Cargando…
YARN essentials : a comprehensive, hands-on guide to install, administer, and configure settings in YARN /
If you have a working knowledge of Hadoop 1.x but want to start afresh with YARN, this book is ideal for you. You will be able to install and administer a YARN cluster and also discover the configuration settings to fine-tune your cluster both in terms of performance and scalability. This book will...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham, UK :
Packt Publishing,
2015.
|
| Colección: | Community experience distilled.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Need for YARN; The redesign idea; Limitations of the classical MapReduce or Hadoop 1.x; YARN as the modern operating system of Hadoop; What are the design goals for YARN; Summary; Chapter 2: YARN Architecture; Core components of YARN architecture; ResourceManager; ApplicationMaster (AM); NodeManager (NM); YARN scheduler policies; The FIFO (First In First Out) scheduler; The fair scheduler; The capacity scheduler; Recent developments in YARN architecture; Summary
- Chapter 3: YARN InstallationSingle-node installation; Prerequisites; Platform; Software; Starting with the installation; The standalone mode (local mode); The pseudo-distributed mode; The fully-distributed mode; HistoryServer; Slave files; Operating Hadoop and YARN clusters; Starting Hadoop and YARN clusters; Stopping Hadoop and YARN clusters; Web interfaces of the Ecosystem; Summary; Chapter 4: YARN and Hadoop Ecosystems; The Hadoop 2 release; A short introduction to Hadoop 1.x and MRv1; MRv1 versus MRv2; Understanding where YARN fits into Hadoop; Old and new MapReduce APIs
- Backward compatibility of MRv2 APIsBinary compatibility of org.apache.hadoop.mapred APIs; Source compatibility of org.apache.hadoop.mapred APIs; Practical examples of MRv1 and MRv2; Preparing the input file(s); Running the job; Result; Summary; Chapter 5: YARN Administration; Container allocation; Container allocation to the application; Container configurations; YARN scheduling policies; The FIFO (First In First Out) scheduler; The FIFO (First In First Out) scheduler; The capacity scheduler; Capacity scheduler configurations; The fair scheduler; Fair scheduler configurations
- YARN multitenancy application supportYARN administration; Administrative tools; Adding and removing nodes from a YARN cluster; Administrating YARN jobs; MapReduce job configurations; YARN log management; YARN web user interface; Summary; Chapter 6: Developing and Running a Simple YARN Application; Running sample examples on YARN; Running a sample Pi example; Monitoring YARN applications with web GUI; YARN's MapReduce support; The MapReduce ApplicationMaster; Example YARN MapReduce settings; YARN's compatibility with MapReduce applications; Developing YARN applications
- The YARN application workflowWriting the YARN client; Writing the YARN ApplicationMaster; Responsibilities of the ApplicationMaster; Summary; Chapter 7: YARN Frameworks; Apache Samza; Writing a Kafka producer; Writing the hello-samza project; Starting a grid; Storm-YARN; Prerequisites; Hadoop YARN should be installed; Apache ZooKeeper should be installed; Setting up Storm-YARN; Getting the storm.yaml configuration of the launched Storm cluster; Building and running Storm-Starter examples; Apache Spark; Why run on YARN?; Apache Tez; Apache Giraph; HOYA (HBase on YARN); KOYA (Kafka on YARN)