الدرس 9 | Apache Hadoop

قائمة الدروس

  1. 1. Course Overview
  2. 2.1. Big Data Introduction Data Variety
  3. 2.2. Big Data Introduction Distributed Systems
  4. 2.3. Big Data Introduction What is Big Data?
  5. 2.4. Big Data Introduction Why Do We Need Big Data Now?
  6. 2.5 Big Data Introduction Big Data Applications - Recommendations
  7. 2.6 Big Data Introduction Big Data Applications - A/B Testing
  8. 2.7 Big Data Introduction Big Data Customers
  9. 2.8. Big Data Introduction Big Data Solutions
  10. 2.9. Big Data Introduction What Is Apache Hadoop?
  11. 2.11. Big Data Introduction Overview Of Apache Hadoop Ecosystem
  12. 3.1. Lab Overview Introduction
  13. 4.1. Apache Zookeeper Race Condition
  14. 4.2. Apache Zookeeper Deadlock
  15. 4.3. Apache Zookeeper Coordination
  16. 4.4. Apache Zookeeper Introduction
  17. 4.5. Apache Zookeeper Hands-On - Getting Started
  18. 4.6. Apache Zookeeper Data Model
  19. 4.7. Apache Zookeeper Znode Types
  20. 4.8. Apache Zookeeper Hands-On - Znodes
  21. 4.8.1. Ambari Zookeeper - Establishing Server Connection
  22. 4.9. Apache Zookeeper Architecture
  23. 4.11. Apache Zookeeper Election & Majority
  24. 4.12. Apache Zookeeper Sessions
  25. 4.13. Apache Zookeeper Application
  26. 5.1. HDFS Why HDFS?
  27. 5.2. HDFS NameNode & DataNodes
  28. 5.3. HDFS Design & Limitations
  29. 5.4. HDFS Replication
  30. 5.5. HDFS File Reading
  31. 5.6. HDFS Namenode Backup & Failover
  32. 5.7. HDFS Hands-On with Ambari
  33. 5.8. HDFS Hands-On with Hue
  34. 6.1. YARN Why YARN?
  35. 6.2. YARN Evolution From MapReduce 1.0
  36. 6.3. YARN Architecture
  37. 7.1. Mapreduce Basics Understanding Sorting
  38. 7.2. Mapreduce Basics Overview
  39. 7.3. Mapreduce Basics Thinking In MR - Programatic & SQL
  40. 7.4. Mapreduce Basics Thinking In MR - Unix Pipeline
  41. 7.5. Mapreduce Basics Thinking In MR - External Sort
  42. 8.1. Mapreduce Programming Writing MapReduce Code Using Java
  43. 8.2. Mapreduce Programming Building MapReduce Project Using Apache Ant
  44. 8.3. Mapreduce Programming Writing MapReduce Code Using Eclipse
  45. 8.4. Mapreduce Programming Writing MapReduce Code Using Eclipse (Windows)
  46. 8.5. Mapreduce Programming Run MapReduce Jobs Using Hadoop Streaming
  47. 9.1. Pig Introduction
  48. 9.2. Pig Execution Modes
  49. 9.3. Pig Data Types
  50. 9.4. Pig Relational Operators - Load, Store And Dump
  51. 9.5. Pig Lazy Evaluation
  52. 10.1. Hive Introduction
  53. 10.2. Hive Data Types
  54. 10.3. Hive Getting Started - Hands-On
  55. 10.4. Hive Tables
  56. 10.5. Hive Managed Tables - Hands-On
  57. 10.6. Hive External Tables - Hands On
  58. 10.7. Hive Select And Aggregation Queries
  59. 10.8. Hive Saving Data
  60. 10.9. Hive DDL - Alter Table
  61. 11.1. Sqoop Introduction
  62. 11.2. Sqoop Sqoop Import - MySQL To HDFS
  63. 11.3. Sqoop Sqoop Import - MySQL To Hive
  64. 12.1. Flume Introduction
  65. 12.2. Flume Agents
  66. 12.3. Flume Sources & Delivery Reliability
  67. 12.4. Flume Hands-On Demo On CloudxLab
  68. 12.5. Flume Summary
  69. 13.1. Oozie Introduction
  70. 13.2. Oozie Running Sqoop Action Using Oozie From Hue
  71. 14.1. NoSQL Scaling Out / Up
  72. 14.2. NoSQL ACID Properties And RDBMS Story
  73. 14.3. NoSQL Types Of NoSQL Stores
  74. 14.4. NoSQL CAP Theorem
  75. 15.1. HBase Introduction
  76. 15.2. HBase Architecture
  77. 15.4. HBase Data Model
  78. 15.5. HBase Design Guidelines
  79. 15.6. HBase Data Model Example
  80. 15.7. HBase Hands On With Hue
  81. 15.8. HBase Hands-On With Console
  82. 15.9. HBase Data Location
  83. 15.11. HBase Bloom Filter
  84. 15.12. HBase REST
  85. 15.3. HBase Architecture - Regions
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2.8. Big Data Introduction   Big Data Solutions

ترتيب الدرس : 09

00:00:52

2.8. Big Data Introduction Big Data Solutions

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