ElasticSearch Case Studies & Practical Application 2

Question 1

An e-commerce platform needs to autocomplete product names as users type. Which Elasticsearch feature is best suited for this use case?

Accepted Answer

Match phrase prefix query

Answer

Match phrase prefix query efficiently handles prefix-based autocomplete by matching documents where the last term is treated as a prefix.

Question 2

A healthcare company stores patient records and needs to ensure that a doctor's query only returns records for their assigned patients. Which Elasticsearch mechanism should be used?

Accepted Answer

Document-level security with role-based queries

Answer

Document-level security allows role-based queries that filter which documents a user can retrieve, enforcing per-user data boundaries.

Question 3

A news website indexes thousands of articles per hour. Queries are slow because the index has too many small shards. What is the recommended remedy?

Accepted Answer

Use shrink API to reduce shard count

Answer

The Shrink API consolidates many small shards into fewer larger shards, reducing overhead and improving query throughput.

Question 4

A SaaS company runs multi-tenant search where each tenant has unpredictable data volume. Which indexing strategy best balances isolation and resource efficiency?

Accepted Answer

A shared index with a tenant_id field and routing

Answer

A shared index with a tenant_id field and custom routing keeps tenant data co-located on specific shards, balancing isolation with resource efficiency.

Question 5

An application logs millions of IoT sensor events daily. Users only query the last 7 days of data. What ILM policy action should be applied to data older than 7 days?

Accepted Answer

Move to frozen tier

Answer

The frozen tier stores indices on cheaper storage and unmounts them from heap, making old data queryable on demand without wasting resources.

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ElasticSearch Practice Test

ElasticSearch Case Studies & Practical Application 2