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From "Joel Bernstein (JIRA)" <>
Subject [jira] [Commented] (SOLR-13047) Add facet2D Streaming Expression
Date Thu, 18 Apr 2019 13:48:00 GMT


Joel Bernstein commented on SOLR-13047:

Good questions.

It gets confusing when trying to understand the differences between sum, count, min, max and
avg, and the math expression functions like *dotProduct.*

The math expression functions all extend sub-classes of StreamEvaluator. They are designed
to work over data that has been read into memory structures like arrays, matrices and numbers.

The functions sum, count, min, max, avg all extend from the Metric class. Metrics are most
often translated to functions that are translated to JSON facet API aggregations. You'll notice
in the FacetStream they are used to build up the JSON facet API expression.

Currently there are only five Metrics available: sum, count, min, max and avg. But, the output
of Facet2D can be read into memory and the operated on by math expressions as shown in the



About the constructor...

The are two constructors in the FacetStream. The one that matters is 
public FacetStream(StreamExpression expression, StreamFactory factory) throws IOException{
You can adapt this constructor for Facet2D.

This constructor is the one that will be called by the Streaming Expression parser. The FacetStream
implementation shows how to extract the parameters using the *expression* and the *factory*. 


> Add facet2D Streaming Expression
> --------------------------------
>                 Key: SOLR-13047
>                 URL:
>             Project: Solr
>          Issue Type: New Feature
>      Security Level: Public(Default Security Level. Issues are Public) 
>            Reporter: Joel Bernstein
>            Assignee: Joel Bernstein
>            Priority: Major
> The current facet expression is a generic tool for creating multi-dimension aggregations.
The *facet2D* Streaming Expression has semantics specific for 2 dimensional facets which are
designed to be *pivoted* into a matrix and operated on by *Math Expressions*. 
> facet2D will use the json facet API under the covers. 
> Proposed syntax:
> {code:java}
> facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, 10", count(*)){code}
> The example above will return tuples containing the top 300 diseases and the top ten
symptoms for each disease. 
> Using math expression the tuples can be *pivoted* into a matrix where the rows of the
matrix are the diseases, the columns of the matrix are the symptoms and the cells in the matrix
contain the counts. This matrix can then be *clustered* to find clusters of *diseases* that
are correlated by *symptoms*. 
> {code:java}
> let(a=facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, 10", count(*)),
>     b=pivot(a, diseases, symptoms, count(*)),
>     c=kmeans(b, 10)){code}
> *Implementation Note:*
> The implementation plan for this ticket is to create a new stream called Facet2DStream.
The FacetStream code is a good starting point for the new implementation and can be adapted
for the Facet2D parameters. Similar tests to the FacetStream can be added to StreamExpressionTest

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