Inverted index data structure in Elasticsearch - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

What is the primary purpose of an inverted index in Elasticsearch?

Elasticsearch uses an inverted index to improve search speed. What does this index mainly help with?

A Storing documents in the order they were added

B Mapping terms to the documents that contain them

C Indexing documents by their creation date

D Encrypting document contents for security

💡 Hint

Think about how search engines find documents quickly by words.

An inverted index maps each term to the list of documents containing that term, enabling fast full-text search.

❓ query_result

intermediate

What documents will match this Elasticsearch query?

Given an inverted index with documents:
Doc1: "apple banana"
Doc2: "banana cherry"
Doc3: "apple cherry"

Which documents will match the query {"match": {"content": "apple"}}?

A Doc2 only

B Doc3 only

C Doc1, Doc2, and Doc3

D Doc1 and Doc3

💡 Hint

Look for documents containing the word 'apple'.

The query matches documents containing 'apple', which are Doc1 and Doc3.

📝 Syntax

advanced

Identify the syntax error in this Elasticsearch query

Which option contains a syntax error in the Elasticsearch query?

{"query": {"match": {"content": "apple"}}}

A {"query": {"match": {"content": apple}}}

B {"query": {"match": {content: "apple"}}}

C }}}"elppa" :"tnetnoc"{ :"hctam"{ :"yreuq"{

D {"query": {"match": {"content": "apple"}}}

💡 Hint

Check if all string values are properly quoted.

Option A misses quotes around the term 'apple', causing a syntax error.

❓ optimization

advanced

Which approach optimizes inverted index size in Elasticsearch?

To reduce the size of the inverted index, which method is best?

A Using stop words to exclude common terms

B Indexing all fields without filtering

C Storing full document source in the index

D Disabling compression on the index files

💡 Hint

Think about removing unnecessary words that appear very often.

Stop words are common words excluded from the index to save space and improve search speed.

🔧 Debug

expert

Why does this Elasticsearch query return no results despite matching documents existing?

Given documents indexed with terms 'apple' and 'banana', this query returns no results:

{"query": {"match": {"content": "Apple"}}}

Why?

A The inverted index is corrupted

B The field 'content' does not exist in the index

C The query is case-sensitive and 'Apple' does not match 'apple'

D The query syntax is invalid

💡 Hint

Consider how Elasticsearch handles case in text analysis.

Elasticsearch lowercases terms during indexing and querying by default, but if custom analyzers are used that preserve case, queries become case-sensitive.