Why Multi-match query in Elasticsearch? - Purpose & Use Cases

The Big Idea

What if you could search many places at once with just one simple question?

The Scenario

Imagine you have a huge library of books and you want to find all books that mention a certain word either in the title, the author name, or the summary. You try searching each field one by one manually.

The Problem

Searching each field separately means you have to write many queries and combine results yourself. This is slow, complicated, and easy to miss matches if you forget a field. It's like looking for a needle in many haystacks one by one.

The Solution

The multi-match query lets you search multiple fields at once with a single query. It automatically checks all the fields you want and finds the best matches, saving time and effort.

Before vs After

✗ Before

GET /books/_search
{
  "query": {
    "bool": {
      "should": [
        { "match": { "title": "magic" } },
        { "match": { "author": "magic" } },
        { "match": { "summary": "magic" } }
      ]
    }
  }
}

✓ After

GET /books/_search
{
  "query": {
    "multi_match": {
      "query": "magic",
      "fields": ["title", "author", "summary"]
    }
  }
}

What It Enables

It makes searching across many fields simple and powerful, helping you find relevant results faster and with less code.

Real Life Example

When shopping online, you want to find products by name, description, or brand all at once. Multi-match query helps the search engine do exactly that behind the scenes.

Key Takeaways

Manual searching across fields is slow and error-prone.

Multi-match query searches many fields in one go.

This saves time and finds better results easily.

Practice

1. What is the main purpose of a multi-match query in Elasticsearch?

easy

A. To search multiple fields with a single query

B. To update multiple documents at once

C. To delete multiple indexes simultaneously

D. To create multiple indexes in one request

Solution

1. Step 1: Understand the multi-match query concept

   A multi-match query allows searching across several fields in one query, making it easier to find matches in different parts of documents.

2. Step 2: Compare with other options

   The other options describe operations like creating indexes, updating documents, or deleting indexes, which are not the purpose of multi-match queries.

3. Final Answer:

   To search multiple fields with a single query -> Option A

4. Quick Check:

   Multi-match = search multiple fields [OK]

Hint: Multi-match searches many fields at once [OK]

Common Mistakes:

• Confusing multi-match with update or delete operations
• Thinking it creates or deletes indexes
• Assuming it searches only one field

2. Which of the following is the correct syntax to perform a multi-match query searching for the word "apple" in fields "title" and "description"?

easy

A. { "multi_match": { "query": "apple", "fields": ["title", "description"] } }

B. { "match": { "query": "apple", "fields": ["title", "description"] } }

C. { "multi_match": { "fields": ["title", "description"] } }

D. { "multi_match": { "query": "apple" } }

Solution

1. Step 1: Identify required keys in multi-match query

   A multi-match query requires a "query" key with the search term and a "fields" key listing the fields to search.

2. Step 2: Check each option for correct syntax

   { "multi_match": { "query": "apple", "fields": ["title", "description"] } } correctly includes both "query" and "fields" keys. { "match": { "query": "apple", "fields": ["title", "description"] } } uses "match" instead of "multi_match". { "multi_match": { "fields": ["title", "description"] } } misses the "query" key. { "multi_match": { "query": "apple" } } misses the "fields" key.

3. Final Answer:

   { "multi_match": { "query": "apple", "fields": ["title", "description"] } } -> Option A

4. Quick Check:

   multi_match needs query and fields [OK]

Hint: multi_match needs both query and fields keys [OK]

Common Mistakes:

• Using 'match' instead of 'multi_match'
• Omitting the 'query' key
• Omitting the 'fields' key

3. Given this multi-match query, what will be the effect?

{
  "multi_match": {
    "query": "quick fox",
    "fields": ["title", "content"],
    "type": "phrase"
  }
}

medium

A. Searches only the title field for the phrase "quick fox"

B. Searches for documents containing "quick" or "fox" anywhere in title or content

C. Searches for documents where "quick fox" appears as a phrase in either title or content

D. Searches for documents with exact match "quick fox" in all fields

Solution

1. Step 1: Understand the 'type' parameter in multi-match

   The "type": "phrase" option makes the query look for the exact phrase "quick fox" in the specified fields.

2. Step 2: Check fields and matching behavior

   The fields are "title" and "content", so the phrase must appear in either field, not necessarily both.

3. Final Answer:

   Searches for documents where "quick fox" appears as a phrase in either title or content -> Option C

4. Quick Check:

   type phrase = exact phrase match in fields [OK]

Hint: type phrase means exact phrase search [OK]

Common Mistakes:

• Thinking it searches for words separately (not phrase)
• Assuming it searches only one field
• Believing it requires phrase in all fields

4. Identify the error in this multi-match query:

{
  "multi_match": {
    "query": "data",
    "fields": "title, description"
  }
}

medium

A. "query" should be an array of words

B. "fields" should be an array, not a string

C. "multi_match" should be "match"

D. "fields" should be omitted for multi-match

Solution

1. Step 1: Check the type of "fields" value

   The "fields" key must be an array of field names, not a single string with commas.

2. Step 2: Validate other keys

   The "query" key is correctly a string. "multi_match" is the correct query type. "fields" should not be omitted.

3. Final Answer:

   "fields" should be an array, not a string -> Option B

4. Quick Check:

   fields must be array, not comma string [OK]

Hint: Fields must be an array, not a comma string [OK]

Common Mistakes:

• Passing fields as a comma-separated string
• Changing multi_match to match incorrectly
• Thinking query must be an array

5. You want to search for the term "coffee" giving higher importance to the "title" field than "description" and "tags" fields. Which multi-match query correctly applies this weighting?

hard

A. { "multi_match": { "query": "coffee", "fields": ["title", "description", "tags"], "boost": 3 } }

B. { "multi_match": { "query": "coffee", "fields": ["title", "description^3", "tags"] } }

C. { "multi_match": { "query": "coffee", "fields": ["title", "description", "tags"], "type": "boost" } }

D. { "multi_match": { "query": "coffee", "fields": ["title^3", "description", "tags"] } }

Solution

1. Step 1: Understand field boosting syntax

   To give more importance to a field, add a caret (^) and a boost number after the field name, e.g., "title^3".

2. Step 2: Check each option for correct boosting

   { "multi_match": { "query": "coffee", "fields": ["title^3", "description", "tags"] } } boosts "title" by 3, others default. { "multi_match": { "query": "coffee", "fields": ["title", "description^3", "tags"] } } boosts "description" incorrectly. { "multi_match": { "query": "coffee", "fields": ["title", "description", "tags"], "boost": 3 } } tries to boost all fields equally with "boost" key, which is invalid here. { "multi_match": { "query": "coffee", "fields": ["title", "description", "tags"], "type": "boost" } } uses an invalid "type" value.

3. Final Answer:

   { "multi_match": { "query": "coffee", "fields": ["title^3", "description", "tags"] } } -> Option D

4. Quick Check:

   Use ^number to boost fields [OK]

Hint: Boost fields with ^number after field name [OK]

Common Mistakes:

• Boosting wrong field
• Using 'boost' key incorrectly
• Setting invalid 'type' value