"The Apache Ignite Book" distribution channels

From this year we have added a few more channels for distributing our book "The Apache Ignite book", which is considered as one of...


An impatient start with Apache Ignite machine learning grid

Recently Apache Ignite 2.0 introduce a beta version of the in-memory machine learning grid, which is a distributed machine learning library built on top of the Apache IMDG. This beta release of ML library can perform local and distributed vector, decompositions and matrix algebra operations. The data structure can be stored in Java heap, off-heap or distributed Ignite caches. At this moment, the Apache Ignite ML grid doesn't support any prediction or recommendation analysis. In this short post, we are going to download the new Apache Ignite 2.0 release, build the example and run them.

1. Download and unpack the Apache Ignite 2.0 distribution.

Download the Apache Ignite 2.0 binary release version from the following link. Unpack the distribution somewhere in your workstation (e.g /home/ignite/2.0) and set the IGNITE_HOME path to the directory.

2. Start the Apache Ignite remote node

Run the following command in the terminal window. examples/config/example-ignite.xml 

Note that, Remote nodes for examples should always be started with the special configuration file which enables P2P class loading: `examples/config/example-ignite.xml`.

Also, note that Apache Ignite version 2.0 needs Java version 1.8 or higher.

3. Build the machine learning examples

Go to the /examples folder of the Apache Ignite distribution. If you already installed and configure maven, run the following command from the examples folder.

mvn clean install -Pml

The above command will active the machine learning (ml) profile and build the project.

4. Run it

Lets run the simple local onheap version of the Vector example. Execute the following command in your terminal windows:

mvn exec:java

You should get the following logs in your console.

All the examples are autonomous, does't need any special configuration. Examples name with 'Cache' such as CacheMatrixExample or CacheVectorExample needs remote Ignite node with P2P class loading. Let's run the CacheMatrixExample with the following command.
mvn exec:java

You should get the following output as shown below.

Additionally, Apache Ignite ML grid provides a simple utility class allows pretty-printing of matrices/vectors. You can run the TracerExample as follows:
mvn exec:java

This above command will launch a web browser and provide some HTML output as follows:

This enough for now. If you like this post, you should also like the book.

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