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Cloudera CCD-333 Exam Syllabus Topics:

Section	Objectives
Topic 1: Data Processing Tools	- Hive 1. SQL-like querying on Hadoop - Pig 1. Pig Latin scripting
Topic 2: Workflow and Scheduling	- Oozie 1. Workflow coordination and job scheduling
Topic 3: Data Processing with MapReduce	- Optimization and debugging 1. Performance tuning basics 2. Job troubleshooting techniques - MapReduce programming model 1. Shuffle and sort phase 2. Mapper and Reducer logic
Topic 4: Hadoop Ecosystem and Architecture	- YARN Resource Management 1. Resource allocation and scheduling 2. Cluster resource management concepts - Hadoop Distributed File System (HDFS) 1. HDFS architecture and components 2. Data replication and fault tolerance
Topic 5: Data Formats and Storage	- Serialization formats 1. Avro, Parquet, and SequenceFile concepts
Topic 6: Data Ingestion and Integration	- Flume 1. Log collection and streaming ingestion - Sqoop 1. Import/export between RDBMS and Hadoop

Cloudera Certified Developer for Apache Hadoop Sample Questions:

Question #1

Combiners Increase the efficiency of a MapReduce program because:

A. They provide a mechanism for different mappers to communicate with each Other, thereby reducing synchronization overhead.
B. They provide an optimization and reduce the total number of computations that are needed to execute an algorithm by a factor of n, where is the number of reducer.
C. They aggregate intermediate map output horn a small number of nearby (i.e., rack-local) machines and therefore reduce the amount of data that needs to be shuffled across the network to the reducers.
D. They aggregate intermediate map output locally on each individual machine and therefore reduce the amount of data that needs to be shuffled across the network to the reducers.

Reveal Solution Discussion 0

Correct Answer: D 🗳️