MM - Hadoop ecosystem, Map Reduce, Pig, Hive

Sure! Here are the keywords and short sentences to create mind maps for the key concepts in the "Hadoop Ecosystem: MapReduce, Pig, Hive" topic:

Hadoop Ecosystem

• Overview
  • Distributed computing framework
  • Handles big data
  • Core components: HDFS, YARN, MapReduce

MapReduce

• Concepts
  • Programming model
  • Parallel processing
• Phases
  • Map Phase
    • Input: key/value pairs
    • Process data, generate intermediate pairs
  • Shuffle and Sort Phase
    • Group, sort intermediate keys
    • Transfer data to reducers
  • Reduce Phase
    • Aggregate intermediate data
    • Produce final output
• Example
  • Word count: <word, 1>
  • Group, sum values

Pig

• Overview
  • High-level platform on Hadoop
  • Language: Pig Latin
• Features
  • Simplifies data transformations
  • Extensible with custom functions
  • Optimizes execution
• Workflow
  • Load data: LOAD
  • Transform data: FILTER, GROUP, JOIN
  • Output: DUMP, STORE
• Example
  • Tokenize, count words

Hive

• Overview
  • Data warehousing on Hadoop
  • SQL-like language: HiveQL
• Features
  • Familiar SQL constructs
  • Schema on read
  • Integrates with BI tools
• Workflow
  • Define schema: CREATE TABLE
  • Load data: LOAD DATA
  • Query data: SELECT, JOIN, GROUP BY
• Example
  • Create, load tables
  • Explode, count words

Mind Map Structure

1. Hadoop Ecosystem

   • MapReduce

     • Concepts
       • Programming model
       • Parallel processing
     • Phases
       • Map Phase
         • Input: key/value pairs
         • Process data, generate intermediate pairs
       • Shuffle and Sort Phase
         • Group, sort intermediate keys
         • Transfer data to reducers
       • Reduce Phase
         • Aggregate intermediate data
         • Produce final output
     • Example
       • Word count: <word, 1>
       • Group, sum values

   • Pig

     • Overview
       • High-level platform on Hadoop
       • Language: Pig Latin
     • Features
       • Simplifies data transformations
       • Extensible with custom functions
       • Optimizes execution
     • Workflow
       • Load data: LOAD
       • Transform data: FILTER, GROUP, JOIN
       • Output: DUMP, STORE
     • Example
       • Tokenize, count words

   • Hive

     • Overview
       • Data warehousing on Hadoop
       • SQL-like language: HiveQL
     • Features
       • Familiar SQL constructs
       • Schema on read
       • Integrates with BI tools
     • Workflow
       • Define schema: CREATE TABLE
       • Load data: LOAD DATA
       • Query data: SELECT, JOIN, GROUP BY
     • Example
       • Create, load tables
       • Explode, count words

These keywords and short sentences should help you recall the key concepts and create effective mind maps for future reference.