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Cloudera Certified Administrator for Apache Hadoop(CCAH认证)

Exam Sections and Blueprint 1. HDFS (17%) Describe the function of HDFS daemons Describe the normal operation of an Apache Hadoop cluster, both in data storage and in data processing Identify current features of computing systems that motivate a system like Apache Hadoop Classify major goals of HDFS Design Given a scenario, identify appropriate use case for HDFS Federation Identify components and daemon of an HDFS HA-Quorum cluster Analyze the role of HDFS security (Kerberos) Determine the best data serialization choice for a given scenario Describe file read and write paths Identify the commands to manipulate files in the Hadoop File System Shell 2. YARN and MapReduce version 2 (MRv2) (17%) Understand how upgrading a cluster from Hadoop 1 to Hadoop 2 affects cluster settings Understand how to deploy MapReduce v2 (MRv2 / YARN), including all YARN daemons Understand basic design strategy for MapReduce v2 (MRv2) Determine how YARN handles resource allocations Identify the workflow of MapReduce job running on YARN Determine which files you must change and how in order to migrate a cluster from MapReduce version 1 (MRv1) to MapReduce version 2 (MRv2) running on YARN 3. Hadoop Cluster Planning (16%) Principal points to consider in choosing the hardware and operating systems to host an Apache Hadoop cluster Analyze the choices in selecting an OS Understand kernel tuning and disk swapping Given a scenario and workload pattern, identify a hardware configuration appropriate to the scenario Given a scenario, determine the ecosystem components your cluster needs to run in order to fulfill the SLA Cluster sizing: given a scenario and frequency of execution, identify the specifics for the workload, including CPU, memory, storage, disk I/O Disk Sizing and Configuration, including JBOD versus RAID, SANs, virtualization, and disk sizing requirements in a cluster Network Topologies: understand network usage in Hadoop (for both HDFS and MapReduce) and propose or identify key network design components for a given scenario 4. Hadoop Cluster Installation and Administration (25%) Given a scenario, identify how the cluster will handle disk and machine failures Analyze a logging configuration and logging configuration file format Understand the basics of Hadoop metrics and cluster health monitoring Identify the function and purpose of available tools for cluster monitoring Be able to install all the ecoystme components in CDH 5, including (but not limited to): Impala, Flume, Oozie, Hue, Cloudera Manager, Sqoop, Hive, and Pig Identify the function and purpose of available tools for managing the Apache Hadoop file system 5. Resource Management (10%) Understand the overall design goals of each of Hadoop schedulers Given a scenario, determine how the FIFO Scheduler allocates cluster resources Given a scenario, determine how the Fair Scheduler allocates cluster resources under YARN Given a scenario, determine how the Capacity Scheduler allocates cluster resources 6. Monitoring and Logging (15%) Understand the functions and features of Hadoop’s metric collection abilities Analyze the NameNode and JobTracker Web UIs Understand how to monitor cluster daemons Identify and monitor CPU usage on master nodes Describe how to monitor swap and memory allocation on all nodes Identify how to view and manage Hadoop’s log files Interpret a log file http://www.cloudera.com/training/certification/ccah.html

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混合云存储跨云灾备方案之跨云备份

公有云市场现状,问题及趋势 从全球公有云市场来看,亚马逊AWS一枝独秀,占据了接近40%的市场份额。2017年全年,AWS营收为43.3亿美元,销售额为174.6亿美元。而在中国公有云市场,阿里云的市场份额达到了47.6%。在连续11个季度三位数增长之后,领先优势继续扩大:同期,国内第2至5位云服务商市场份额分别为9.6%、6.5%、6%和5.5%。 然而,近期公有云厂商出现了不少次故障和宕机事故: 2017年2月,一位AWS工程师试图对位于弗吉尼亚州数据中心内的一个S3存储系统进行调试的时候,意外地输入了一个错误命令行,随后大部分互联网,包括Slack、Quora和Trello在内的很多企业平台停机了4个小时。9月份,该区域(美东)又发生了一起存储事故。 2017年3月,微软Azure公有云存储可用性问题超过8个小时,主要影响到美国东部

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