Elasticsearch 7 and Elastic Stack - In Depth and Hands On! - Using Analyzers and Tokenizers

The video tutorial explains the use of analyzers in controlling text field searches. It distinguishes between keyword and text type fields, highlighting how analyzers enable partial matches and relevance ranking. Practical examples demonstrate search queries and results, showing the impact of analyzers. The tutorial also covers reindexing with new mappings to achieve exact matches and tests these mappings with search queries.

What is the primary purpose of using analyzers in text fields?

• To prevent any matches

• To make searches case-sensitive

• To allow partial matches and rank by relevance

• To ensure exact matches only

Which type of text field mapping suppresses analyzing entirely?

• Date type

• Numeric type

• Keyword type

• Text type

What happens when a text field is defined as a keyword type?

• It applies language-specific analyzers

• It allows partial matches

• It allows case-insensitive matches

• It only allows exact matches

In the example search for 'Star Trek', why did 'Star Wars' also appear in the results?

• Because the search was case-sensitive

• Because both titles contain the word 'Star'

• Because 'Star Wars' is more popular

• Because 'Wars' is a synonym for 'Trek'

How does the search engine handle multiple search terms in an analyzed field?

• All terms must match exactly

• Only the first term is considered

• At least one term must match

• None of the terms need to match

What is the effect of normalizing data in analyzed fields?

• It makes searches case-sensitive

• It treats uppercase and lowercase as equivalent

• It prevents partial matches

• It requires exact phrase matches

Why might you want to redefine mappings in a search index?

• To make the index case-insensitive

• To allow more partial matches

• To delete all data in the index

• To ensure exact matches for certain fields

What is a potential risk when deleting an entire index?

• It prevents future searches

• It may lead to data loss if not backed up

• It makes the index case-sensitive

• It cannot be recreated

How can you apply language-specific rules to a text field?

• By using a keyword type

• By using a numeric type

• By making the field case-sensitive

• By applying a language-specific analyzer

What is the main advantage of using a text type field with an analyzer?

• It makes searches case-sensitive

• It allows for more flexible and forgiving searches

• It prevents any matches

• It ensures exact matches