-Related Frameworks and Tools /
Vohra, Deepak.

Practical Hadoop EcosystemA Definitive Guide to Hadoop-Related Frameworks and Tools /[electronic resource] :by Deepak Vohra. - 1st ed. 2016. - XX, 421 p. 311 illus., 293 illus. in color.online resource.

Part I. Fundamentals -- Introduction -- 1. HDFS and MapReduce -- Part II Storing & Querying -- 2. Apache Hive -- 3. Apache HBase -- Part III Bulk Transferring & Streaming -- 4. Apache Sqoop -- 5. Apache Flume -- Part IV Serializing -- 6. Apache Avro -- 7. Apache Parquet -- Part V Messaging & Indexing -- 8. Apache Kafka -- 9. Apache Solr -- 10.Apache Mahout.

This book is a practical guide on using the Apache Hadoop projects including MapReduce, HDFS, Apache Hive, Apache HBase, Apache Kafka, Apache Mahout and Apache Solr. From setting up the environment to running sample applications each chapter is a practical tutorial on using a Apache Hadoop ecosystem project. While several books on Apache Hadoop are available, most are based on the main projects MapReduce and HDFS and none discusses the other Apache Hadoop ecosystem projects and how these all work together as a cohesive big data development platform. What you'll learn How to set up environment in Linux for Hadoop projects using Cloudera Hadoop Distribution CDH 5. How to run a MapReduce job How to store data with Apache Hive, Apache HBase How to index data in HDFS with Apache Solr How to develop a Kafka messaging system How to develop a Mahout User Recommender System How to stream Logs to HDFS with Apache Flume How to transfer data from MySQL database to Hive, HDFS and HBase with Sqoop How create a Hive table over Apache Solr.

ISBN: 9781484221990

Standard No.: 10.1007/978-1-4842-2199-0doiSubjects--Topical Terms:

981821
Big data.

LC Class. No.: QA76.9.B45

Dewey Class. No.: 005.7

Practical Hadoop Ecosystem = A Definitive Guide to Hadoop-Related Frameworks and Tools /
LDR:02739nam a22003855i 4500 001 978666
003 DE-He213
005 20200705090706.0
007 cr nn 008mamaa
008 201211s2016 xxu| s |||| 0|eng d
020 $a 9781484221990 $9 978-1-4842-2199-0
024 7 $a 10.1007/978-1-4842-2199-0 $2 doi
035 $a 978-1-4842-2199-0
050 4 $a QA76.9.B45
072 7 $a UN $2 bicssc
072 7 $a COM021000 $2 bisacsh
072 7 $a UN $2 thema
082 0 4 $a 005.7 $2 23
100 1 $a Vohra, Deepak. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 679434
245 1 0 $a Practical Hadoop Ecosystem $h [electronic resource] : $b A Definitive Guide to Hadoop-Related Frameworks and Tools / $c by Deepak Vohra.
250 $a 1st ed. 2016.
264 1 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2016.
300 $a XX, 421 p. 311 illus., 293 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a Part I. Fundamentals -- Introduction -- 1. HDFS and MapReduce -- Part II Storing & Querying -- 2. Apache Hive -- 3. Apache HBase -- Part III Bulk Transferring & Streaming -- 4. Apache Sqoop -- 5. Apache Flume -- Part IV Serializing -- 6. Apache Avro -- 7. Apache Parquet -- Part V Messaging & Indexing -- 8. Apache Kafka -- 9. Apache Solr -- 10.Apache Mahout.
520 $a This book is a practical guide on using the Apache Hadoop projects including MapReduce, HDFS, Apache Hive, Apache HBase, Apache Kafka, Apache Mahout and Apache Solr. From setting up the environment to running sample applications each chapter is a practical tutorial on using a Apache Hadoop ecosystem project. While several books on Apache Hadoop are available, most are based on the main projects MapReduce and HDFS and none discusses the other Apache Hadoop ecosystem projects and how these all work together as a cohesive big data development platform. What you'll learn How to set up environment in Linux for Hadoop projects using Cloudera Hadoop Distribution CDH 5. How to run a MapReduce job How to store data with Apache Hive, Apache HBase How to index data in HDFS with Apache Solr How to develop a Kafka messaging system How to develop a Mahout User Recommender System How to stream Logs to HDFS with Apache Flume How to transfer data from MySQL database to Hive, HDFS and HBase with Sqoop How create a Hive table over Apache Solr.
650 0 $a Big data. $3 981821
650 0 $a Database management. $3 557799
650 1 4 $a Big Data. $3 1017136
650 2 4 $a Database Management. $3 669820
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9781484221983
776 0 8 $i Printed edition: $z 9781484222003
856 4 0 $u https://doi.org/10.1007/978-1-4842-2199-0
912 $a ZDB-2-CWD
912 $a ZDB-2-SXPC
950 $a Professional and Applied Computing (SpringerNature-12059)
950 $a Professional and Applied Computing (R0) (SpringerNature-43716)