Loading data into Apache Ignite

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When you start with a new technology like Apache Ignite, you just want to quickly load in some data rather than fire up an IDE.

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Loading data into Apache Ignite
Stephen Darlington
01 May 2019
2019 © GridGain Systems

2019 © GridGain Systems GridGain Company Confidential
Apache Ignite In-Memory Computing Platform
Mainframe NoSQL HadoopIgnite Persistence
Persistent Layer
RDBMS
Machine and Deep Learning
EventsStreamingMessagingTransactionsSQLKey-Value
Service GridCompute Grid
Application Layer
Web SaaS SocialMobile IoT
In-Memory Data Store

2019 © GridGain Systems GridGain Company Confidential
How do I load data?
This Photo by
Unknown
Author is
licensed under
CC BY-SA

2019 © GridGain Systems GridGain Company Confidential
Official answer
1. Open your IDE
2. Create a project
3. Edit pom.xml to include Apache Ignite libraries
4. Create a new class
5. Code to open and parse input file
6. Boilerplate Ignite cluster code
7. IgniteDataStreamer code
8. Debug
9. Edit
10. Debug
11. Edit
12. Debug
13. Run
14. Play with resulting data

2019 © GridGain Systems GridGain Company Confidential2019 © GridGain Systems
There must be an easier way?
8
This Photo by Unknown Author is licensed under CC BY-NC-
ND

2019 © GridGain Systems GridGain Company Confidential
Using SQL

2019 © GridGain Systems GridGain Company Confidential
But it gets complicated…

2019 © GridGain Systems GridGain Company Confidential
SQL Streaming
Apache Ignite In-Memory Computing Platform
Mainframe NoSQL HadoopIgnite Persistence
Persistent Layer
RDBMS
Machine and Deep Learning
EventsMessagingTransactions
Service GridCompute Grid
Application Layer
Web SaaS SocialMobile IoT
In-Memory Data Store
Key-Value

2019 © GridGain Systems GridGain Company Confidential
Using Python

2019 © GridGain Systems GridGain Company Confidential
SQL
Apache Ignite In-Memory Computing Platform
Mainframe NoSQL HadoopIgnite Persistence
Persistent Layer
RDBMS
Machine and Deep Learning
EventsMessagingTransactionsKey-Value
Service GridCompute Grid
Application Layer
Web SaaS SocialMobile IoT
In-Memory Data Store
Streaming

2019 © GridGain Systems GridGain Company Confidential
Using Apache Spark

2019 © GridGain Systems GridGain Company Confidential2019 © GridGain Systems
What did we learn?
17
• Many options
– Python, Spark, SQL
– Scala
– Groovy
– Node.js
• No one “best” answer
• REPLs are awesome
– …and can be used for a lot more than just loading data

2019 © GridGain Systems GridGain Company Confidential
Resources
• Apache Ignite documentation
– https://apacheignite.readme.io/docs
– https://ignite.apache.org
• Blog
– Loading Data into Ignite. https://link.medium.com/66dzsrWw4V
– Python, part 1. https://link.medium.com/CUjDnzBQcW
– Python, part 2. https://link.medium.com/3dWH1oDQcW

2019 © GridGain Systems GridGain Company Confidential
And finally…
• Get a free ticket to the In-Memory Computing Summit Europe 2019 (June
3-4) by completing this survey:
– http://bit.ly/IMCSeu2019
• More information here:
– https://www.imcsummit.org/2019/eu/

2019 © GridGain Systems GridGain Company Confidential2019 © GridGain Systems
Thank you
20
Stephen Darlington
Senior Consultant
GridGain Systems
@sdarlington

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