apache spark

What is Apache spark?

Apache Spark and Scala Certification Training Course offer you hands-on knowledge to create Spark applications using Scala programming. It gives you a clear comparison between Spark and Hadoop. The course provides you techniques to increase application performance and enable high-speed processing using Spark RDDs as well as help in customization of Spark using Scala.

  • Introduction to Apache Spark
    • Introduction to Spark, how Spark overcomes the drawbacks of working MapReduce, understanding in-memory MapReduce,interactive operations on MapReduce, Spark stack, fine vs. coarse grained update, Spark stack,Spark Hadoop YARN, HDFS Revision, YARN Revision, the overview of Spark and how it is better Hadoop, deploying Spark without Hadoop,Spark history server, Cloudera distribution.
  • Why to attend Xcloudmatrix Online Training ?
    • Classes are conducted by Certified Apache Spark Working Professionals with 100 % Quality Assurance.
      With an experienced Certified practitioner who will teach you the essentials you need to know to kick-start your career on Apache Spark. Our training make you more productive with your Apache Spark Training Online. Our training style is entirely hands-on. We will provide access to our desktop screen and will be actively conducting hands-on labs with real-time projects
  • Apache Spark Training Curriculum
    • Introduction of Spark
      Introduction to Spark, how Spark overcomes the drawbacks of working MapReduce, understanding in-memory MapReduce,interactive operations on MapReduce, Spark stack, fine vs. coarse grained update, Spark stack,Spark Hadoop YARN, HDFS Revision, YARN Revision, the overview of Spark and how it is better Hadoop, deploying Spark without Hadoop,Spark history server, Cloudera distribution.

    • Spark Basics
      Spark installation guide,Spark configuration, memory management, executor memory vs. driver memory, working with Spark Shell, the concept of Resilient Distributed Datasets (RDD), learning to do functional programming in Spark, the architecture of Spark.

    • Working with RDDs in Spark
      Spark RDD, creating RDDs, RDD partitioning, operations & transformation in RDD,Deep dive into Spark RDDs, the RDD general operations, a read-only partitioned collection of records, using the concept of RDD for faster and efficient data processing,RDD action for Collect, Count, Collectsmap, Saveastextfiles, pair RDD functions.

    • Aggregating Data with Pair RDDs
      Understanding the concept of Key-Value pair in RDDs, learning how Spark makes MapReduce operations faster, various operations of RDD,MapReduce interactive operations, fine & coarse grained update, Spark stack.

    • Writing and Deploying Spark Applications
      Comparing the Spark applications with Spark Shell, creating a Spark application using Scala or Java, deploying a Spark application,Scala built application,creation of mutable list, set & set operations, list, tuple, concatenating list, creating application using SBT,deploying application using Maven,the web user interface of Spark application, a real world example of Spark and configuring of Spark.

    • Parallel Processing
      Learning about Spark parallel processing, deploying on a cluster, introduction to Spark partitions, file-based partitioning of RDDs, understanding of HDFS and data locality, mastering the technique of parallel operations,comparing repartition & coalesce, RDD actions.

    • Spark RDD Persistence
      The execution flow in Spark, Understanding the RDD persistence overview,Spark execution flow & Spark terminology, distribution shared memory vs. RDD, RDD limitations, Spark shell arguments,distributed persistence, RDD lineage,Key/Value pair for sorting implicit conversion like CountByKey, ReduceByKey, SortByKey, AggregataeByKey

    • Spark Streaming & Mlib
      Spark Streaming Architecture, Writing streaming programcoding, processing of spark stream,processing Spark Discretized Stream (DStream), the context of Spark Streaming, streaming transformation, Flume Spark streaming, request count and Dstream, multi batch operation, sliding window operations and advanced data sources. Different Algorithms, the concept of iterative algorithm in Spark, analyzing with Spark graph processing, introduction to K-Means and machine learning, various variables in Spark like shared variables, broadcast variables, learning about accumulators.

    • Improving Spark Performance
      Introduction to various variables in Spark like shared variables, broadcast variables, learning about accumulators, the common performance issues and troubleshooting the performance problems.

    • Spark SQL and Data Frames
      Learning about Spark SQL, the context of SQL in Spark for providing structured data processing, JSON support in Spark SQL, working with XML data, parquet files, creating HiveContext, writing Data Frame to Hive, reading JDBC files, understanding the Data Frames in Spark, creating Data Frames, manual inferring of schema, working with CSV files, reading JDBC tables, Data Frame to JDBC, user defined functions in Spark SQL, shared variable and accumulators, learning to query and transform data in Data Frames, how Data Frame provides the benefit of both Spark RDD and Spark SQL, deploying Hive on Spark as the execution engine.

    • Scheduling/ Partitioning
      Learning about the scheduling and partitioning in Spark,hash partition, range partition, scheduling within and around applications, static partitioning, dynamic sharing, fair scheduling,Map partition with index, the Zip, GroupByKey, Spark master high availability, standby Masters with Zookeeper, Single Node Recovery With Local File System, High Order Functions.

      Controllers and Markup
      Introduction to AngularJS Controllers, Controllers and Scope, Creating Controllers, Working with border-image
      Working with colocations in AngularJS
      Displaying Repeating Information, Demo with ng-repeat
      Working with events in AngularJS
      Handling Events, Event Scope, Event Directives
      Built-in Directives
      Working with built in directives, Other Directives
      Working with Expressions in AngularJS
      Expressions
      Working with Expressions in Filters
      Understanding Filters, Built-in Filters
      Two Way Binding in AngularJS
      Impotence of two way binding, Two Way Binding Demo
      Validation
      Importance of validation, Working example
      Creating and Using Services
      Introduction of services in AngularJS, Understanding importance of Services, Working with and Example

  • Salary Trends
    • Average AngularJS Salary in USA is increasing and is much better than other products.
  • Benefits to our Global Learners
    • Xcloudmatrix services are Student-centered learning.
    • Qualitative & cost effective learning at your pace.
    • Geographical access to learn from any part of the world.
  • Course Features


    Instructor-led Sessions

    There will be 24 hours of instructor led Interactive online classes and you will also get access to 2 self-paced videos with 5 hours content.


    Real-life Case Studies

    Towards the end of the Course, you will learn how to create an Angluar Application.


    Assignments

    Each class has practical assignments which shall be finished before the next class and helps you to apply the concepts taught during the class.


    Lifetime Access

    You get lifetime access to the Learning Management System (LMS). Class recordings and presentations can be viewed online from the LMS.


    24 x 7 Expert Support

    We have 24×7 online support team available to help you with any technical queries you may have during the course.


    Certification

    Towards the end of the course, you will be working on a project. Xcloud Matrix certifies you as an Angular Expert based on the project.

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