Learning Path: Getting Started with Kudu – Getting started with Kyodo
If you’re building a relational, time series, IoT, or real-time architectures using Hadoop, you should be familiar with Apache Kudu. Kudu enables fast analytics on fast data by completing Hadoop’s storage layers, providing a new option for fast scans and fast random access from a single API. This Learning Path introduces you to Apache Kudu, exploring what it is, when to use it, and how to use it in conjunction with popular Hadoop ecosystem tools. You will apply this knowledge by building and running a real-time analytical application using Kudu, Impala, Kafka, and Spark.
Table of Contents:
– Welcome To The Course 00:00:25
– About The Author 00:01:27
– HDFS History 00:06:04
– HBase History 00:03:08
– Kudu And The Changing Hardware Landscape 00:02:04 – 02
– Why Kudu 00:07:10
– General Kudu Architecture 00:06:16
– Kudu Read And Write Operations 00:08:56
– Tables And Scenes In Kudu 00:07:07
– Kudu Partitioning 00:06:57
– How To Access Your Working Files 00:01:15
– Kudu Installation 00:03:07
– Creating a Table And Inserting a Data In Kudu 00:06:22
– Querying Data In Kudu 00:04:29
– Using The Kudu API 00:06 : 59
– How To Access Your Working Files 00:01:15
– Integrating Kudu With Apache Flume 00:11:49
– Using Kudu With Apache Spark Part 1 00:07:45
– Using Kudu With Apache Spark Part 2 00:06:07
– How To Access Your Working Files 00:01:15
– Time Series Introduction And Data Generation With Kafka 00:11 : 34
– Kudu Time Series Table Design And Creation 00:11:37
– Near Real-Time Data Ingestion In Kudu With Spark Streaming 00:15:46
– Fast Data Consumption And Analytics In Kudu With Impala 00:12:07
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Manufacturer: Orly / O’Reilly
Language of instruction: English
Teacher: Ryan Bosshart
Level of training: Preliminary
time of training: 2 hours + 30 minutes
File Size: 823 MB
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