The fields as default defined in the solr schema are vastly different String stores a word/sentence as an exact string without performing tokenization etc. Commonly useful for storing exact matches, e. G, for facetting Text typically performs tokenization, and secondary processing (such as lower-casing etc.). Useful for all scenarios when we want to match part of a sentence If the following sample This is a sample sentence is indexed to both fields we must search for exactly the text This is a sample sentence to get a hit from the string field, while it may suffice to search for sample (or even samples with stemmning enabled) to get a hit to get a hit from the text field.
The fields as default defined in the solr schema are vastly different. String stores a word/sentence as an exact string without performing tokenization etc. Commonly useful for storing exact matches, e. G, for facetting.
Text typically performs tokenization, and secondary processing (such as lower-casing etc. ). Useful for all scenarios when we want to match part of a sentence. If the following sample, "This is a sample sentence", is indexed to both fields we must search for exactly the text This is a sample sentence to get a hit from the string field, while it may suffice to search for sample (or even samples with stemmning enabled) to get a hit to get a hit from the text field.
– Rahul Aug 25 at 9:31 You will get a larger index size when tokenizing, how large depends on your processing chain. Index creation will also be marginally slower since there's more work. Index read/creation will be great either way, so don't worry about it unless approaching millions of documents.
– Johan Sjöberg Aug 25 at 9:37 I am reading through millions of documents..hope that is not a problem..so I am going for string field since it seems efficient in all cases AND I do not need tokenizers/full text search – Rahul Aug 25 at 10:47.
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