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Cloudera CCA-410 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Troubleshooting & Optimization | 10% | - Performance tuning - Common error diagnosis - Job failure resolution |
| Topic 2: Cluster Management & Monitoring | 25% | - Managing nodes and daemons - Capacity and performance planning - Starting/stopping services - Monitoring health and logs |
| Topic 3: HDFS Operations & High Availability | 20% | - File system maintenance - HDFS High Availability (HA) - Replication and block management - NameNode and DataNode management |
| Topic 4: Security & Data Governance | 15% | - Kerberos authentication - Data protection and backup - Authorization and permissions |
| Topic 5: Hadoop Cluster Installation & Configuration | 30% | - MapReduce v1 configuration - CDH4 deployment - HDFS architecture and configuration - Network and OS tuning |
Cloudera Certified Administrator for Apache Hadoop CDH4 Sample Questions:
Where does a MapReduce job store the intermediate data output from Mappers?
- A. In HDFS, in the job's output directory.
- B. On the underlying filesystem of the local disk machine on which the JobTracker ran.
- C. Stores on the underlying filesystem of the local disk of the machine on which the Reducer.
- D. In HDFS, in temporary directory defined mapred.tmp.dir.
- E. On the underlying filesystem of the local disk of the machine on which the Mapper ran.
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A client application opens a file write stream on your cluster. Which two metadata changes occur during a file write?
- A. the change is written to the secondary namenode
- B. the change is written to the fsimage file
- C. The change is written to the edits file
- D. the metadata in Ram on the namenode is flushed to disk
- E. The metadata in a Ram on the name node is updated
- F. the namenode triggers a block report to update block locations in the edits file
- G. The change is written to the namenode disk
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MapReduce V2 (MRv2/YARN) splits which two major functions of the jobtracker into separate daemons?
- A. Managing tasks
- B. Job scheduling/monitoring
- C. Health status check (heartbeats)
- D. Launching tasks
- E. Job coordination between the resource manager and the node manager
- F. MapReduce metric reporting
- G. Managing file system metadata
- H. Resource management
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Which three processes does HDFS High Availability (HA) enable on your cluster?
- A. Write data to two clusters simultaneously
- B. Configure unlimited hot standby NameNode.
- C. Manually 'fail over' between NameNodes
- D. Automatically 'fail over' between NameNodes if one goes down
- E. Shut one NameNode down for maintenance without halting the cluster
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Your developers request that you enable them to use pig on your hadoop cluster. What do you need to configure and / or install?
- A. Install the pig interpreter on all nodes in the cluster, and the client machines
- B. Install the pig interpreter on the master node which is running the jobtracker
- C. Install the pig interpreter on the client machines only.
- D. Install the pig jar's on the all slave nodes in the cluster the pig interpreter on the client machines
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