Distributed Databases with Apache Ignite

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Janani Ravi

1:55:57

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01 - Introduction

01 - Overview of Apache Ignite.mp4

04:20

02 - 1. Getting Started with Apache Ignite

01 - Memory-centric architecture.mp4

03:49

02 - The Ignite data model.mp4

02:52

03 - Running a single node Ignite cluster.mp4

05:27

04 - Exploring the Ignite node running in Docker.mp4

03:29

05 - Running an in-memory Ignite cluster.mp4

01:39

06 - Connect to Apache Ignite using DBeaver.mp4

02:50

03 - 2. Storing and Monitoring Data

01 - Working with in-memory data.mp4

04:38

02 - Running a cluster with native persistence enabled.mp4

05:21

03 - Persistent storage in an Ignite cluster.mp4

02:24

04 - Running a multi-node Ignite cluster.mp4

04:57

05 - Configuring monitoring using GridGain.mp4

04:26

06 - Monitoring clusters with GridGain.mp4

03:10

04 - 3. Data Partitioning and Replication

01 - Data partitioning and replication.mp4

05:20

02 - Creating partitioned tables with affinity keys.mp4

04:56

03 - Handling partition losses.mp4

04:03

04 - Creating tables with backups.mp4

03:24

05 - Handling partition losses with backups.mp4

01:43

06 - Creating tables with replication.mp4

02:53

07 - Handling partition losses with replication.mp4

01:11

05 - 4. Running SQL Queries and Bulk Loading Data

01 - Resetting back to Ignite version 2.14.0.mp4

02:19

02 - Setting up for bulk loading of data.mp4

03:31

03 - Bulk loading data using a SQL script.mp4

01:33

04 - Bulk loading data using COPYINTO.mp4

01:42

05 - Bulk loading data using streaming mode.mp4

02:16

06 - Indexing.mp4

04:17

06 - 5. Programmatically Accessing Ignite with Python

01 - Using the cache API with pyignite.mp4

04:13

02 - Populating complex data types in the cache.mp4

04:40

03 - Retrieving complex data from the cache.mp4

03:27

04 - Configuring cache expiry.mp4

03:20

05 - Configuring cache consistency modes.mp4

04:55

06 - Client failover.mp4

05:25

07 - Conclusion

01 - Summary and next steps.mp4

01:27

Description

Apache Ignite is an open source, distributed database and computing platform that delivers high performance, scalability, and durability for both data-intensive applications and real-time processing. In this course, certified Google cloud architect and data engineer Janani Ravi highlights advanced content on using distributed databases with Apache Ignite. Learn about memory-centric architecture and how it applies to Apache Ignite. Go over running a single node Ignite cluster, and explore the Ignite node running in Docker. Find out how to create an in-memory Ignite cluster and connect to Ignite using DBeaver. Cover ways to store and monitor data, as well as data partitioning and replication. Learn how to run SQL queries and bulk load data using an SQL script, COPYINTO, and streaming mode. Plus, step through how to programmatically access Ignite with Python.

This course was created by Janani Ravi. We are pleased to host this training in our library.

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Database Programming

Janani Ravi

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