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Posted to dev@lucene.apache.org by "Abhishek Kumar Singh (JIRA)" <ji...@apache.org> on 2018/01/07 19:51:00 UTC

[jira] [Updated] (SOLR-11741) Offline training mode for schema guessing

     [ https://issues.apache.org/jira/browse/SOLR-11741?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Abhishek Kumar Singh updated SOLR-11741:
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    Attachment: screenshot-1.png

> Offline training mode for schema guessing
> -----------------------------------------
>
>                 Key: SOLR-11741
>                 URL: https://issues.apache.org/jira/browse/SOLR-11741
>             Project: Solr
>          Issue Type: Improvement
>      Security Level: Public(Default Security Level. Issues are Public) 
>            Reporter: Ishan Chattopadhyaya
>         Attachments: screenshot-1.png
>
>
> Our data driven schema guessing doesn't work under many situations. For example, if the first document has a field with value "0", it is guessed as Long and subsequent fields with "0.0" are rejected. Similarly, if the same field had alphanumeric contents for a latter document, those documents are rejected. Also, single vs. multi valued field guessing is not ideal.
> Proposing an offline training mode where Solr accepts bunch of documents and returns a guessed schema (without indexing). This schema can then be used for actual indexing. I think the original idea is from Hoss.
> I think initial implementation can be based on an UpdateRequestProcessor. We can hash out the API soon, as we go along.



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