有没有人spark on yarn 模式，开发spark streaming

汉语言搞大数据 2018-10-25 10:18:22

有人遇到过container be kill 吗？查看内存，显示堆外内存一直在增长。

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汉语言搞大数据 2018-10-25

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网上查的解决方式是，关闭yarn 的虚拟内存检查和物理内存检查。这个的原理是，堆外内存到达最大值会执行gc ，但是为什么会一直增长呢

Title: Hadoop: The Definitive Guide, 4th Edition Author: Tom White Length: 768 pages Edition: 4 Language: English Publisher: O'Reilly Media Publication Date: 2015-04-10 ISBN-10: 1491901632 ISBN-13: 9781491901632 Get ready to unlock the power of your data. With the fourth edition of this comprehensive guide, you’ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. Using Hadoop 2 exclusively, author Tom White presents new chapters on YARN and several Hadoop-related projects such as Parquet, Flume, Crunch, and Spark. You’ll learn about recent changes to Hadoop, and explore new case studies on Hadoop’s role in healthcare systems and genomics data processing. Learn fundamental components such as MapReduce, HDFS, and YARN Explore MapReduce in depth, including steps for developing applications with it Set up and maintain a Hadoop cluster running HDFS and MapReduce on YARN Learn two data formats: Avro for data serialization and Parquet for nested data Use data ingestion tools such as Flume (for streaming data) and Sqoop (for bulk data transfer) Understand how high-level data processing tools like Pig, Hive, Crunch, and Spark work with Hadoop Learn the HBase distributed database and the ZooKeeper distributed configuration service Table of Contents Part I. Hadoop Fundamentals Chapter 1. Meet Hadoop Chapter 2. MapReduce Chapter 3. The Hadoop Distributed Filesystem Chapter 4. YARN Chapter 5. Hadoop I/O Part II. MapReduce Chapter 6. Developing a MapReduce Application Chapter 7. How MapReduce Works Chapter 8. MapReduce Types and Formats Chapter 9. MapReduce Features Part III. Hadoop Operations Chapter 10. Setting Up a Hadoop Cluster Chapter 11. Administering Hadoop Part IV. Related Projects Chapter 12. Avro Chapter 13. Parquet Chapter 14. Flume Chapter 15. Sqoop Chapter 16. Pig Chapter 17. Hi

spark on yarn Spark on yarn：Spark 使用了 yarn 管理器。Spark 运行在 YARN 上时，不需要启动 Spark 集群，只需要启动 YARN 即可，YARN 的 ResourceManager 相当于 Spark Standalone 模式下的 Master。 spark中的两种模式（Cluster和Client） Cluster和Clien...

本部分内容全面涵盖了Spark生态系统的概述及其编程模型，深入内核的研究，Spark on Yarn,Spark RDD、Spark Streaming流式计算原理与实践，Spark SQL,Spark的多语言编程以及SparkR的原理和运行。本套Spark教程不仅...

1 启动方式执行命令./spark-shell --master yarn默认运行的是client模式。执行./spark-shell --master yarn-client或者./spark-shell --master yarn --deploy-mode client运行的也是client。执行./spark-shell --master yarn-cluster或者./spar...

Client模式和Cluster模式最最本质的区别是： Driver程序运行在哪里。Client模式：学习测试时使用，生产不推荐(要用也可以,性能略低,稳定性略低)1.Driver运行在Client上,和集群的通信成本高2.Driver输出结果会在客户端显示Cluster模式：生产环境中使用该模式1.Driver程序在YARN集群中，和集群的通信成本低2.Driver输出结果不能在客户端显示。

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