CCA175 Exam Information and Guideline
CCA Spark and Hadoop Developer
Below are complete topics detail with latest syllabus and course outline, that will help you good knowledge about exam objectives and topics that you have to prepare. These contents are covered in questions and answers pool of exam.
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.