ElasticSearch ElasticSearch Indexing & Data Management 3

Question 1

What is an 'ingest pipeline' in Elasticsearch?

Accepted Answer

A set of processors that transform documents before they are indexed

Answer

A Logstash configuration file

Answer

A scheduled job for bulk indexing

Answer

A Kibana dashboard for monitoring ingest rates

Question 2

What does the 'geo_point' field type enable in Elasticsearch?

Accepted Answer

Storing latitude/longitude coordinates and performing geo-spatial queries

Answer

Storing IP address ranges

Answer

Mapping document URLs to geographic regions

Answer

Tagging documents with country codes

Question 3

What is a 'nested' field type used for in Elasticsearch?

Accepted Answer

Storing deeply nested JSON arrays of objects while maintaining their inner relationships

Answer

Nesting one index inside another

Answer

Defining parent-child relationships between different indices

Answer

Storing hierarchical category trees

Question 4

What is the 'join' field type used for in Elasticsearch?

Accepted Answer

Defining parent-child relationships between documents within the same index

Answer

Performing SQL-like joins between two indices

Answer

Merging duplicate documents during indexing

Answer

Linking an index alias to multiple indices

Question 5

What is the purpose of 'index templates' in Elasticsearch?

Accepted Answer

Automatically applying settings, mappings, and aliases to new indices matching a name pattern

Answer

Pre-built Kibana dashboards for new indices

Answer

Templates for generating bulk index requests

Answer

A GUI for designing index mappings

Question 6

What does 'force merge' do in Elasticsearch?

Accepted Answer

Manually triggers segment merging to reduce the number of segments in an index

Answer

Forces a primary shard to merge with its replica

Answer

Merges two indices into one

Answer

Forces a re-election of the master node