Proceed by selecting the 4_Graph
notebook.
Run the first three paragraphs, creating partition function, partition scheme and graph.

You can create both partitioned and unpartitioned graphs with Vora 1.4. Above you could see how to use the partition schema to create a partitioned function and below you can see how to create an unpartitioned graph.

You can drop a graph as below.

You can see what varieties of any type you have in your graph. For instance, in this example you can see what varieties of learning topics you have in the graph. As you can see below the result shows the topics as Machine Learning and Machine Teaching.

There are also wildcards available to you with graph. In below example you return the name
value on any node that includes that information. For the nodes that don’t have any property called name
the returned value is null
.

This query is using the wildcards to return the Title
value from any nodes that have that information.

You can call the graph specific functions on the graph data. In the example below you will see the Topics
that are related to the Contents
and see how far apart are they from each other by calling the DISTANCE(DIRECTED A,B)
function.

Find out what is the smallest ID
associated with the strong or weak component connecting to your Learning Contents by calling the CONNECTED_COMPONENT(STRONG A)
and CONNECTED_COMPONENT(WEAK a)
functions within your select statement.

Find out the Learning Topics that have connections to more that one incoming connected node.

You can also use aggregations in your SELECT
statement and in combination of any graph function. In the example below the statement returns the average value of the incoming degree for the Topics
.
