First search query in Elasticsearch

Introduction

You use a search query to find information stored in Elasticsearch quickly and easily.

You want to find all documents that match a specific word or phrase.

You need to search for data in a website's search box powered by Elasticsearch.

You want to filter results to show only items with certain properties.

You want to test if your Elasticsearch index contains the data you expect.

You want to explore how Elasticsearch returns matching documents.

Syntax

Elasticsearch

{
  "query": {
    "match": {
      "field_name": "search_text"
    }
  }
}

This is a simple JSON object sent to Elasticsearch to search.

Replace field_name with the name of the field you want to search in.

Examples

Searches for documents where the title field contains the word "apple".

Elasticsearch

{
  "query": {
    "match": {
      "title": "apple"
    }
  }
}

Searches for documents where the description field contains the words "fresh" and "orange".

Elasticsearch

{
  "query": {
    "match": {
      "description": "fresh orange"
    }
  }
}

Sample Program

This example sends a search request to the fruits index to find documents where the name field contains "banana".

Elasticsearch

POST /fruits/_search
{
  "query": {
    "match": {
      "name": "banana"
    }
  }
}

Important Notes

Elasticsearch queries are written in JSON format.

The match query analyzes the search text and finds matching documents.

You can use other query types for more complex searches.

Summary

A first search query helps you find documents by matching text in a field.

Use the match query inside a query object in JSON.

Replace field names and search text to fit your data.

Practice

1.

What does a match query do in an Elasticsearch search?

easy

A. It finds documents where the specified field contains the search text.

B. It deletes documents matching the search text.

C. It updates documents with the search text.

D. It creates a new index with the search text.

Solution

1. Step 1: Understand the purpose of match query

   The match query is used to find documents where a field contains the given text.

2. Step 2: Differentiate from other operations

   Deleting, updating, or creating indexes are different Elasticsearch operations, not done by match.

3. Final Answer:

   It finds documents where the specified field contains the search text. -> Option A

4. Quick Check:

   match query = find documents [OK]

Hint: Match query searches text in fields, not modify data [OK]

Common Mistakes:

• Confusing search with delete or update operations
• Thinking match creates or modifies indexes
• Assuming match returns all documents regardless of content

2.

Which of the following is the correct syntax for a basic Elasticsearch match query to search for "apple" in the field "fruit"?

{
  "query": {
    "match": {
      "fruit": "apple"
    }
  }
}

easy

A. { "query": { "match": { "fruit": "apple" } } }

B. { "match": { "query": { "fruit": "apple" } } }

C. { "query": { "fruit": { "match": "apple" } } }

D. { "query": { "match": { "apple": "fruit" } } }

Solution

1. Step 1: Identify the correct JSON structure for a match query

   The correct structure places match inside query, with the field name as key and search text as value.

2. Step 2: Compare options to this structure

   { "query": { "match": { "fruit": "apple" } } } matches the correct syntax exactly. Others misplace keys or swap field and text.

3. Final Answer:

   { "query": { "match": { "fruit": "apple" } } } -> Option A

4. Quick Check:

   Correct JSON structure = { "query": { "match": { "fruit": "apple" } } } [OK]

Hint: Match query is inside query, field name as key, text as value [OK]

Common Mistakes:

• Swapping field name and search text
• Placing match outside query
• Using wrong nesting of JSON keys

3.

Given this Elasticsearch query, what will it search for?

{
  "query": {
    "match": {
      "title": "quick brown fox"
    }
  }
}

medium

A. Documents where the title field contains the exact phrase "quick brown fox".

B. Documents where the title field contains only the word "fox".

C. Documents where the title field is empty.

D. Documents where the title field contains any of the words "quick", "brown", or "fox".

Solution

1. Step 1: Understand how match query works with multiple words

   The match query analyzes the text and searches for documents containing any of the words, not necessarily the exact phrase.

2. Step 2: Compare options with this behavior

   Documents where the title field contains any of the words "quick", "brown", or "fox". correctly states it searches for any of the words. Documents where the title field contains the exact phrase "quick brown fox". is phrase match, which requires a different query type.

3. Final Answer:

   Documents where the title field contains any of the words "quick", "brown", or "fox". -> Option D

4. Quick Check:

   match = any word match [OK]

Hint: Match finds any word in text, not exact phrase [OK]

Common Mistakes:

• Thinking match does exact phrase search
• Assuming match finds only one word
• Confusing match with match_phrase query

4.

Identify the error in this Elasticsearch query:

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

medium

A. The match query should be outside the query object.

B. The field name content should be in quotes.

C. The search text apple should be in quotes.

D. The query object is missing a closing brace.

Solution

1. Step 1: Check JSON syntax for values

   In JSON, string values must be enclosed in double quotes. Here, apple is unquoted.

2. Step 2: Verify other parts of the query

   The field name and braces are correctly quoted and closed. The match query is correctly inside query.

3. Final Answer:

   The search text apple should be in quotes. -> Option C

4. Quick Check:

   Strings need quotes in JSON [OK]

Hint: Always quote string values in JSON queries [OK]

Common Mistakes:

• Leaving string values unquoted
• Misplacing match outside query
• Forgetting closing braces

5.

You want to find documents where the field "description" contains the word "fresh" but only if the field "category" equals "fruit". Which Elasticsearch query correctly combines these conditions?

hard

A. { "query": { "match": { "description": "fresh" }, "match": { "category": "fruit" } } }

B. { "query": { "bool": { "must": [ { "match": { "description": "fresh" } }, { "match": { "category": "fruit" } } ] } } }

C. { "query": { "term": { "description": "fresh" }, "term": { "category": "fruit" } } }

D. { "query": { "match": { "description": "fresh fruit" } } }

Solution

1. Step 1: Understand combining multiple conditions in Elasticsearch

   To require both conditions, use a bool query with must array containing each match query.

2. Step 2: Evaluate each option's structure

   { "query": { "bool": { "must": [ { "match": { "description": "fresh" } }, { "match": { "category": "fruit" } } ] } } } correctly uses bool with must for both matches. { "query": { "match": { "description": "fresh fruit" } } } searches combined text in one field. Options A and C have invalid JSON or incorrect query structure.

3. Final Answer:

   { "query": { "bool": { "must": [ { "match": { "description": "fresh" } }, { "match": { "category": "fruit" } } ] } } } -> Option B

4. Quick Check:

   Use bool must to combine queries [OK]

Hint: Use bool must array to combine multiple match queries [OK]

Common Mistakes:

• Combining terms incorrectly in one match
• Using invalid JSON with repeated keys
• Not using bool query for multiple conditions