Big Data Hadoop and Spark Developer Certification Training
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Course Overview

It is an extensive training course which is designed by Hadoop industry experts to help you grasp the modules of Spark and Big Data Hadoop modules pondering the present job requirements in the market. This certification course is industry-recognized that is a mere amalgamation of training courses in Hadoop administrator, Hadoop developer, analytics with Apache Spark, and Hadoop testing.

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Big Data Hadoop and Spark Developer Certification Training
Key Features Course Content Course Fees Projects Certification Testimonials FAQs
Course Overview
  • 60 hours of instructor LED live training
  • World Class Training By Industry Experts
  • Live Server Based Hands-On Training
  • 500000 Learner Placement 200000 Global Placement
  • Average CTC: 6 LPA / Highest CTC: 52 LPA
  • Global Certification Program Designed By Top University Professors From USA, UK, Australia
  • Faculties from Harvard, MIT, Stanford, IIT, IIM
  • First Global EdTech Firm Backed With 20 Years Of Classroom Training Portfolio
  • World’s Top Tech Training Brand To Offer Absolute Placement Assistance With Global Exposure
  • Most Trusted Brand In Tech Training With 100+ Awards & Acknowledgments
  • 15+ Capstone Project
  • Dedicated one on one career mentor
  • 500+ Top Global MNC Placement Partner

Big Data Hadoop and Spark Developer Certification Training Content

1.1 Distributed processing of Pig and Map Reducing Framework
1.2 Navigating the Hadoop ecosystem and ways to optimize it
1.3 Basics of scala and Functional programming
1.4 Processing real-time streaming data
1.5 Working with RDD in Apache Spark
1.6 Learning about Apache Spark
1.7 Ingesting of data using Flume, Sqoop, and Kafka
1.8 Performing data frame operations using SQL
1.9 Partitioning, implementation, indexing and bucketing in Hive

2.1 Comprehending the working mechanism of MR
2.2 Interpretation of reducing stages and mapping in MR
2.3 Diving deep in several terminologies of MR like partitioners, shuffle, sort, output, and input format

3.1 Descriptive planning of Hive
3.2 Constructing table, group, and database by other clauses
3.3 Comparison of Hive with RDBMS and Pig
3.4 Storing of Hive Partitioning, hive results, and buckets
3.5 Operating with Hive language
3.6 Getting a hang of several types of HCatalog and hive tables

4.1 Introducing impala
4.2 Indication in Hive
4.3 Comparison between Impala and hive
4.4 Performing with complex data type
4.5 Descriptive planning of impala

5.1 Drawbacks of Sqoop
5.2 Input and output of data
5.3 Defining Cap theorem and HBase
5.4 Introducing Apache Sqoop
5.5 Improvement in performance with Sqoop
5.6 Understanding and introducing Flume

6.1 Several schema and data types in Hive
6.2 Introducing Apache Pig along with its several characteristics
6.3 Functions availability in Tuples, pig, hive bags and fields

7.1 Overview of RDD
7.2 Data sources of RDD
7.3 Operations of RDD
7.4 Saving and construction of RDD’s

8.1 MR
8.2 Other paired RDD operations
8.3 The key value of paired RDD

9.1 Execution of transformation
9.2 Passing and writing functions of transformation
9.3 Conversions between DataFrames and RDD

10.1 Constructing datasets
10.2 Operations of datasets
10.3 Dataframes and datasets
10.4 Storing and loading of datasets

11.1 Generating of streaming DataFrames
11.2 Conversion of DataFrames
11.3 Accomplishing streaming querries
11.4 Overview of Apache Spark Streaming

12.1 affixing streaming DataFrames
12.2 streaming combination

13.1 Obtaining Kafka messages
13.2 An outline
13.3 Conveying Kafka messages

14.1 HDFS Planning
14.2 Cluster components of Apache Hadoop
14.3 Employing HDFS

15.1 Commencement of Spark Shell
15.2 Operating Spark Shell
15.3 Dataframe performance
15.4 Defining Apache Spark

16.1 Partitions of RDD
16.2 Planning of job accomplishments
16.3 Different tasks and stages
16.4 Review of Apache spark on cluster

17.1 ML
17.2 Similar cases of Apache Spark
17.3 Repetitive algorithms in Spark

18.1 Creation and administration of the application
18.2 Web UI of the application
18.3 Noting the application
18.4 Presenting the properties of the application
18.5 Deployment mode of application

19.1 Checking consistent data
19.2 Dataset and DataFrames consistency
19.3 Storage level

20.1 Querying views and files
20.2 Tables in Spark with SQL usage
20.3 API Catalog

21.1 Accumulation and assembling of queries
21.2 Utilizing column expressions for querying data frames
21.3 Uniting data frames
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    Big Data Hadoop and Spark Developer Certification Training Projects

    In this Hadoop YARN project, we make use of transaction data that is recorded every day in Relational Database Management System (RDBMS) by transferring it into the Hadoop Distributed File System (HDFS) for big data analytics. You will get the opportunity to work on live YARN cluster, which is a part of the Hadoop ecosystem which allows Hadoop to separate Mapreduce and position a competitive procession and huge array of apps.

    This project will allow you to connect the penhato with Hadoop. Penhato works quite fine with Hbase, Zookeeper, HDFS, and Oozie. You will learn ways to connect a cluster of Hadoop with Penhato data analytics, report designer, penhato server, and integration. It will allow you to enhance a complete knowledge of the Penhato ETL tool.

    This project will allow you to analyze tweets on Twitter by making use of Twitter API. You will get the opportunity to do programming making use of PHP or Python and integrate the twitter API to develop the necessary serverside codes. Also, it will allow you to read the outcomes of several operations by parsing, aggregating, and filtering it, depending on the requirement of the tweet analysis.

    This is an explicit Apache Spark project positioned for the real world app of movie recommendations. This project will allow you to get the required know-how in Spark MiLib also known as Machine Learning Library. Also, you will learn how to create a collaborative regression, filtering, dimensionally reduction and clustering making use of MiLib. After you have completed this project, you will get an experience of Apache Spark sampling, statistics, streaming data analysis, testing, and other required skills.

    You will get the opportunity to get in-hand experience of analyzing Wikipedia data using the Spark SQL tool in this project. Also, the first-hand experience can be obtained in the integration of Spark SQL for several applications including batch analysis, ML, processing of data, visualizing, real-time analysis of data and ETL processes

    Big Data Hadoop Course Fee

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    Online Classroom

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    Corporate Training
    • 36 hours of instructor-led online training
    • Flexibility to choose classes
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    All Our Programs Include

    This training course is designed to help you clear the Cloudera Spark and Hadoop Developer Certification (CCA175) exams.

    Real-world projects from industry experts

    With real world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want.

    Technical mentor support support

    With real world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want.

    Personal career coach and career services

    With real world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want.

    Flexible learning program

    With real world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want.

    ENROLL NOW
    Big Data Hadoop and Spark Developer Certification Training Certification

    This training program is specially designed by Hadoop experts to help you master the Cloudera Spark and Hadoop Developer Certification or CC175 exams. The course content is on the edge with these explicit certification programs which helps you clear these exams with ease to help you attain the best jobs in the top-performing MNC’s.

    This training program is specially designed by Hadoop experts to help you master the Cloudera Spark and Hadoop Developer Certification or CC175 exams. The course content is on the edge with these explicit certification programs which helps you clear these exams with ease to help you attain the best jobs in the top-performing MNC’s. The Big data training course will provide you insights into the tools and methodologies of Big Data along with the Hadoop ecosystem for preparing you to succeed as a Big data Engineer. The certification by Skill Interface will certify to your on job expertise along with your Big data skills. Upon completing this program, several quizzes would be conducted which would reflect the kind of questions asked to help you perform better in the exam. A course completion certificate will be granted on the completion of this project and scoring at least 60% in the quiz.

    Student Reviews
    4.5   (1.2k)
    FAQ’s

    It is very well known that the demand for Hadoop professionals outruns the supply, which is why choosing Hadoop as a career option is a great choice for your career. Skill Interface is one of the most well-versed websites which will help you to equip you to master the course by starting from scratch. Skill Interface training course includes major components of Hadoop and Big Data like MR, Pig, Apache Spark, HDFS, Oozie, Sqoop, Flume, and much more. The entire training has been curated by industry professionals to provide you top-class experience. 24/7 lifetime support, videos, high-quality course material, and free upgrade to the latest version of the courses are some of the added benefits of this course.

    Big data is known as a collection of a large volume of data that includes structured, unstructured as well as semi-structured data which comes from huge data sources that have distinct formats. These data sets are broad and complex which is why they can't be processed making use of traditional techniques. Big data when combined with analytics helps in making better decisions and solving business problems more effectively.

    Yes, you can learn Hadoop without a programming background. Al you need to do is brush up your Linux and Java skills to help you in learning Hadoop technologies and programs in a better and a much faster way.

    Skill interface offers you the most relevant, up to date and high-value real-life projects as a part of this session which helps you in implementing the acquired skills in the real-world industry set up in a better manner. This training comes with various projects that test your learning, skills, and in-hand knowledge to make you industry-ready. You will get the opportunity to work on explicit domains of commerce, sales, banking, technology, marketing, e-commerce, and much more. These skills will equip you as equal to 6 months trained professional.

    Skill Interface provides placement assistance to every student who has completed their training session. Our websites have tied up with top MNC’s from the world to help you get placed in one of the most outstanding organizations. The skill interface also helps you in preparing you for the interviews and equipping your resume.

    You can enroll in self-paced training or instructor-led live online training at Skill Interface. You are also provided with corporate training to upskill your talents. The organization has several years of relevant industry experience that makes them subject matter experts.

    The organization helps the learners in learning at their pace by providing you several benefits of query resolution through live sessions with trainers, email, access to learning modules of the organization for a lifetime, and round the clock support. It also provides you the latest version of the course without extra cost.

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