Hi Rajesh,
Processing flow is same for both indexing and querying. What is compared
at the end are resulting tokens. In general flow is: text -> char filter
-> filtered text -> tokenizer -> tokens -> filter1 -> tokens ... ->
filterN -> tokens.
You can read more about analysis chain in Solr wiki:
https://cwiki.apache.org/confluence/display/solr/Understanding+Analyzers,+Tokenizers,+and+Filters
Regards,
Emir
--
Monitoring * Alerting * Anomaly Detection * Centralized Log Management
Solr & Elasticsearch Support * http://sematext.com/
On 02.03.2016 10:00, G, Rajesh wrote:
Hi Team,
Can you please clarify the below. My understanding is tokenizer is used to say how the
content should be indexed physically in file system. Filters are used to query result. The
blow lines are from my setup. But I have seen eg that include filters inside <analyzer
type=”index”> and tokenizer in <analyzer type=”query”> that confused me.
<fieldType name="customSearch" class="solr.TextField"
positionIncrementGap="100" >
<analyzer type="index">
<tokenizer
class="solr.LowerCaseTokenizerFactory"/>
<tokenizer
class="solr.StandardTokenizerFactory"/>
<tokenizer class="solr.NGramTokenizerFactory"
minGramSize="2" maxGramSize="2"/>
</analyzer>
<analyzer type="query">
<filter class="solr.NGramFilterFactory" minGramSize="2"
maxGramSize="2"/>
</analyzer>
</fieldType>
My goal is to user solr and find the best match among the technology names e.g
Actual tech name
1. Microsoft Visual Studio
2. Microsoft Internet Explorer
3. Microsoft Visio
When user types Microsoft Visal Studio user should get Microsoft Visual Studio.
Basically misspelled and jumble words should match closest tech name
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