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Cloudera CCD-333 Exam Syllabus Topics:
| Section | Objectives |
| Hadoop Fundamentals | - MapReduce programming model
- HDFS architecture and data storage concepts
|
| Hadoop Cluster Operations | - Resource management with YARN
- Cluster configuration and management basics
|
| Data Processing with Hadoop Ecosystem | - Pig Latin scripting basics
- Hive query language and data warehousing
|
| Data Analysis and Optimization | - Query optimization in Hive
- Performance tuning in MapReduce jobs
|
| Data Ingestion and Workflow | - Sqoop data import/export
- Flume data ingestion concepts
|
Cloudera Certified Developer for Apache Hadoop Sample Questions:
1. You need to create a GUI application to help your company's sales people add and edit customer information. Would HDFS be appropriate for this customer information file?
A) Yes, because HDFS is optimized for fast retrieval of relatively small amounts of data.
B) No, because HDFS is optimized for write-once, streaming access for relatively large files.
C) No, because HDFS can only be accessed by MapReduce applications.
D) Yes, because HDFS is optimized for random access writes.
2. Your client application submits a MapReduce job to your Hadoop cluster. The Hadoop framework looks for an available slot to schedule the MapReduce operations on which of the following Hadoop computing daemons?
A) JobTracker
B) DataNode
C) TaskTracker
D) Secondary NameNode
E) NameNode
3. How does the NameNode detect that a DataNode has failed?
A) When the NameNode fails to receive periodic heartbeats from the DataNode, it considers the DataNode as failed.
B) The NameNode periodically pings the datanode. If the DataNode does not respond, the NameNode considers the DataNode as failed.
C) The NameNode does not need to know that a DataNode has failed.
D) When HDFS starts up, the NameNode tries to communicate with the DataNode and considers the DataNode as failed if it does not respond.
4. Which of the following describes how a client reads a file from HDFS?
A) The client contacts the NameNode for the block location(s). The NameNode then queries the DataNodes for block locations. The DataNodes respond to the NameNode, and the NameNode redirects the client to the DataNode that holds the requested data block(s). The client then reads the data directly off the DataNode.
B) The client queries all DataNodes in parallel. The DataNode that contains the requested data responds directly to the client. The client reads the data directly off the DataNode.
C) The client contacts the NameNode for the block location(s). The NameNode contacts theDataNode that holds the requested data block. Data is transferred from the DataNode to the NameNode, and then from the NameNode to the client.
D) The client queries the NameNode for the block location(s). The NameNode returns the block location(s) to the client. The client reads the data directly off the DataNode(s).
5. You need a distributed, scalable, data Store that allows you random, realtime read/write access to hundreds of terabytes of data. Which of the following would you use?
A) Pig
B) Sqoop
C) Flume
D) Hive
E) Oozie
F) Hue
G) HBase
Solutions:
Question # 1 Answer: B | Question # 2 Answer: A | Question # 3 Answer: A | Question # 4 Answer: A | Question # 5 Answer: G |