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Apache Ignite

This presentation gives an overview of the Apache Ignite project. It explains Ignite in relation to its architecture, scaleability, caching, datagrid and machine learning abilities. <br> <br>Links for further information and connecting<br><br>http://www.amazon.com/Michael-Frampton/e/B00NIQDOOM/<br><br>https://nz.linkedin.com/pub/mike-frampton/20/630/385<br><br>https://open-source-systems.blogspot.com/

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Apache Ignite

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  1. What Is Apache Ignite ? ● An in memory distributed database ● A cluster based processing platform ● Open source / Apache 2.0 license ● A key / value store ● Written in Java, C#, C++, SQL ● Multiple API's available ● Multiple deployment options ● Developed by GridGain Systems

  2. What Is Apache Ignite ? ● Persistence is turned off – A distributed in-memory database – In memory data grid – Use SQL or key-value APIs ● Persistence is turned on – A distributed, horizontally scalable database – Guarantees full data consistency – Is resilient to full cluster failures

  3. How Does Ignite Work ? ● Persistence can be toggled ● Small data sets can be stored in memory ● Large datasets can use disk ● Memory can be used as a caching mechanism ● RDBMS or NoSQL integration ● Partitioning or replication of data across cluster ● Horizontally scaleable

  4. How Does Ignite Work ? ● Use Ignite as a distributed cache ● Implements JCache specification (JSR 107) ● Supports ACID transactions ● Supports SQL ( with limitations ) ● Supports Java, C++, and .NET ● Has a feature rich key-value API ● Offers two user interface ( UI ) options ● Supports collocated processing

  5. How Does Ignite Work ? ● Ignite has client and server nodes in it's cluster ● Server nodes are for storage and computation ● Client nodes are connection points to the database ● They may be embedded in client applications ● Application code written in Java, C# or C++ ● Ignite supports ODBC, JDBC and REST

  6. Ignite DataGrid

  7. Ignite DataGrid ● An in-memory distributed key-value store ● Horizontal scaleable ● Add nodes on demand ● Scale to hundreds of nodes ● View as a distributed partitioned hash map ● Every cluster node owns a portion of the data ● As cluster (server) nodes are added more data is cached

  8. Ignite Console

  9. GridGain Console

  10. Ignite Machine Learning

  11. Ignite Machine Learning ● Multiple development API's ● A set of simple / efficient ML functions ● Massively scaleable ● Co-location of data and processing ● Minimised the need for costly data transfers ● Minimised ETL as ML functions act on distributed data ● Algorithms support – Classification, Regression, Clustering – Recommendation, Preprocessing

  12. Ignite Deployment Options ● Multiple deployment options – Docker – Amazon AWS – Google Cloud – Mesos – YARN – VMWare – Microsoft Azure – Kubernetes

  13. Available Books ● See “Big Data Made Easy” Apress Jan 2015 – See “Mastering Apache Spark” ● Packt Oct 2015 – See “Complete Guide to Open Source Big Data Stack ● “Apress Jan 2018” – ● Find the author on Amazon www.amazon.com/Michael-Frampton/e/B00NIQDOOM/ – Connect on LinkedIn ● www.linkedin.com/in/mike-frampton-38563020 –

  14. Connect ● Feel free to connect on LinkedIn –www.linkedin.com/in/mike-frampton-38563020 ● See my open source blog at open-source-systems.blogspot.com/ – ● I am always interested in – New technology – Opportunities – Technology based issues – Big data integration

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