10.5. Hive Managed Tables - Hands-On

Course Lessons

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