full text search - Elasticsearch document modelling options -
i know best practices when designing data model indices in elasticsearch. have system in need pull data cloud storage systems(eg:dropbox),social media(eg:twitter),articles web etc.
the design issue facing each type of docs have different fields/mapping.
some of options i've explored.
use different types under single index since having different doc structure(eg : elastic types facebook,twitter,drobpox,googledrive etc.).this tend add lot of types under index.
use dynamic mapping index add fields whenever necessary. , use same mapping docs. in case,most of fields null.(eg: elastic document storage social media specific fields null).
use different indices different data points. in case, there lots of indices.
i know of these options best in our use-case. consideration search , indexing performance , scalability. appreciated.
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