Spark cultivation Path--spark learning route, curriculum outline

Source: Internet
Author: User
Tags spark mllib

Course Content
    1. Spark cultivation (Basic)--linux Foundation (15), Akka distributed programming (8 Speak)
    2. Spark Cultivation (Advanced)--spark Introduction to Mastery (30 speak)
    3. Spark cultivation Path (actual combat)--spark application Development Practice (20 Speak)
    4. Spark Cultivation (Advanced)--spark source parsing (50)

Some of the content will be dynamically adjusted, or supplemented, or deleted, when it is actually written.

Spark cultivation (Basic)--linux Big Data Development Foundation (15),
    1. Linux Big Data Development Basics-section I: Ubuntu Linux Installation and introduction
    2. Linux Big Data Development Foundation--section II: Linux File system, directory (i)
    3. Linux Big Data Development Foundation--section III: Linux file systems, directories (ii)
    4. Linux Big Data Development Foundation--fourth: Linux users, groups and rights management
    5. Linux Big Data Development Basics--Fifth: package management
    6. Linux Big Data Development Foundation--sixth: process Management
    7. Linux Big Data Development Foundation--Seventh: network management
    8. Linux Big Data Development Foundation--eighth: SSH principle and application
    9. Linux Big Data Development Foundation--Nineth: VI Programmer (i)
    10. Linux Big Data Development Foundation--Tenth: VI Programmer (II)
    11. Fundamentals of Linux Big Data Development--11th: Shell Programming Basics (i)
    12. Fundamentals of Linux Big Data Development--12th: Shell Programming Basics (ii)
    13. Fundamentals of Linux Big Data Development--13th: Shell Programming Fundamentals (III)
    14. Fundamentals of Linux Big Data Development--14th: Shell Programming Basics (IV)
    15. Linux Big Data Development Basics--15th: Installation and use of Java development environment, MySQL, and Tomcat
Spark cultivation (Basic)--akka concurrent programming (domestic starter, Scala edition)
    1. Akka Concurrent Programming-section I: Introduction to Akka, deployment of development environment and first Akka application
    2. Akka concurrent Programming--section II: Actors, Typed Actors, Actorsystem
    3. Akka Concurrent Programming--section III: Akka fault tolerance mechanism
    4. Akka concurrent Programming--section Fourth: FUTURES and AGENTS
    5. Akka Concurrent Programming--section fifth: Akka message Channel
    6. Akka Concurrent Programming--section sixth: Akka transactions
    7. Akka concurrent Programming--section seventh: Routing, IO, etc.
    8. Akka concurrent Programming--eighth: Akka application Development under distributed environment
Spark Cultivation (Advanced)--spark Introduction to Mastery (30 speak)
  1. Getting started with spark to mastery (Getting started)-section I: Introduction to spark, introducing the spark ecosystem, architecture, and fault-tolerant mechanisms
  2. Introduction to spark to Mastery--section II: Development Environment Deployment (i), Linux system installation, Hadoop cluster setup
  3. Introduction to spark to mastery--section III: Development Environment Deployment (ii), Hadoop cluster setup, spark cluster deployment and testing
  4. Introduction to spark to mastery--fourth: Development environment Deployment (iii), INTELLIJ idea Spark development environment builds and develops the first spark application
  5. Introduction to spark to mastery--fifth: Spark interactive command line, how to use Spark interactive command line, understand Spark task submission process, execute process, if view any execution state through WebUI
  6. Introduction to spark to mastery--sixth: RDD Elastic Distributed data set, Introduction to the RDD implementation principle, understanding of action and transformation, understanding narrow dependencies and wide dependencies
  7. Introduction to spark to mastery--seventh section: RDD Common functions (i)
  8. Spark Primer to Mastery--eighth: RDD common functions (ii)
  9. Spark Primer to Mastery--nineth: RDD common functions (iii)
  10. Spark Primer to Mastery--tenth: Spark job Execution Principle analysis, shuffle operation parsing
  11. Spark Primer to Mastery--11th: Spark broadcast variables and accumulators, cache and checkpoint issues
  12. Getting started with spark to mastering--12th: Spark multi-language programming
  13. Getting started with spark to Mastery (Spark SQL)--13th: Spark SQL components, schemas
  14. Spark Primer to Mastery (spark SQL)--14th: DataFrame, Sparksql operating principle
  15. Getting started with spark to Mastery (Spark SQL)--15th: Spark SQL Basic App
  16. Getting started with spark to Mastery (spark SQL)--16th: Complex application case
  17. Getting started with spark to Mastery (spark SQL)--17th: Sparksql Performance Tuning
  18. Spark Primer to Mastery (spark streaming)-18th: Spark streaming operating principle, DStream
  19. Spark Primer to Mastery (spark streaming)--19th: DStream Common functions (i)
  20. Spark Primer to Mastery (spark streaming)--20th: DStream common functions (ii)
  21. Spark Primer to Mastery (spark streaming)--21st: Application Case Combat
  22. Spark Primer to Mastery (spark MLlib)-22nd section: Machine learning on Spark Introduction, common data structure
  23. Spark Primer to Mastery (spark MLlib)--23rd: Logistic regression algorithm combat
  24. Spark Primer to Mastery (spark MLlib)-24th: K-Mean algorithm combat
  25. Spark Primer to Mastery (spark MLlib)--25th: Collaborative filtering recommendation algorithm combat
  26. Spark Primer to Mastery (spark MLlib)--26th: convolutional Neural network CNN algorithm combat
  27. Spark Primer to Mastery (spark MLlib)--27th: Advanced Text Processing Combat
  28. Getting started with spark to Mastery (spark MLlib)--28th: Real-time machine learning combat based on spark streaming
  29. Spark Primer to Mastery (spark GRAPHX)-29th: Introduction to spark graph calculations, spark GRAPHX architecture and principles
  30. Spark Primer to Mastery (spark GRAPHX)-30th section: GRAPHX common data structures (e.g. vertices, etc.)
  31. Spark Primer to Mastery (spark GRAPHX)-31st section: GRAPHX Basic operations
  32. Spark Primer to Mastery (spark GRAPHX)--32nd: PageRank algorithm Combat
  33. Spark Primer to Mastery (spark R)--33rd: Spark R and closing
Spark cultivation Path (actual combat)--spark application Development Practice (15 Speak)
    1. Spark Application Development Practice-Section One: Spark real-time recommendation system development (i)
    2. Spark Application Development Practice-section II: Spark Real-time recommendation system development (II.)
    3. Spark Application Development Practice-section III: Spark Real-time recommendation system development (III.)
    4. Spark application Development--fourth: Spark real-time recommendation system development (IV)
    5. Spark application Development--fifth: Spark real-time Referral system development (v)
    6. Spark application Development--sixth: Spark SQL website Log analysis (i)
    7. Spark application Development--seventh: Spark SQL website log analysis (ii)
    8. Spark application Development--eighth: Spark SQL website log Analysis (iii)
    9. Spark application Development--nineth: Spark SQL website log analysis (iv)
    10. Spark application Development--tenth: Spark SQL website Log Analysis (v)
    11. Spark application Development--11th: Financial Data Analysis Cases (i)
    12. Spark application Development--12th: Financial Data Analysis Cases (II.)
    13. Spark application Development--13th: Financial Data Analysis Case (iii)
    14. Spark application Development--14th: Financial Data Analysis Cases (iv)
    15. Spark application Development--15th: Financial Data Analysis Cases (v)
Spark Cultivation (Advanced)--spark source parsing (50)
    1. Spark Source parsing--spark Source Analysis environment building, source analysis skills
    2. Spark Source parsing--rdd Source Analysis
    3. Spark Source parsing--sparkcontext Source Analysis
    4. Spark Source parsing--taskscheduler Source Analysis
    5. Spark Source parsing--dagscheduler Source Analysis
    6. Source analysis of Spark source parsing--spark Standalone Scheduler
    7. Spark Source parsing--worker, executor source analysis
    8. Spark Source parsing--mlib Source Analysis
    9. Spark Source parsing--dataframe Source Analysis
    10. Spark Source parsing--dstream Source parsing
    11. ...............................................................

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Spark cultivation Path--spark learning route, curriculum outline

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