Defining Custom Analyzers, Multi-Fields, and Mappings in Elasticsearch 7.13

From the Kibana console, create the strings_as_keywords component template with the following requirements:

• Dynamically maps string fields as the keyword datatype.
• Only indexes the first 256 characters.

From the Kibana console, create the social_media_analyzer component template with the following requirements:

• Creates a custom analyzer called social_media that uses the classic tokenizer.
• Uses the lowercase filter and a custom english_stop filter. The english_stop filter should remove English stop words.
• Uses a custom emoticons mapping character filter with the following mappings:
  • :) as happy
  • :D as laughing
  • :( as sad
  • :') as crying
  • :O as surprised
  • ;) as winking

From the Kibana console, create the twitter_template index template with the following requirements:

• Matches all indices that start with "twitter-".
• Composed of the strings_as_keywords and social_media_analyzer component templates.
• Maps the tweet field as an analyzed string field with the social_media analyzer.
• Maps a tweet.keyword multi-field as type keyword and only indexes the first 280 characters.
• Sets the number of shards to 1 and replicas to 0.