model.xml

    <project name='project_01' pubsub='auto' threads='1' use-tagged-token='true'> 
    <description> 
	This project is a basic demonstration of using a Model Reader window to facilitate the scoring
	of an input data set using a pre-trained ASTORE model. A Model Reader window receives request 
	events that include the location and type of an offline analytics store (ASTORE) model, and 
	publishes a model event that contains the ASTORE model to a Score window. It should be noted 
	that the request the Model Reader window will receive can either come from a preceding Source
	window, or can be specified in the schema of the Model Reader window itself. For this example,
	the request is specified within the schema of the Model Reader window. 

	In this example, the ASTORE model RPCA.sasast is a Robust Principal Components Analysis (RPCA) 
	ASTORE that was created using CAS. 

	This project contains a single continuous query consisting of the following: 
	1.	A Source window, called w_data, that receives the input data set to be analyzed 
	2.	A Model Reader window, called w_reader, which receives request events that include the
		location and type of an offline analytics store (ASTORE) model, and publishes a model 
		event that contains the ASTORE to a score window 
	3.	A Score window, called w_score, which uses the model it receives from the Model Reader
		window to perform scoring on the input data set 
    </description>
      <contqueries>
        <contquery name='cq_01' trace='w_score1'>
          <windows>
            <window-source name='w_data' insert-only='true' autogen-key='false' index='pi_EMPTY'> 
            <description> 
		This source window receives the included example input data file via a file socket connector.
		The input data stream is placed into nine fields for each observation, as specified in the 
		schema-string for this window. 
	    </description>
              <schema-string>State:string,M:double,RA:double,RO:double,A:double,B:double,L:double,AT:double,index1*:int32</schema-string>
               <connectors>
                <connector class='fs' name='pub'>
                  <properties>
                    <property name='type'>pub</property>
                    <property name='fstype'>csv</property>
                    <property name='fsname'>input.csv</property>
                    <property name='transactional'>true</property>
                    <property name='blocksize'>1</property>
                    <property name='header'>1</property>
                    <property name="addcsvopcode">true</property>
                    <property name="addcsvflags">normal</property>
                  </properties>
                </connector>
              </connectors>
            </window-source>

            <window-model-reader name='w_reader' model-type='astore'> 
            <description> 
		This Model Reader window receives request events that include the location and type of an
		offline analytic store (ASTORE) model. If publishes a model event that contains the ASTORE
		model to a Score window. 
            </description>
              <parameters>
                <properties> 
                  <property name='action'>load</property> 
                  <property name='type'>astore</property> 
                  <property name='reference'>RPCA.sasast</property>
                  <property name='RPCA_PROJECTION_TYPE'>0</property>
                </properties>
              </parameters>
            </window-model-reader>

            <window-score name='w_score1'> 
            <description> 
		This scoring window applies the Robust Principal Components Analysis (RPCA) model contained 
		in the ASTORE model RPCA.sasast to perform scoring on the input data set. The resulting output
		is then written to the file result.out via a file socket connector. 
            </description>
              <schema>  
                <fields>
                  <field name='State' type='string' key='true'/>
                  <field name='L' type='double' />
                  <field name='Prin1' type='double' />
                  <field name='Prin2' type='double' />
                </fields> 
	      </schema>
              <models>
                <offline model-type='astore'>
                  <input-map>
                    <properties>
                      <property name='M'>M</property>
                      <property name='RA'>RA</property>
                      <property name='RO'>RO</property>
                      <property name='L'>L</property>
                      <property name='State'>State</property>
                    </properties>
                  </input-map>
                  <output-map>
                    <properties>
                      <property name='L'>L</property>
                      <property name='State'>State</property>
                      <property name='Prin1'>Prin1</property>
                      <property name='Prin2'>Prin2</property>
                    </properties>
                  </output-map>
                </offline>
             </models>
              <connectors>
                <connector class='fs' name='sub'>
                  <properties>
                    <property name='type'>sub</property>
                    <property name='fstype'>csv</property>
                    <property name='fsname'>result.out</property>
                    <property name='snapshot'>true</property>
                    <property name='header'>true</property> 
                  </properties>
                </connector>
              </connectors>
            </window-score>
          </windows>
          <edges>
            <edge source='w_data'    target='w_score1'  role='data'/>
            <edge source='w_reader'  target='w_score1'  role='model'/>
          </edges>
        </contquery>
      </contqueries>
    </project>