The answer is this-: Because we can't declare a field of different data types within a same index in different document types.
Say there's an index called "college".
Then there are document types called "student" "teacher" "administration" "staff".
What problem would occur if we allow this?
Books and documentations are saying that if a field called "date_of_join" is given a "text" data type in "student", then we can't give "date_of_join" as "date" data type in "staff".
It says that it's due to the way Lucene is.
This is because of the way Lucene maintains the field types in an index. As Lucene manages fields on an index level, there is no flexibility to declare two fields of different data types in the same index
But this is not clear without an example(of how lucene is storing index). Can you guys clarify this?
I know that lucene stores inverted indexes though. But still I'm not clear.
Once you define field in Lucene Elastic Search, it is considered of same datatype internally in there system, so basically if was issue in there system, that you cannot have 2 columns of different tables with different datatype but same name, so they decided to remove this limitations from ES 8
In an SQL database, tables are independent of each other. The columns in one table have no bearing on columns with the same name in another table. This is not the case for fields in a mapping type.
In an Elasticsearch index, fields that have the same name in different mapping types are backed by the same Lucene field internally. In other words, using the example above, the
user_namefield in the
usertype is stored in exactly the same field as the
user_namefield in the
tweettype, and both
user_namefields must have the same mapping (definition) in both types.
This can lead to frustration when, for example, you want
deletedto be a
datefield in one type and a
booleanfield in another type in the same index.
On top of that, storing different entities that have few or no fields in common in the same index leads to sparse data and interferes with Lucene’s ability to compress documents efficiently.
For these reasons, we have decided to remove the concept of mapping types from Elasticsearch.
Try looking at these articles
.you need to check that Elastic search have removed Index from version 8
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