• Урок 1. 00:07:43
    Introduction
  • Урок 2. 00:05:22
    Setup Java and JDK
  • Урок 3. 00:04:16
    Setup IntelliJ with Scala Plugin
  • Урок 4. 00:06:53
    Develop Hello World Program using IntelliJ with Scala Plugin
  • Урок 5. 00:05:46
    Setup SBT to build jar files for Scala applications
  • Урок 6. 00:07:32
    Setup Ubuntu using Windows Subsystem for Linux
  • Урок 7. 00:01:21
    Setup Development Environment for Scala - Conclusion
  • Урок 8. 00:07:46
    Setup Data Sets
  • Урок 9. 00:14:39
    Setup Kafka locally on Windows or Mac or Linux
  • Урок 10. 00:10:27
    Validate Kafka setup by creating test topic
  • Урок 11. 00:09:19
    Validate Kafka setup using simulated web server logs (gen_logs)
  • Урок 12. 00:19:21
    Apache Kafka - Multinode cluster - Overview
  • Урок 13. 00:10:04
    Apache Kafka - Multinode cluster - Review Properties
  • Урок 14. 00:14:37
    Apache Kafka - Concepts
  • Урок 15. 00:10:15
    Scenarios - Single Partition Topic - One Consumer
  • Урок 16. 00:06:12
    Scenarios - Single Partition Topic - Multiple Consumers
  • Урок 17. 00:07:13
    Scenarios - Multi Partition Topic - Single Consumer
  • Урок 18. 00:08:31
    Scenarios - Multi Partition Topic - Multiple Consumers
  • Урок 19. 00:08:57
    Messages and Message Format
  • Урок 20. 00:04:41
    Introduction
  • Урок 21. 00:12:41
    Pre-requisites for multi cluster setup
  • Урок 22. 00:10:04
    Setup Kafka and Zookeeper binaries
  • Урок 23. 00:08:55
    Configure Zookeeper
  • Урок 24. 00:11:11
    Zookeeper Commands
  • Урок 25. 00:07:37
    Configure Kafka Brokers
  • Урок 26. 00:14:45
    Validate Kafka
  • Урок 27. 00:01:03
    Introduction
  • Урок 28. 00:02:37
    Revision of Kafka Topic
  • Урок 29. 00:04:35
    Create Project - KafkaWorkshop
  • Урок 30. 00:05:47
    Add Dependencies for Kafka APIs
  • Урок 31. 00:10:52
    Externalize Properties using typesafe config
  • Урок 32. 00:22:57
    Producer APIs using REPL
  • Урок 33. 00:13:46
    Producer APIs using Program
  • Урок 34. 00:13:39
    Consumer APIs using REPL
  • Урок 35. 00:10:30
    Consumer APIs using Program
  • Урок 36. 00:09:35
    Introduction
  • Урок 37. 00:10:22
    Characteristics of Kafka Topic
  • Урок 38. 00:10:05
    Producer APIs - ProducerRecord Functions
  • Урок 39. 00:13:43
    Producer APIs - Produce Log Messages into Partitioned Topic - with out key
  • Урок 40. 00:16:41
    Producer APIs - Produce Log Messages into Partitioned Topic - using Key
  • Урок 41. 00:14:26
    Setup maxmind geoip database and API dependencies
  • Урок 42. 00:13:28
    Producer APIs - Produce Log Messages into Partitioned Topic - using Partition
  • Урок 43. 00:12:44
    Producer APIs - More important properties from ProducerConfig
  • Урок 44. 00:13:24
    Producer APIs - Build as Application
  • Урок 45. 00:17:26
    Consumer APIs - Review of ConsumerConfig, KafkaConsumer and ConsumerRecord
  • Урок 46. 00:19:57
    Consumer APIs - Subscribing to a Topic
  • Урок 47. 00:03:51
    Introduction
  • Урок 48. 00:15:36
    Flume Overview
  • Урок 49. 00:09:54
    Setup gen_logs
  • Урок 50. 00:18:10
    Develop first Flume Agent
  • Урок 51. 00:20:45
    Understand Source, Sink and Channel
  • Урок 52. 00:17:39
    Simple Multi Agent Flow
  • Урок 53. 00:03:43
    Consolidation
  • Урок 54. 00:07:25
    Multiplexing and Replicating
  • Урок 55. 00:14:25
    Getting Log Data into HDFS - Define Source
  • Урок 56. 00:18:05
    Getting Log Data into HDFS - Define Sink
  • Урок 57. 00:07:02
    Getting Log Data into HDFS - Understand Escape Sequences
  • Урок 58. 00:13:16
    Getting Logs into Kafka - Define Kafka Sink
  • Урок 59. 00:13:27
    Getting Logs into Kafka - Using File Channel
  • Урок 60. 00:07:39
    Limitations and Conclusion
  • Урок 61. 00:05:41
    Overview Of Spark Streaming (Legacy)
  • Урок 62. 00:01:33
    Overview of DStreams and APIs
  • Урок 63. 00:01:26
    Typical Development Life Cycle for Spark Streaming Applications
  • Урок 64. 00:16:54
    Develop Streaming Department Count using socketTextStream
  • Урок 65. 00:12:19
    Develop Streaming Department Count using Kafka
  • Урок 66. 00:04:17
    Spark Streaming - Windowing Functions Overview
  • Урок 67. 00:01:49
    Setup HBase Locally
  • Урок 68. 00:10:25
    Basic NoSQL Concepts and HBase
  • Урок 69. 00:13:19
    CRUD Operations in HBase using HBase Shell
  • Урок 70. 00:03:58
    Setup sbt Project for Scala and HBase
  • Урок 71. 00:13:32
    CRUD Operations using Scala REPL
  • Урок 72. 00:08:25
    Develop and Run Scala Programs using HBase as Database
  • Урок 73. 00:10:55
    Overview of Data Modeling in HBase
  • Урок 74. 00:12:12
    Develop applications for thin schema
  • Урок 75. 00:04:20
    Develop applications for thick schema
  • Урок 76. 00:13:36
    Examples of HBase filters
  • Урок 77. 00:03:25
    Develop applications using HBase filters
  • Урок 78. 00:01:13
    Introduction
  • Урок 79. 00:07:04
    Overview of Ingestion Technologies
  • Урок 80. 00:05:01
    Overview of Real Time Processing
  • Урок 81. 00:04:31
    Overview of Databases and Visualization
  • Урок 82. 00:04:16
    Overview of Streaming Pipeline Frameworks
  • Урок 83. 00:09:59
    Spark Structured Streaming - Introduction
  • Урок 84. 00:05:59
    Setup Spark Locally
  • Урок 85. 00:03:28
    Development Life Cycle and Setup Project - StreamingDemo
  • Урок 86. 00:04:25
    Define Dependencies
  • Урок 87. 00:06:07
    Externalize Properties
  • Урок 88. 00:02:33
    Define Problem Statement and Understand Data
  • Урок 89. 00:08:20
    Data Processing using Data Frame Operations - Quick Review
  • Урок 90. 00:15:29
    Spark Structured Streaming - Getting Streaming Department Traffic using socket
  • Урок 91. 00:12:50
    Build jar and Deploy - Get Streaming Department Traffic using socket
  • Урок 92. 00:07:42
    Setup Project for Kafka and Spark Structured Streaming Integration
  • Урок 93. 00:14:44
    Kafka and Spark Structured Streaming Integration - using REPL
  • Урок 94. 00:08:57
    Kafka and Spark Structured Streaming Integration - using IDE
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