The document outlines a backend API solution for fast prototyping using Solr, detailing steps for adding a new core, defining the schema, feeding and updating data, and performing queries. Key instructions include creating a core, editing schema.xml, and using JSON format for data updates and queries. The next steps involve understanding Solr's mechanisms and integrating with Django Rest Framework for further development.

1. Search Engine Back End API
Solution for Fast Prototyping
https://github.com/jimmylai/
search_engine_backend_template
Solr
Jimmy Lai
r97922028 [at] ntu.edu.tw
http://tw.linkedin.com/pub/jimmy-lai/27/4a/536
2013/01/28

2. Outline - Solr
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Add a new core
Define the schema
Feed data and update partial data
Query and Ranking
Spatial Query
• Prerequisite: Introduction and Tutorial
http://www.slideshare.net/jimmy_lai/search-engine-back-end-api-solution-for-fast-prototyping
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3. Add a New Core
• Core in Solr: a set of configuration of schema
and indexing.
• Cmd: fab create_core:$core_name
– What happended:
1. Copy the dir data/solr_core_template to dir
solr_conf with new name $core_name
2. Set config in core.properties with name=
$core_name
3. Put it under solr_conf and then run solr with
solr.solr.home=solr_conf, and then solr can find
the new core.
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Can be done with: fab start_solr
Ref:
h'p://wiki.apache.org/solr/CoreAdmin

4. Define the Schema
• Edit file solr_conf/$core_name/conf/
shcema.xml
• Add more fields in <fields> section:
– <field name="sourcesite" type="string" indexed="true" stored="true"
required="false" />
• Define your type in <types> section:
<fieldType name=”chinese" class="solr.TextField"
positionIncrementGap="100">
<analyzer>
<tokenizer class="solr.SmartChineseSentenceTokenizerFactory"/>
<filter class="solr.RemoveDuplicatesTokenFilterFactory”/>
</analyzer>
</fieldType>
Ref:
h'p://wiki.apache.org/solr/SchemaXml

5. Feed Data and Update Partial Data
• Run solr after schema updated:
– fab run_solr
• Prepare new feed data in JSON format:
– [{‘id’: id1, ‘field1’: value11, ‘field2’: value21}, {‘id’: id2,
‘field_1’:value21}]
• Send by Http Post to Solr:
– curl http://localhost:8983/solr/$core_name/update/json?
commit=true --data-binary @$json_file_name -i -H 'Contenttype:application/json’
• Partial Update JSON format:
– [{‘id’: id1, ‘field1’: {‘set’: new_value}]
Ref:
h'p://wiki.apache.org/solr/UpdateJSON

6. Query and Ranking
• Let’s use pysolr:
– solr = pysolr.Solr('http://localhost:8983/solr/movie’)
– results = [i for i in solr.search('*:*', **{‘row’: 100})]
• Query (1st parameter of search())
– Specify value of a field ‘field:value’
– Range query
‘field:[1 TO 100]’
– Boolean operation ‘field1:v1 AND field2:v2’
• Sort (put in 2nd parameter of search())
– {‘sort’: ‘field desc’}
Ref:
h'p://wiki.apache.org/solr/SolrQuerySyntax

7. Query and Ranking
Exploit the Solr UI

8. Spatial Query
• In shcema.xml, set the the type of field as
location:
– <field name="location" type="location" indexed="true" stored="true"
required="false" />
• Query:
– {'pt': ’23.853,120.498’, 'sfield': 'location', 'sort': 'geodist() asc'}
• Get the distance (KM) by:
– {‘fl’: ‘*,distance:geodist()’}
Ref:
h'p://wiki.apache.org/solr/SpaEalSearch

9. The next steps
• Understand the mechanism of:
– Solr:
• Update schema
• Update partial data
• Query language of Solr
– Djangorestframework:
• Add more parameters
• Input validation
• Output rendering
• Deploy to production environment
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