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Big Data Hadoop Certification Training - Sydney, Australia
Intellipaat Big Data Hadoop training course lets you master Big Data Hadoop and Spark at Sydney to get ready for the Cloudera CCA Spark and Hadoop Developer Certification (CCA175), as well as master Hadoop administration with 14 real-time industry-oriented case-study projects.
About Big Data Hadoop Certification Training Course
What will you learn in this Big Data Hadoop course?
- Fundamentals of Hadoop
- Writing applications on YARN
- Working on Hadoop components like HDFS, Hive, Pig, MapReduce, Spark, Oozie, Flume, etc.
- Configuring pseudo-node and multi-node clusters
- Managing, monitoring, administering and troubleshooting the Hadoop cluster
- Working with Avro data formats
- Working on Spark, Spark RDD, MLlib and GraphX
- Concepts of Big Data Analytics
- Testing Hadoop applications
Who should take up this Big Data Hadoop online training course?
- Programming Developers and System Administrators
- Experienced working professionals and Project Managers
- Big Data Hadoop Developers eager to learn other verticals like Testing, Analytics and Administration
- Mainframe Professionals, Architects and Testing Professionals
- Business Intelligence, Data warehousing and Analytics Professionals
- Graduates and undergraduates eager to learn the latest Big Data technology
What are the prerequisites for learning Hadoop?
There is no pre-requisite to take up this Big Data training and to master Hadoop. But basics of UNIX, SQL and Java would be beneficial. At Intellipaat, we provide the complimentary Linux and Java courses with our Big Data certification training to brush-up the required skills so that you are good on your Hadoop learning path.
What are the Hadoop job opportunities in Sydney?
Sydney is the economic and financial hub for the world’s top-notch firms in the entire Asia Pacific region. Growing at a swift pace, this city is filled with the companies which are investing heavily into research and analytics. As Big Data is driving most of the industries nowadays, the application of technologies like Hadoop is rising rapidly. Therefore, there is a huge scope of Hadoop professionals in this city.
What is the Hadoop market trend in Sydney?
Sydney is one of the most developed cities in Australia inviting investors from across the globe. As Data Analytics has emerged as a vital operation over past few years, the companies have started paying extra attention towards extracting meaningful insights from these data. As it is possible only through skilled Big Data professionals, the trend for job opportunities is constantly going upwards in this city.
Why should you learn Big Data and Hadoop?
- Global Hadoop market to reach $84.6 billion in two years – Allied Market Research
- The number of jobs for all the US Data Professionals will increase to 2.7 million per year – IBM
- A Hadoop Administrator in the US can get a salary of $123,000 – Indeed
Big Data has become the definite way to success in this highly digitized technology world. Since Hadoop is a prominent name in this direction, learning this technology will help the candidates launch their careers in this space.
What Hadoop projects will you be working on?
As part of this training, learners will be carrying out 14 real-time projects based on Hadoop and its components like MapReduce, Hive, Spark, Pig, Oozie, Flume, Weblog Analytics, etc. Moreover, this training course helps them prepare for CCA175 and CCAH exams through practical lab sessions, assignments and interactive sessions.
Big Data Hadoop Course Content
Hadoop Installation and Setup
The architecture of Hadoop 2.0 cluster, what is High Availability and Federation, how to setup a production cluster, various shell commands in Hadoop, understanding configuration files in Hadoop 2.0, installing single node cluster with Cloudera Manager and understanding Spark, Scala, Sqoop, Pig and Flume
Introduction to Big Data Hadoop and Understanding HDFS and MapReduce
Introducing Big Data and Hadoop, what is Big Data and where does Hadoop fit in, two important Hadoop ecosystem components, namely, MapReduce and HDFS, in-depth Hadoop Distributed File System – Replications, Block Size, Secondary Name node, High Availability and in-depth YARN – resource manager and node manager
Hands-on Exercise: HDFS working mechanism, data replication process, how to determine the size of the block, understanding a data node and name node
Deep Dive in MapReduce
Learning the working mechanism of MapReduce, understanding the mapping and reducing stages in MR, various terminologies in MR like Input Format, Output Format, Partitioners, Combiners, Shuffle and Sort
Hands-on Exercise: How to write a Word Count program in MapReduce, how to write a Custom Partitioner, what is a MapReduce Combiner, how to run a job in a local job runner, deploying unit test, what is a map side join and reduce side join, what is a tool runner, how to use counters, dataset joining with map side and reduce side joins
Introduction to Hive
Introducing Hadoop Hive, detailed architecture of Hive, comparing Hive with Pig and RDBMS, working with Hive Query Language, creation of database, table, Group by and other clauses, various types of Hive tables, HCatalog, storing the Hive Results, Hive partitioning and Buckets
Hands-on Exercise: Database creation in Hive, dropping a database, Hive table creation, how to change the database, data loading, Hive table creation, dropping and altering table, pulling data by writing Hive queries with filter conditions, table partitioning in Hive and what is a Group by clause
Advanced Hive and Impala
Indexing in Hive, the Map Side Join in Hive, working with complex data types, the Hive User-defined Functions, Introduction to Impala, comparing Hive with Impala, the detailed architecture of Impala
Hands-on Exercise: How to work with Hive queries, the process of joining table and writing indexes, external table and sequence table deployment and data storage in a different table
Introduction to Pig
Apache Pig introduction, its various features, various data types and schema in Hive, the available functions in Pig, Hive Bags, Tuples and Fields
Hands-on Exercise: Working with Pig in MapReduce and local mode, loading of data, limiting data to 4 rows, storing the data into files and working with Group By, Filter By, Distinct, Cross, Split in Hive
Flume, Sqoop and HBase
Apache Sqoop introduction, overview, importing and exporting data, performance improvement with Sqoop, Sqoop limitations, introduction to Flume and understanding the architecture of Flume and what is HBase and the CAP theorem
Hands-on Exercise: Working with Flume to generating of Sequence Number and consuming it, using the Flume Agent to consume the Twitter data, using AVRO to create Hive Table, AVRO with Pig, creating Table in HBase and deploying Disable, Scan and Enable Table
Writing Spark Applications Using Scala
Using Scala for writing Apache Spark applications, detailed study of Scala, the need for Scala, the concept of object oriented programming, executing the Scala code, various classes in Scala like Getters, Setters, Constructors, Abstract, Extending Objects, Overriding Methods, the Java and Scala interoperability, the concept of functional programming and anonymous functions, Bobsrockets package and comparing the mutable and immutable collections, Scala REPL, Lazy Values, Control Structures in Scala, Directed Acyclic Graph (DAG), first Spark application using SBT/Eclipse, Spark Web UI, Spark in Hadoop ecosystem.
Hands-on Exercise: Writing Spark application using Scala, understanding the robustness of Scala for Spark real-time analytics operation
Spark framework
Detailed Apache Spark, its various features, comparing with Hadoop, various Spark components, combining HDFS with Spark, Scalding, introduction to Scala and importance of Scala and RDD
Hands-on Exercise: The Resilient Distributed Dataset in Spark and how it helps to speed up Big Data processing
RDD in Spark
Understanding the Spark RDD operations, comparison of Spark with MapReduce, what is a Spark transformation, loading data in Spark, types of RDD operations viz. transformation and action and what is a Key/Value pair
Hands-on Exercise: How to deploy RDD with HDFS, using the in-memory dataset, using file for RDD, how to define the base RDD from external file, deploying RDD via transformation, using the Map and Reduce functions and working on word count and count log severity
Data Frames and Spark SQL
The detailed Spark SQL, the significance of SQL in Spark for working with structured data processing, Spark SQL JSON support, working with XML data and parquet files, creating Hive Context, writing Data Frame to Hive, how to read a JDBC file, significance of a Spark Data Frame, how to create a Data Frame, what is schema manual inferring, how to work with CSV files, JDBC table reading, data conversion from Data Frame to JDBC, Spark SQL user-defined functions, shared variable and accumulators, how to query and transform data in Data Frames, how Data Frame provides the benefits of both Spark RDD and Spark SQL and deploying Hive on Spark as the execution engine
Hands-on Exercise: Data querying and transformation using Data Frames and finding out the benefits of Data Frames over Spark SQL and Spark RDD
Machine Learning Using Spark (MLlib)
Introduction to Spark MLlib, understanding various algorithms, what is Spark iterative algorithm, Spark graph processing analysis, introducing Machine Learning, K-Means clustering, Spark variables like shared and broadcast variables and what are accumulators, various ML algorithms supported by MLlib, Linear Regression, Logistic Regression, Decision Tree, Random Forest, K-means clustering techniques, building a Recommendation Engine
Hands-on Exercise: Building a Recommendation Engine
Integrating Apache Flume and Apache Kafka
Why Kafka, what is Kafka, Kafka architecture, Kafka workflow, configuring Kafka cluster, basic operations, Kafka monitoring tools, integrating Apache Flume and Apache Kafka
Hands-on Exercise: Configuring Single Node Single Broker Cluster, Configuring Single Node Multi Broker Cluster, Producing and consuming messages, Integrating Apache Flume and Apache Kafka.
Spark Streaming
Introduction to Spark streaming, the architecture of Spark streaming, working with the Spark streaming program, processing data using Spark streaming, requesting count and DStream, multi-batch and sliding window operations and working with advanced data sources, Introduction to Spark Streaming, features of Spark Streaming, Spark Streaming workflow, initializing StreamingContext, Discretized Streams (DStreams), Input DStreams and Receivers, transformations on DStreams, Output Operations on DStreams, Windowed Operators and why it is useful, important Windowed Operators, Stateful Operators.
Hands-on Exercise: Twitter Sentiment Analysis, streaming using netcat server, Kafka-Spark Streaming and Spark-Flume Streaming
Hadoop Administration – Multi-node Cluster Setup Using Amazon EC2
Create a 4-node Hadoop cluster setup, running the MapReduce Jobs on the Hadoop cluster, successfully running the MapReduce code and working with the Cloudera Manager setup
Hands-on Exercise: The method to build a multi-node Hadoop cluster using an Amazon EC2 instance and working with the Cloudera Manager
Hadoop Administration – Cluster Configuration
The overview of Hadoop configuration, the importance of Hadoop configuration file, the various parameters and values of configuration, the HDFS parameters and MapReduce parameters, setting up the Hadoop environment, the Include and Exclude configuration files, the administration and maintenance of name node, data node directory structures and files, what is a File system image and understanding Edit log.
Hands-on Exercise: The process of performance tuning in MapReduce
Hadoop Administration – Maintenance, Monitoring and Troubleshooting
Introduction to the checkpoint procedure, name node failure and how to ensure the recovery procedure, Safe Mode, Metadata and Data backup, various potential problems and solutions, what to look for and how to add and remove nodes
Hands-on Exercise: How to go about ensuring the MapReduce File System Recovery for different scenarios, JMX monitoring of the Hadoop cluster, how to use the logs and stack traces for monitoring and troubleshooting, using the Job Scheduler for scheduling jobs in the same cluster, getting the MapReduce job submission flow, FIFO schedule and getting to know the Fair Scheduler and its configuration
ETL Connectivity with Hadoop Ecosystem
How ETL tools work in Big Data industry, introduction to ETL and data warehousing, working with prominent use cases of Big Data in ETL industry and end-to-end ETL PoC showing Big Data integration with ETL tool
Hands-on Exercise: Connecting to HDFS from ETL tool and moving data from Local system to HDFS, moving data from DBMS to HDFS, working with Hive with ETL Tool and creating MapReduce job in ETL tool
Project Solution Discussion and Cloudera Certification Tips and Tricks
Working towards the solution of the Hadoop project solution, its problem statements and the possible solution outcomes, preparing for the Cloudera certifications, points to focus for scoring the highest marks and tips for cracking Hadoop interview questions
Hands-on Exercise: The project of a real-world high value Big Data Hadoop application and getting the right solution based on the criteria set by the Intellipaat team
Following topics will be available only in self-paced mode:
Hadoop Application Testing
Why testing is important, Unit testing, Integration testing, Performance testing, Diagnostics, Nightly QA test, Benchmark and end-to-end tests, Functional testing, Release certification testing, Security testing, Scalability testing, Commissioning and Decommissioning of data nodes testing, Reliability testing and Release testing
Roles and Responsibilities of Hadoop Testing Professional
Understanding the Requirement, preparation of the Testing Estimation, Test Cases, Test Data, Test Bed Creation, Test Execution, Defect Reporting, Defect Retest, Daily Status report delivery, Test completion, ETL testing at every stage (HDFS, Hive and HBase) while loading the input (logs, files, records, etc.) using Sqoop/Flume which includes but not limited to data verification, Reconciliation, User Authorization and Authentication testing (Groups, Users, Privileges, etc.), reporting defects to the development team or manager and driving them to closure, consolidating all the defects and create defect reports, validating new feature and issues in Core Hadoop
Framework Called MRUnit for Testing of MapReduce Programs
Report defects to the development team or manager and driving them to closure, consolidate all the defects and create defect reports, responsible for creating a testing framework called MRUnit for testing of MapReduce programs
Unit Testing
Automation testing using the OOZIE and data validation using the query surge tool
Test Execution
Test plan for HDFS upgrade, test automation and result
Test Plan Strategy and Writing Test Cases for Testing Hadoop Application
How to test, install and configure
What Hadoop Projects You Will Be Working on?
Highlights:
- Sqoop data transfer from RDBMS to Hadoop
- Coding in Hive Query Language
- Data querying and analysis
Highlights:
- MapReduce program for working on the data file
- Apache Pig for analyzing data
- Apache Hive data warehousing and querying
Highlights:
- Using Sqoop commands to bring the data into HDFS
- End-to-end flow of transaction data
- Working with the data from HDFS
Highlights:
- Manual Partitioning
- Dynamic Partitioning
- Bucketing
Highlights:
- Working knowledge of ETL and Business Intelligence
- Configuring Pentaho to work with Hadoop distribution
- Loading, transforming and extracting data into Hadoop cluster
Highlights:
- Hadoop installation and configuration
- Running a Hadoop multi-node using a 4-node cluster on Amazon EC2
- Deploying of MapReduce job on the Hadoop cluster
Highlights:
- Writing JUnit tests using MRUnit for MapReduce applications
- Doing mock static methods using PowerMock and Mockito
- MapReduce Driver for testing the map and reduce pair
Highlights:
- Aggregation of log data
- Apache Flume for data transportation
- Processing of data and generating analytics
Highlights:
- Working with name node directory structure
- Audit logging, data node block scanner and balancer
- Failover, fencing, DISTCP and Hadoop file formats
Highlights:
- Download the tweets and load into Pig storage
- Divide tweets into words to calculate sentiment
- Rating the words from +5 to −5 on AFFIN dictionary
- Filtering the tweets and analyzing sentiment
Highlights:
- Load the data into HDFS
- Analyze the data using Apache Pig or Hive
- Based on user queries give the right output
Apache Spark Projects
Highlights:
- Apache Spark MLlib component
- Statistical analysis
- Regression and clustering
Highlights:
- Making requests to Twitter API
- Building the server-side codes
- Filtering, parsing and aggregating data
Highlights:
- Machine Learning using Spark
- Deploying data visualization
- Spark SQL integration
Sample Big Data Video Tutorials
Hadoop Tutorial
About Big Data Course
Hive Introduction
Existing Learner Feedback
It is a known fact that the demand for Hadoop professionals far outstrips the supply. So, if you want to learn and make a career in Hadoop, then you need to enroll for Intellipaat Hadoop course which is the most recognized name in Hadoop training and certification. Intellipaat Hadoop training includes all major components of Big Data and Hadoop like Apache Spark, MapReduce, HBase, HDFS, Pig, Sqoop, Flume, Oozie and more. The entire Intellipaat Hadoop training has been created by industry professionals. You will get 24/7 lifetime support, high-quality course material and videos and free upgrade to latest version of course material. Thus, it is clearly a one-time investment for a lifetime of benefits.
Big Data Hadoop Certification
This training course is designed to help you clear the Cloudera Spark and Hadoop Developer Certification (CCA175) exams. The entire training course content is in line with these certification programs and helps you clear these certification exams with ease and get the best jobs in the top MNCs.
As part of this training, you will be working on real-time projects and assignments that have immense implications in the real-world industry scenarios, thus helping you fast-track your career effortlessly.
At the end of this training program, there will be quizzes that perfectly reflect the type of questions asked in the respective certification exams and help you score better.
Intellipaat Course Completion Certificate will be awarded upon the completion of the project work (after expert review) and upon scoring at least 60% marks in the quiz. Intellipaat certification is well recognized in top 80+ MNCs like Ericsson, Cisco, Cognizant, Sony, Mu Sigma, Saint-Gobain, Standard Chartered, TCS, Genpact, Hexaware, etc.
Big Data Hadoop Training Review
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Disclaimer
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- To avail this offer, enroll before 19th April 2019.
- This offer cannot be combined with any other offer.
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Thankful to Intellipaat
I'm really thankful to Intellipaat about the Hadoop Architect Course with Big Data certification. First of all, the team supported me in finding the best Big Data online course based on my experiences and current assignment. Also, the session is so practical, and the trainers are seasoned and available for any queries even in offline mode after the sessions of Big Data Hadoop course. I'm really recommending this training to anyone who wants to understand the concept of Big Data by learning Hadoop and its ecosystem and obtain a most valuable certification in Hadoop from a recognized institution.
This course is worth the money and time.
I got practical exposure to Big Data tools with real-world projects. Instructors taught both theory and implementations of concepts. This Hadoop training was just what I was looking for.
I am really looking forward for a long association with Intellipaat.
I found Intellipaat to be one of the best online learning platform for the latest technologies. Trainers have very sound knowledge and are always ready to help. I completed Hadoop certification course, and my learning experience has been great. I highly recommend Intellipaat to every learner who is interested in Hadoop.
Impactful training videos
Hi, Intellipaat Big Data course video quality is of the highest level. I had enrolled for the self-paced Big Data Hadoop training; the videos offered the best platform for learning at one’s leisurely pace, since it has been created by industry experts and the attention to detail and real-world examples in the videos are worth mentioning. According to me, this is an industry-recognized Big Data certification training.
Qualified support team
Full marks for the Intellipaat support team for providing excellent support services. Hadoop was new to me and I used to have many queries, but the support team was very qualified and very patient in listening to my queries and resolving them to my highest expectations. The entire Big Data course was completely oriented towards the practical aspects.
Great Learning
I am very much happy with the Intellipaat big data Hadoop training. The trainer knowledge and experience was very good. I got more than what I had expected as part of the training program and because of this I could easily master the Hadoop technology. I would recommend the Intellipaat big data course to all.
Great Learning
I am completely satisfied with the Intellipaat big data hadoop training. The trainer came with over a decade of industry experience. The entire big data online course was segmented into modules that were created with care so that the learning is complete and as per the industry needs.
Great learning – Cleared Cloudera Certification – Got job in Cognizant
I wanted to learn big data since it had a huge scope. My career changed positively upon completion of Intellipaat Big Data Hadoop Online Training. Go with Intellipaat for a Bright Career !!! Thanks.
The best investment I ever made in my career ! Awesome Learning Experience
I had taken Intellipaat Big Data Hadoop Online. An excellent online mode of learning. Now I am confident I can look out for a career in Big Data. upon successfully completing this big data course Thanks again and looking forward to a lot more learning from Intellipaat !! I highly recommend the big data online course. All the best.
Great Learning. I highly recommend it.
Recently I completed Big Data Hadoop Certification Training from intellipaat. Great Learning. The best investment I ever made in my career. I've learnt and benefitted a lot from intellipaat big data online course and continue to be a member.
Incredibly good
Thank you very much for your training. The trainer resolved my query in record time and that too as per my utmost sanctification. I have no words to describe my gratitude to Intellipaat.
Exactly what I needed
"Dear Intellipaat team. I am fully satisfied with your services. Thank you for your guidance. I want to make a reference about the quiz at the end of the course that was perfectly designed to gauge my proficiency. Thanks a lot for making it so comprehensive with attention to detail. "
AMAZING Course!!
This Intellipaat Hadoop tutorial has delivered more than what they had promised to me. Since I have undergone previous Hadoop training I am quite familiar with Big Data Hadoop concepts but Intellipaat took it to a different level with their attention to details and Hadoop domain expertise. I recommend this training to everybody. You will learn everything from basic Hadoop concepts to advanced Hadoop technology deployment. I am more than satisfied with this training. Thank you Intellipaat!
Fabulous
A big thank you to the entire Intellipaat Big Data Hadoop Team! You have delivered a great Hadoop online certification training course, with equally informative Hadoop online tutorials, Big Data video tutorials that are absolutely free. Highly experienced and qualified Big Data Hadoop trainers made the learning process completely effortless and enjoyable for me. I am extremely happy for having enrolled for the best Hadoop training!
Good Online Platform
I mastered Hadoop through the Intellipaat Big Data Hadoop online training. Let me frankly tell you that this course is designed in a unique and comprehensive manner that is by far the best. Plus you get loads of free tutorials and video content all along. The entire coursework is easy to understand, very simple language but highly effective from the learner’s point of view. There is a natural flow in the big data Hadoop online training course offered by Intellipaat. This is highly recommended for getting the Hadoop certification.
Awesome Training
This online big data Hadoop training is extremely industry-focused and job-oriented. Overall I am giving 10 out of 10 for this Hadoop certification course from Intellipaat!
Great Course
I wish I knew about Intellipaat online Hadoop training before. I have hugely benefitted from this big data Hadoop certification course. Excellent course material and highly recommended Hadoop trainers will provide you full understanding of Hadoop concepts.
Excellent Course
This is regards to conveying my deepest gratitude to Intellipaat. The quality and methodology of the online Hadoop training is matchless. The self-study program for which I had enrolled for big data Hadoop training ticked all the right boxes. I had access to free tutorials and videos to help me in my learning endeavour. A special mention must be made regarding the promptness and enthusiasm that Intellipaat showed when it comes to query resolution and doubt clearance. Kudos!
Good Stuff
A big data Hadoop online training course that hits the bull’s eye. The Hadoop trainer was a master of big data and Hadoop concepts and implementation. Great to learn at Intellipaat!