Vector Scoring Plugin for Solr : Dot Product and Cosine Similarity

With this plugin you can query documents with vectors and score them based on dot product or cosine similarity. This plugin is the same as Vector Scoring Plugin for Elasticsearch.

Plugin installation

The plugin was developed and tested on Solr 6.6.0.

  1. Copy VectorPlugin.jar to {solr.install.dir}/dist/plugins/
  2. Add the library to solrconfig.xml file:
    <lib dir="${solr.install.dir:../../../..}/dist/plugins/" regex=".*\.jar" />
  3. Add the plugin Query parser to solrconfig.xml:
    <queryParser name="vp" class="com.github.saaay71.solr.VectorQParserPlugin" />
  4. Add the fieldType VectorField to schema file(managed-schema):
    <fieldType name="VectorField" class="solr.TextField" indexed="true" termOffsets="true" stored="true" termPayloads="true" termPositions="true" termVectors="true" storeOffsetsWithPositions="true">
    <analyzer>
      <tokenizer class="solr.WhitespaceTokenizerFactory"/>
      <filter class="solr.DelimitedPayloadTokenFilterFactory" encoder="float"/>
    </analyzer>
    </fieldType>
  5. Add the field vector to schema file:
    <field name="vector" type="VectorField" indexed="true" termOffsets="true" stored="true" termPositions="true" termVectors="true" multiValued="true"/>
  6. Start Solr!

Example

Add example documents

curl -X POST -H "Content-Type: application/json" http://localhost:8983/solr/{your-collection-name}/update?commit=true  --data-binary '
[
    {"name":"example 0", "vector":"0|1.55 1|3.53 2|2.3 3|0.7 4|3.44 5|2.33 "},
    {"name":"example 1", "vector":"0|3.54 1|0.4 2|4.16 3|4.88 4|4.28 5|4.25 "},
    {"name":"example 2", "vector":"0|1.11 1|0.6 2|1.47 3|1.99 4|2.91 5|1.01 "},
    {"name":"example 3", "vector":"0|0.06 1|4.73 2|0.29 3|1.27 4|0.69 5|3.9 "},
    {"name":"example 4", "vector":"0|4.01 1|3.69 2|2 3|4.36 4|1.09 5|0.1 "},
    {"name":"example 5", "vector":"0|0.64 1|3.95 2|1.03 3|1.65 4|0.99 5|0.09 "}
]'

Query documents

Open your browser and copy the links

Query 1

http://localhost:8983/solr/{your-collection-name}/query?fl=name,score,vector&q={!vp f=vector vector="0.1,4.75,0.3,1.2,0.7,4.0"}

You should see the following result:

{
  "responseHeader":{
    "status":0,
    "QTime":1,
    "params":{
      "q":"{!myqp f=vector vector=\"0.1,4.75,0.3,1.2,0.7,4.0\"}",
      "fl":"name,score,vector"}},
  "response":{"numFound":6,"start":0,"maxScore":0.99984086,"docs":[
      {
        "name":["example 3"],
        "vector":["0|0.06 1|4.73 2|0.29 3|1.27 4|0.69 5|3.9 "],
        "score":0.99984086},
      {
        "name":["example 0"],
        "vector":["0|1.55 1|3.53 2|2.3 3|0.7 4|3.44 5|2.33 "],
        "score":0.7693964},
      {
        "name":["example 5"],
        "vector":["0|0.64 1|3.95 2|1.03 3|1.65 4|0.99 5|0.09 "],
        "score":0.76322395},
      {
        "name":["example 4"],
        "vector":["0|4.01 1|3.69 2|2 3|4.36 4|1.09 5|0.1 "],
        "score":0.5328145},
      {
        "name":["example 1"],
        "vector":["0|3.54 1|0.4 2|4.16 3|4.88 4|4.28 5|4.25 "],
        "score":0.48513117},
      {
        "name":["example 2"],
        "vector":["0|1.11 1|0.6 2|1.47 3|1.99 4|2.91 5|1.01 "],
        "score":0.44909418}]
  }}

Query 2

Adding the parameter cosine=false calculates the dot product

http://localhost:8983/solr/{your-collection-name}/query?fl=name,score,vector&q={!vp f=vector vector="0.1,4.75,0.3,1.2,0.7,4.0" cosine=false}

result of query 2:


{
  "responseHeader":{
    "status":0,
    "QTime":0,
    "params":{
      "q":"{!myqp f=vector vector=\"0.1,4.75,0.3,1.2,0.7,4.0\" cosine=false}",
      "fl":"name,score,vector"}},
  "response":{"numFound":6,"start":0,"maxScore":40.1675,"docs":[
      {
        "name":["example 3"],
        "vector":["0|0.06 1|4.73 2|0.29 3|1.27 4|0.69 5|3.9 "],
        "score":40.1675},
      {
        "name":["example 0"],
        "vector":["0|1.55 1|3.53 2|2.3 3|0.7 4|3.44 5|2.33 "],
        "score":30.180502},
      {
        "name":["example 1"],
        "vector":["0|3.54 1|0.4 2|4.16 3|4.88 4|4.28 5|4.25 "],
        "score":29.354},
      {
        "name":["example"],
        "vector":["0|4.01 1|3.69 2|2 3|4.36 4|1.09 5|0.1 "],
        "score":24.923502},
      {
        "name":["example"],
        "vector":["0|0.64 1|3.95 2|1.03 3|1.65 4|0.99 5|0.09 "],
        "score":22.1685},
      {
        "name":["example"],
        "vector":["0|1.11 1|0.6 2|1.47 3|1.99 4|2.91 5|1.01 "],
        "score":11.867001}]
  }}

Query 3

Quering on other fields and with vector scoring.

http://localhost:8983/solr/{your-collection-name}/query?fl=name,score,vector&q={!vp f=vector vector="0.1,4.75,0.3,1.2,0.7,4.0" cosine=false}name="example 2","example 4"

result of query 3:

{
  "responseHeader":{
    "status":0,
    "QTime":1,
    "params":{
      "q":"{!myqp f=vector vector=\"0.1,4.75,0.3,1.2,0.7,4.0\" cosine=false}name=\"example 2\",\"example 4\"",
      "fl":"name,score,vector"}},
  "response":{"numFound":2,"start":0,"maxScore":24.923502,"docs":[
      {
        "name":["example 4"],
        "vector":["0|4.01 1|3.69 2|2 3|4.36 4|1.09 5|0.1 "],
        "score":24.923502},
      {
        "name":["example 2"],
        "vector":["0|1.11 1|0.6 2|1.47 3|1.99 4|2.91 5|1.01 "],
        "score":11.867001}]
  }}