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CCA175 Exam Format | CCA175 Course Contents | CCA175 Course Outline | CCA175 Exam Syllabus | CCA175 Exam Objectives

Exam Detail:

The CCA175 (CCA Spark and Hadoop Developer) is a certification exam that validates the skills and knowledge of individuals in developing and deploying Spark and Hadoop applications. Here are the exam details for CCA175:



- Number of Questions: The exam typically consists of multiple-choice and hands-on coding questions. The exact number of questions may vary, but typically, the exam includes around 8 to 12 tasks that require coding and data manipulation.



- Time Limit: The time allocated to complete the exam is 120 minutes (2 hours).



Course Outline:

The CCA175 course covers various topics related to Apache Spark, Hadoop, and data processing. The course outline typically includes the following topics:



1. Introduction to Big Data and Hadoop:

- Overview of Big Data concepts and challenges.

- Introduction to Hadoop and its ecosystem components.



2. Hadoop File System (HDFS):

- Understanding Hadoop Distributed File System (HDFS).

- Managing and manipulating data in HDFS.

- Performing file system operations using Hadoop commands.



3. Apache Spark Fundamentals:

- Introduction to Apache Spark and its features.

- Understanding Spark architecture and execution model.

- Writing and running Spark applications using Spark Shell.



4. Spark Data Processing:

- Transforming and manipulating data using Spark RDDs (Resilient Distributed Datasets).

- Applying transformations and actions to RDDs.

- Working with Spark DataFrames and Datasets.



5. Spark SQL and Data Analysis:

- Querying and analyzing data using Spark SQL.

- Performing data aggregation, filtering, and sorting operations.

- Working with structured and semi-structured data.



6. Spark Streaming and Data Integration:

- Processing real-time data using Spark Streaming.

- Integrating Spark with external data sources and systems.

- Handling data ingestion and data integration challenges.



Exam Objectives:

The objectives of the CCA175 exam are as follows:



- Evaluating candidates' knowledge of Hadoop ecosystem components and their usage.

- Assessing candidates' proficiency in coding Spark applications using Scala or Python.

- Testing candidates' ability to manipulate and process data using Spark RDDs, DataFrames, and Spark SQL.

- Assessing candidates' understanding of data integration and streaming concepts in Spark.



Exam Syllabus:

The specific exam syllabus for the CCA175 exam covers the following areas:



1. Data Ingestion: Ingesting data into Hadoop using various techniques (e.g., Sqoop, Flume).



2. Transforming Data with Apache Spark: Transforming and manipulating data using Spark RDDs, DataFrames, and Spark SQL.



3. Loading Data into Hadoop: Loading data into Hadoop using various techniques (e.g., Sqoop, Flume).



4. Querying Data with Apache Hive: Querying data stored in Hadoop using Apache Hive.



5. Data Analysis with Apache Spark: Analyzing and processing data using Spark RDDs, DataFrames, and Spark SQL.



6. Writing Spark Applications: Writing and executing Spark applications using Scala or Python.

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