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Cloudera - CCA Spark and Hadoop Developer Certification
Overview
Learn how to import data into an Apache Hadoop cluster and process it using modern data analysis tools like Spark, Flume, Hive, Impala, Sqoop and more – in just 3 days.
On this accelerated CCA Spark and Hadoop Developer course, you’ll identify which data analysis tools to use in a given situation and gain hands-on development experience using those tools.
Experience Firebrand’s Lecture | Lab | Review methodology as you prepare for the real world challenges faced by Hadoop developers. You’ll learn:
- How data is distributed, stored, and processed in a Hadoop cluster
- Data distribution in Apache Spark
- How to use Sqoop and Flume to ingest and model data as tables
You’ll also learn how to choose the best data storage format and study best practices for data storage.
Plus, you’ll sit the CCA Spark and Hadoop Developer exam (CCA175) during your accelerated course. This exam is covered by your Certification Guarantee.
Benefits
Other accelerated training providers rely heavily on lecture and independent self-testing and study.
Effective technical instruction must be highly varied and interactive to keep attention levels high, promote camaraderie and teamwork between the students and instructor, and solidify knowledge through hands-on learning.
Firebrand Training provides instruction to meet every learning need:
- Intensive group instruction
- One-on-one instruction attention
- Hands-on labs
- Lab partner and group exercises
- Question and answer drills
- Independent study
Curriculum
Introduction
- Introduction to Hadoop and the Hadoop Ecosystem
- Problems with traditional large scale systems
- Hadoop!
- Data storage and ingest
- Data processing
- Data analysis and exploration
- Other ecosystem tools
- Introduction to the hands-on exercises
Hadoop architecture and HDFS
- Distributed processing on a cluster
- Storage:
- HDFS architecture
- Using HDFS
- Resource management:
- YARN architecture
- Working with YARN
Importing relational data with Apache Sqoop
- Sqoop overview
- Basic imports and exports
- Limiting results
- Improving Sqoop’s performance
- Sqoop 2
Introduction to Impala and Hive
- Introduction to Impala and Hive
- Why use Impala and Hive?
- Querying data With Impala and Hive
- Comparing Hive and Impala to traditional databases
Modelling and managing data with Impala and Hive
- Data storage overview
- Creating databases and tables
- Loading data into tables
- HCatalog
- Impala metadata caching
Data formats
- Selecting a file format
- Hadoop tool support for file formats
- Avro schemas
- Using Avro with Impala, Hive and Sqoop
- Avro schema evolution
- Compression
Data file partitioning
- Partitioning overview
- Partitioning in Impala and Hive
- Capturing data with Apache Flume
- What is Apache Flume?
- Basic Flume architecture:
- Flume sources
- Flume sinks
- Flume channels
- Flume configuration
Spark basics
- What is Apache Spark?
- Using the Spark Shell
- RDDs (Resilient Distributed Datasets)
- Functional programming in Spark
Working with RDDs in Spark
- Creating RDDs
- Other general RDD operations
Writing and deploying Spark applications
- Spark applications vs Spark Shell
- Creating the SparkContext
- Building a Spark application (Scala and Java)
- Running a Spark application
- The Spark application web UI
- Configuring Spark properties
- Logging
Parallel processing in Spark
- Review: Spark on a Cluster
- RDD partitions
- Partitioning of File-based RDDs
- HDFS and data locality
- Executing parallel operations
- Stages and tasks
Spark RDD persistence
- RDD Lineage
- RDD persistence overview
- Distributed persistence
- Common patterns in spark data processing
- Common Spark use cases
- Iterative algorithms in Spark
- Graph processing and analysis
- Machine learning
- Example: k-means
DataFrames and Spark SQL
- Spark SQL and the SQL context
- Creating DataFrames
- Transforming and querying DataFrames
- Saving DataFrames
- DataFrames and RDDs
- Comparing Spark SQL, Impala, and Hive-on-Spark
Exam Track
You'll sit the following exam at the Firebrand Training Centre, covered by your Certification Guarantee:
- CCA175 - CCA Spark and Hadoop Developer Exam
Additional details:
- Number of questions: 10-12 performance-based (hands-on) tasks on a CDH5 cluster
- Time limit: 120 minutes
- Passing score: 70%
For each CCA question you must solve a particular scenario. You will be required to use tools like Hive and Impala, as well as coding in Scala or Python.
What's Included
Your accelerated course includes:
- Accommodation *
- Meals, unlimited snacks, beverages, tea and coffee *
- On-site exams **
- Exam vouchers **
- Practice tests **
- Certification Guarantee ***
- Courseware
- Up-to 12 hours of instructor-led training each day
- 24-hour lab access
- Digital courseware **
- * For residential training only. Accommodation is included from the night before the course starts. This doesn't apply for online courses.
- ** Some exceptions apply. Please refer to the Exam Track or speak with our experts
- *** Pass first time or train again free as many times as it takes, unlimited for 1 year. Just pay for accommodation, exams, and incidental costs.
Prerequisites
You should be a developer/engineer with programming experience in Scala or Python. Basic knowledge of Linux command line and SQL is also recommended.
Prior experience with Hadoop is not required for this accelerated course.
Unsure whether you meet the prerequisites? Don’t worry. Your training consultant will discuss your background with you to understand if this course is right for you.
Reviews
Here's the Firebrand Training review section. Since 2001 we've trained exactly 134561 students and asked them all to review our Accelerated Learning. Currently, 96.41% have said Firebrand exceeded their expectations.
Read reviews from recent accelerated courses below or visit Firebrand Stories for written and video interviews from our alumni.
"Training was very good, explanation was very clear and teacher detailed a lot, so for a 3 day course and to have a first understanding of POWER BI is good."
Rosanna Seerattan Cruz, JTI. (19/3/2024 (Tuesday) to 21/3/2024 (Thursday))
"The instructor and the structure of the course were very clear."
EK, JTI. (19/3/2024 (Tuesday) to 21/3/2024 (Thursday))
"CEH is a very hard training, but it's doable thanks to the friendly employees at Firebrand and the accommodations."
Kas Ramjiawan, ITQM. (4/3/2024 (Monday) to 8/3/2024 (Friday))
"Heavy stuff! Long days and almost no time for some leisure or preparing for exam... I thought there was more hands-on training involved."
MR. (4/3/2024 (Monday) to 8/3/2024 (Friday))
"The course was well structured and concise with a knowledgeable and personable instructor. I will recommend Firebrand courses to all colleagues"
LT. (6/3/2024 (Wednesday) to 8/3/2024 (Friday))
Course Dates
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19/2/2024 (Monday) |
21/2/2024 (Wednesday) |
Finished - Leave feedback |
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24/6/2024 (Monday) |
26/6/2024 (Wednesday) |
Wait list |
Nationwide |
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5/8/2024 (Monday) |
7/8/2024 (Wednesday) |
Limited availability |
Nationwide |
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16/9/2024 (Monday) |
18/9/2024 (Wednesday) |
Open |
Nationwide |
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28/10/2024 (Monday) |
30/10/2024 (Wednesday) |
Open |
Nationwide |
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9/12/2024 (Monday) |
11/12/2024 (Wednesday) |
Open |
Nationwide |
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