Distributed Databases with Apache Ignite
1h 56mIntermediate2023-09-05
Authors
Janani Ravi
Certified Google Cloud Architect and Data Engineer
Course details
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.
Skills covered
IgniteApacheFull-Stack Web DevelopmentWeb DevelopmentOne-Off
Concepts
0. Introduction
- 01 - Overview of Apache Ignite
1. Getting Started with Apache Ignite
- 02 - Memory-centric architecture
- 03 - The Ignite data model
- 04 - Running a single node Ignite cluster
- 05 - Exploring the Ignite node running in Docker
- 06 - Running an in-memory Ignite cluster
- 07 - Connect to Apache Ignite using DBeaver
2. Storing and Monitoring Data
- 08 - Working with in-memory data
- 09 - Running a cluster with native persistence enabled
- 10 - Persistent storage in an Ignite cluster
- 11 - Running a multi-node Ignite cluster
- 12 - Configuring monitoring using GridGain
- 13 - Monitoring clusters with GridGain
3. Data Partitioning and Replication
- 14 - Data partitioning and replication
- 15 - Creating partitioned tables with affinity keys
- 16 - Handling partition losses
- 17 - Creating tables with backups
- 18 - Handling partition losses with backups
- 19 - Creating tables with replication
- 20 - Handling partition losses with replication
4. Running SQL Queries and Bulk Loading Data
- 21 - Resetting back to Ignite version 2.14.0
- 22 - Setting up for bulk loading of data
- 23 - Bulk loading data using a SQL script
- 24 - Bulk loading data using COPYINTO
- 25 - Bulk loading data using streaming mode
- 26 - Indexing
5. Programmatically Accessing Ignite with Python
- 27 - Using the cache API with pyignite
- 28 - Populating complex data types in the cache
- 29 - Retrieving complex data from the cache
- 30 - Configuring cache expiry
- 31 - Configuring cache consistency modes
- 32 - Client failover
Conclusion
- 33 - Summary and next steps
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