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Apache Hadoop | CloudxLab Official

CloudxLab Official

CloudxLab Official

The CloudxLab YouTube channel provides the learning content on Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Big Data, Hadoop, Spark and related technologies.. We are a highly motivated team of developers, researchers, and engineers who build fresh and lasting learning experiences for our users. Powered by our innovation processes, we provide a gamified environment where learning is fun and constructive. From creative design to intuitive apps we create a seamless lear

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  1. 1 | 1. Course Overview 00:02:22
  2. 2 | 2.1. Big Data Introduction Data Variety 00:01:03
  3. 3 | 2.2. Big Data Introduction Distributed Systems 00:00:37
  4. 4 | 2.3. Big Data Introduction What is Big Data? 00:01:50
  5. 5 | 2.4. Big Data Introduction Why Do We Need Big Data Now? 00:02:57
  6. 6 | 2.5 Big Data Introduction Big Data Applications - Recommendations 00:02:01
  7. 7 | 2.6 Big Data Introduction Big Data Applications - A/B Testing 00:01:39
  8. 8 | 2.7 Big Data Introduction Big Data Customers 00:02:55
  9. 9 | 2.8. Big Data Introduction Big Data Solutions 00:00:52
  10. 10 | 2.9. Big Data Introduction What Is Apache Hadoop? 00:01:42
  11. 11 | 2.11. Big Data Introduction Overview Of Apache Hadoop Ecosystem 00:05:20
  12. 12 | 3.1. Lab Overview Introduction 00:01:03
  13. 13 | 4.1. Apache Zookeeper Race Condition 00:00:41
  14. 14 | 4.2. Apache Zookeeper Deadlock 00:00:29
  15. 15 | 4.3. Apache Zookeeper Coordination 00:01:10
  16. 16 | 4.4. Apache Zookeeper Introduction 00:00:47
  17. 17 | 4.5. Apache Zookeeper Hands-On - Getting Started 00:01:17
  18. 18 | 4.6. Apache Zookeeper Data Model 00:01:22
  19. 19 | 4.7. Apache Zookeeper Znode Types 00:01:42
  20. 20 | 4.8. Apache Zookeeper Hands-On - Znodes 00:03:26
  21. 21 | 4.8.1. Ambari Zookeeper - Establishing Server Connection 00:00:46
  22. 22 | 4.9. Apache Zookeeper Architecture 00:03:19
  23. 23 | 4.11. Apache Zookeeper Election & Majority 00:01:57
  24. 24 | 4.12. Apache Zookeeper Sessions 00:01:18
  25. 25 | 4.13. Apache Zookeeper Application 00:01:25
  26. 26 | 5.1. HDFS Why HDFS? 00:03:23
  27. 27 | 5.2. HDFS NameNode & DataNodes 00:01:55
  28. 28 | 5.3. HDFS Design & Limitations 00:02:34
  29. 29 | 5.4. HDFS Replication 00:02:57
  30. 30 | 5.5. HDFS File Reading 00:02:49
  31. 31 | 5.6. HDFS Namenode Backup & Failover 00:04:53
  32. 32 | 5.7. HDFS Hands-On with Ambari 00:00:59
  33. 33 | 5.8. HDFS Hands-On with Hue 00:01:14
  34. 34 | 6.1. YARN Why YARN? 00:02:48
  35. 35 | 6.2. YARN Evolution From MapReduce 1.0 00:03:28
  36. 36 | 6.3. YARN Architecture 00:03:26
  37. 37 | 7.1. Mapreduce Basics Understanding Sorting 00:02:02
  38. 38 | 7.2. Mapreduce Basics Overview 00:02:36
  39. 39 | 7.3. Mapreduce Basics Thinking In MR - Programatic & SQL 00:02:43
  40. 40 | 7.4. Mapreduce Basics Thinking In MR - Unix Pipeline 00:03:54
  41. 41 | 7.5. Mapreduce Basics Thinking In MR - External Sort 00:05:00
  42. 42 | 8.1. Mapreduce Programming Writing MapReduce Code Using Java 00:09:52
  43. 43 | 8.2. Mapreduce Programming Building MapReduce Project Using Apache Ant 00:08:11
  44. 44 | 8.3. Mapreduce Programming Writing MapReduce Code Using Eclipse 00:07:57
  45. 45 | 8.4. Mapreduce Programming Writing MapReduce Code Using Eclipse (Windows) 01:25:51
  46. 46 | 8.5. Mapreduce Programming Run MapReduce Jobs Using Hadoop Streaming 00:11:42
  47. 47 | 9.1. Pig Introduction 00:02:07
  48. 48 | 9.2. Pig Execution Modes 00:01:50
  49. 49 | 9.3. Pig Data Types 00:00:43
  50. 50 | 9.4. Pig Relational Operators - Load, Store And Dump 00:01:15
  51. 51 | 9.5. Pig Lazy Evaluation 00:00:44
  52. 52 | 10.1. Hive Introduction 00:03:08
  53. 53 | 10.2. Hive Data Types 00:02:41
  54. 54 | 10.3. Hive Getting Started - Hands-On 00:05:15
  55. 55 | 10.4. Hive Tables 00:01:02
  56. 56 | 10.5. Hive Managed Tables - Hands-On 00:08:05
  57. 57 | 10.6. Hive External Tables - Hands On 00:02:02
  58. 58 | 10.7. Hive Select And Aggregation Queries 00:01:31
  59. 59 | 10.8. Hive Saving Data 00:02:35
  60. 60 | 10.9. Hive DDL - Alter Table 00:01:14
  61. 61 | 11.1. Sqoop Introduction 00:00:43
  62. 62 | 11.2. Sqoop Sqoop Import - MySQL To HDFS 00:03:42
  63. 63 | 11.3. Sqoop Sqoop Import - MySQL To Hive 00:02:00
  64. 64 | 12.1. Flume Introduction 00:01:00
  65. 65 | 12.2. Flume Agents 00:01:57
  66. 66 | 12.3. Flume Sources & Delivery Reliability 00:01:03
  67. 67 | 12.4. Flume Hands-On Demo On CloudxLab 00:04:44
  68. 68 | 12.5. Flume Summary 00:00:17
  69. 69 | 13.1. Oozie Introduction 00:03:18
  70. 70 | 13.2. Oozie Running Sqoop Action Using Oozie From Hue 00:03:04
  71. 71 | 14.1. NoSQL Scaling Out / Up 00:01:19
  72. 72 | 14.2. NoSQL ACID Properties And RDBMS Story 00:04:19
  73. 73 | 14.3. NoSQL Types Of NoSQL Stores 00:03:06
  74. 74 | 14.4. NoSQL CAP Theorem 00:04:37
  75. 75 | 15.1. HBase Introduction 00:00:37
  76. 76 | 15.2. HBase Architecture 00:01:05
  77. 77 | 15.4. HBase Data Model 00:04:10
  78. 78 | 15.5. HBase Design Guidelines 00:01:26
  79. 79 | 15.6. HBase Data Model Example 00:04:08
  80. 80 | 15.7. HBase Hands On With Hue 00:02:44
  81. 81 | 15.8. HBase Hands-On With Console 00:03:04
  82. 82 | 15.9. HBase Data Location 00:01:06
  83. 83 | 15.11. HBase Bloom Filter 00:05:52
  84. 84 | 15.12. HBase REST 00:02:27
  85. 85 | 15.3. HBase Architecture - Regions 00:01:10
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