Term query in Elasticsearch - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a Term query in Elasticsearch?

A Term query searches for exact matches of a term in a field. It does not analyze the search term, so it looks for the exact value as stored.

beginner

How does a Term query differ from a Match query?

A Term query looks for exact values without analyzing the input, while a Match query analyzes the input text (like splitting words) before searching.

beginner

Show a simple example of a Term query searching for the value "blue" in the field "color".

{ "term": { "color": { "value": "blue" } } }

intermediate

Can a Term query be used to search text fields that are analyzed?

No, Term queries work best on keyword or non-analyzed fields because they look for exact matches. For analyzed text fields, use Match queries.

intermediate

What happens if you use a Term query on a text field with multiple words?

The Term query will look for the exact whole string including spaces. It won't split the words, so it may not find matches if the field is analyzed.

What does a Term query in Elasticsearch search for?

A Exact matches of a term

B Analyzed and tokenized words

C Partial matches

D Fuzzy matches

A Term query searches for exact matches of the term without analyzing it.

Which field type is best suited for a Term query?

A Keyword or non-analyzed fields

B Analyzed text fields

C Numeric fields only

D Date fields only

Term queries work best on keyword or non-analyzed fields because they look for exact values.

What will happen if you use a Term query on a text field with the value "New York"?

A It will find documents containing "New" or "York"

B It will analyze and split the phrase before searching

C It will find documents with the exact phrase "New York"

D It will not find any documents

On an analyzed text field, "New York" is tokenized into separate terms (e.g., "new", "york"). A term query looks for the exact unanalyzed term "New York", which doesn't exist in the index.

Which query should you use instead of Term query for full-text search?

A Range query

B Match query

C Term query

D Exists query

Match query analyzes the text and is better for full-text search.

Is the Term query case sensitive?

A No, it ignores case

B Only for numeric fields

C Yes, it matches exact case

D Depends on the analyzer

Term query matches the exact term including case.

Explain what a Term query is and when you would use it in Elasticsearch.

Think about searching for exact values like IDs or keywords.

Describe the difference between Term query and Match query in Elasticsearch.

Consider how the input text is treated before searching.

Practice

1. What does a term query in Elasticsearch do?

easy

A. Analyzes and breaks the search term into tokens

B. Finds exact matches of the given term in the data

C. Finds documents with terms similar to the search term

D. Sorts documents based on the term frequency

Solution

1. Step 1: Understand the purpose of term query

   A term query searches for exact matches without analyzing the search term.

2. Step 2: Compare options with term query behavior

   Only Finds exact matches of the given term in the data describes exact matching, which is the core of term query.

3. Final Answer:

   Finds exact matches of the given term in the data -> Option B

4. Quick Check:

   Term query = exact match [OK]

Hint: Term query matches exactly, no analysis or tokenizing [OK]

Common Mistakes:

• Confusing term query with match query that analyzes text
• Thinking term query sorts results
• Assuming term query finds similar or partial matches

2. Which of the following is the correct syntax for a term query in Elasticsearch?

easy

A. { "terms": { "user": ["kimchy"] } }

B. { "match": { "user": "kimchy" } }

C. { "term_query": { "user": "kimchy" } }

D. { "term": { "user": "kimchy" } }

Solution

1. Step 1: Identify correct term query syntax

   The term query uses the key "term" with a field and exact value.

2. Step 2: Check each option

   { "term": { "user": "kimchy" } } matches the correct syntax. { "match": { "user": "kimchy" } } is a match query, C is invalid, D is a terms query (plural) for multiple values.

3. Final Answer:

   { "term": { "user": "kimchy" } } -> Option D

4. Quick Check:

   Term query syntax = { "term": { "user": "kimchy" } } [OK]

Hint: Term query uses "term" key with field and exact value [OK]

Common Mistakes:

• Using "match" instead of "term" for exact match
• Confusing "term" with "terms" for single value
• Adding extra keys like "term_query" which is invalid

3. Given this Elasticsearch query:

{ "query": { "term": { "status": "active" } } }

What documents will this query return?

medium

A. Documents where the status field exactly equals "active"

B. Documents where the status field contains the word "active" anywhere

C. Documents where the status field starts with "active"

D. Documents where the status field is analyzed and matches "active"

Solution

1. Step 1: Understand term query behavior on field

   The term query matches documents where the field value exactly equals the given term without analysis.

2. Step 2: Analyze each option

   Only Documents where the status field exactly equals "active" correctly describes exact equality. Others describe partial or analyzed matches which term query does not do.

3. Final Answer:

   Documents where the status field exactly equals "active" -> Option A

4. Quick Check:

   Term query = exact field value match [OK]

Hint: Term query matches exact field value only [OK]

Common Mistakes:

• Thinking term query matches partial or analyzed text
• Assuming term query matches prefixes or substrings
• Confusing term query with match query behavior

4. You wrote this term query but it returns no results:

{ "query": { "term": { "user": "Kimchy" } } }

Your data has the user field stored as lowercase "kimchy". What is the problem?

medium

A. Term query is case sensitive and "Kimchy" does not match "kimchy"

B. The term query syntax is incorrect

C. The user field is missing in the documents

D. Term query analyzes the term and changes case

Solution

1. Step 1: Understand term query case sensitivity

   Term query matches exact terms and is case sensitive, so "Kimchy" does not match "kimchy".

2. Step 2: Check other options

   Syntax is correct, field exists, and term query does not analyze or change case.

3. Final Answer:

   Term query is case sensitive and "Kimchy" does not match "kimchy" -> Option A

4. Quick Check:

   Term query = exact case match [OK]

Hint: Term query matches exact case; check letter casing [OK]

Common Mistakes:

• Assuming term query ignores case
• Thinking syntax error causes no results
• Believing term query analyzes or lowercases terms

5. You want to find documents where the tags field contains exactly the term urgent. The tags field is an array of keywords. Which query is best to use?

hard

A. { "match": { "tags": "urgent" } }

B. { "terms": { "tags": "urgent" } }

C. { "term": { "tags": "urgent" } }

D. { "term": { "tags.keyword": "urgent" } }

Solution

1. Step 1: Understand term query on array fields

   Term query matches exact terms in arrays, so it works directly on the tags field.

2. Step 2: Evaluate other options

   Match query analyzes text (not exact). Terms query expects multiple values to match any. Using tags.keyword is unnecessary if tags is keyword type.

3. Final Answer:

   { "term": { "tags": "urgent" } } -> Option C

4. Quick Check:

   Term query matches exact term in array [OK]

Hint: Use term query for exact keyword in array fields [OK]

Common Mistakes:

• Using match query which analyzes and may not match exactly
• Using terms query incorrectly for single term
• Confusing field type and using .keyword unnecessarily