Text vs keyword field types in Elasticsearch - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define a keyword field in Elasticsearch mapping.

Elasticsearch

"status": { "type": "[1]" }

Drag options to blanks, or click blank then click option'

Akeyword

Btext

Cinteger

Ddate

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'text' type when exact matching is needed.

Confusing 'keyword' with numeric types.

The keyword type is used for structured content like tags or IDs that should be searchable as exact values.

2fill in blank

medium

Complete the code to define a text field with English analyzer.

Elasticsearch

"description": { "type": "[1]", "analyzer": "english" }

Drag options to blanks, or click blank then click option'

Along

Bkeyword

Cboolean

Dtext

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'keyword' type with an analyzer.

Choosing a numeric type for text content.

The text type is used for full-text search and supports analyzers like 'english' to process the text.

3fill in blank

hard

Fix the error in the mapping: the field should be searchable as exact value but is defined as text.

Elasticsearch

"category": { "type": "[1]" }

Drag options to blanks, or click blank then click option'

Akeyword

Binteger

Ctext

Ddate

Attempts:

3 left

💡 Hint

Common Mistakes

Leaving the field as 'text' when exact matching is required.

Using numeric types for string fields.

To search exact values, the field must be keyword type, not text.

4fill in blank

hard

Fill both blanks to create a mapping with a text field and a keyword subfield.

Elasticsearch

"title": { "type": "[1]", "fields": { "raw": { "type": "[2]" } } }

Drag options to blanks, or click blank then click option'

Atext

Bkeyword

Cinteger

Dboolean

Attempts:

3 left

💡 Hint

Common Mistakes

Using keyword type for the main field when full-text search is needed.

Not defining a keyword subfield for sorting or aggregations.

This mapping defines title as a text field for full-text search, with a keyword subfield raw for exact matching and sorting.

5fill in blank

hard

Fill all three blanks to create a mapping with a text field, a keyword subfield, and a custom analyzer.

Elasticsearch

"summary": { "type": "[1]", "analyzer": "[2]", "fields": { "keyword": { "type": "[3]" } } }

Drag options to blanks, or click blank then click option'

Akeyword

Btext

Dstandard

Attempts:

3 left

💡 Hint

Common Mistakes

Using keyword type with an analyzer (not supported).

Omitting the keyword subfield for exact matches.

The summary field is a text type using the standard analyzer for full-text search, with a keyword subfield for exact matching.

Practice

1. Which Elasticsearch field type should you use if you want to perform full-text search inside sentences?

easy

A. text

B. keyword

C. integer

D. date

Solution

1. Step 1: Understand the purpose of text fields

   Text fields are designed for full-text search, allowing analysis and tokenization of sentences.

2. Step 2: Compare with keyword fields

   Keyword fields are for exact matches and do not analyze the text, so they are not suitable for searching inside sentences.

3. Final Answer:

   text -> Option A

4. Quick Check:

   Full-text search = text [OK]

Hint: Full-text search needs analyzed text fields [OK]

Common Mistakes:

• Choosing keyword for full-text search
• Confusing integer or date types with text
• Thinking keyword fields tokenize text

2. Which of the following is the correct way to define a keyword field in an Elasticsearch mapping?

easy

A. "name": { "type": "text" }

B. "name": { "type": "keyword" }

C. "name": { "type": "string" }

D. "name": { "type": "fulltext" }

Solution

1. Step 1: Recall Elasticsearch field types

   Elasticsearch uses "keyword" as the type for exact match fields.

2. Step 2: Identify the correct syntax

   "keyword" is the correct type name; "text" is for analyzed fields, "string" and "fulltext" are invalid types.

3. Final Answer:

   "name": { "type": "keyword" } -> Option B

4. Quick Check:

   Keyword field syntax = "name": { "type": "keyword" } [OK]

Hint: Keyword type is exactly "keyword" in mapping [OK]

Common Mistakes:

• Using "string" instead of "keyword"
• Confusing "text" with "keyword"
• Using invalid type names like "fulltext"

3. Given this Elasticsearch mapping snippet:

{
  "properties": {
    "title": { "type": "text" },
    "category": { "type": "keyword" }
  }
}

Which query will correctly filter documents where category is exactly "books"?

medium

A. { "term": { "category": "books" } }

B. { "match": { "category": "books" } }

C. { "match": { "title": "books" } }

D. { "term": { "title": "books" } }

Solution

1. Step 1: Identify field types and query types

   "category" is a keyword field, so exact match queries use "term" query.

2. Step 2: Match query usage

   "match" queries are for full-text search on text fields, not exact matches on keyword fields.

3. Final Answer:

   { "term": { "category": "books" } } -> Option A

4. Quick Check:

   Exact filter on keyword = term query [OK]

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

Common Mistakes:

• Using match query on keyword fields
• Filtering text fields with term query expecting full-text search
• Confusing field names in queries

4. You have this mapping:

{
  "properties": {
    "username": { "type": "keyword" },
    "bio": { "type": "text" }
  }
}

A developer tries to filter users with username containing "john" using this query:

{ "match": { "username": "john" } }

Why does this query not work as expected?

medium

A. Because match query only works on numeric fields

B. Because username field should be of type text for exact matches

C. Because match query does not work on keyword fields for partial matches

D. Because bio field should be used instead of username

Solution

1. Step 1: Understand keyword field behavior

   Keyword fields are not analyzed and do not support partial matching with match query.

2. Step 2: Understand match query limitations

   Match query analyzes input and is meant for text fields, not keyword fields which require term or wildcard queries for partial matches.

3. Final Answer:

   Because match query does not work on keyword fields for partial matches -> Option C

4. Quick Check:

   Match query + keyword field = no partial match [OK]

Hint: Match query needs text fields, not keyword [OK]

Common Mistakes:

• Thinking keyword fields support partial match with match query
• Confusing field types for filtering
• Using match query on numeric or date fields

5. You want to store user tags in Elasticsearch so you can both filter by exact tag and search inside tag text. Which mapping setup is best?

hard

A. "tags": { "type": "text" }

B. "tags": { "type": "keyword" }

C. "tags": { "type": "keyword", "fields": { "analyzed": { "type": "text" } } }

D. "tags": { "type": "text", "fields": { "raw": { "type": "keyword" } } }

Solution

1. Step 1: Understand the need for both full-text search and exact filtering

   Full-text search requires text type; exact filtering requires keyword type.

2. Step 2: Use multi-fields to support both

   Mapping with "text" type and a subfield "raw" as "keyword" allows searching inside tags and filtering/sorting by exact tag.

3. Final Answer:

   "tags": { "type": "text", "fields": { "raw": { "type": "keyword" } } } -> Option D

4. Quick Check:

   Multi-fields = text + keyword for search and filter [OK]

Hint: Use multi-fields for both text search and exact filter [OK]

Common Mistakes:

• Using only text type and expecting exact filters
• Using only keyword type and expecting full-text search
• Not defining subfields for multi-purpose queries