Fuzzy matching in Elasticsearch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to perform a fuzzy match on the field "name" with the value "Jon".

Elasticsearch

{
  "query": {
    "fuzzy": {
      "name": {
        "value": "[1]"
      }
    }
  }
}

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

AJane

BJohn

CJon

DJoan

Attempts:

3 left

💡 Hint

Common Mistakes

Using a different name than the intended search term.

Leaving the value empty or misspelled.

The fuzzy query requires the exact value to search fuzzily. Here, "Jon" is the intended search term.

2fill in blank

medium

Complete the code to set the fuzziness level to 2 in the fuzzy query.

Elasticsearch

{
  "query": {
    "fuzzy": {
      "name": {
        "value": "Jon",
        "fuzziness": [1]
      }
    }
  }
}

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

A"AUTO"

B3

C"1"

D2

Attempts:

3 left

💡 Hint

Common Mistakes

Using quotes around numbers which makes them strings.

Using an unsupported fuzziness value.

The fuzziness level controls how many edits are allowed. Setting it to 2 means up to two edits are accepted.

3fill in blank

hard

Fix the error in the fuzzy query by completing the missing key for the search term.

Elasticsearch

{
  "query": {
    "fuzzy": {
      "name": {
        [1]: "Jon",
        "fuzziness": 1
      }
    }
  }
}

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

A"value"

B"term"

C"query"

D"match"

Attempts:

3 left

💡 Hint

Common Mistakes

Using incorrect keys like "term" or "match" inside the fuzzy query.

Omitting the key and only providing the value.

The fuzzy query requires the key "value" to specify the search term.

4fill in blank

hard

Fill both blanks to create a fuzzy query that searches the "title" field for "elastic" with fuzziness 1.

Elasticsearch

{
  "query": {
    "fuzzy": {
      [1]: {
        "value": [2],
        "fuzziness": 1
      }
    }
  }
}

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

A"title"

B"elastic"

C"name"

D"elasticsearch"

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up field names and values.

Not quoting the strings properly.

The field to search is "title" and the fuzzy value is "elastic".

5fill in blank

hard

Fill all three blanks to create a fuzzy query on the "description" field with value "search", fuzziness "AUTO", and prefix length 2.

Elasticsearch

{
  "query": {
    "fuzzy": {
      [1]: {
        "value": [2],
        "fuzziness": [3],
        "prefix_length": 2
      }
    }
  }
}

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

A"description"

B"search"

C"AUTO"

D"searching"

Attempts:

3 left

💡 Hint

Common Mistakes

Using numeric fuzziness instead of "AUTO" when asked.

Forgetting to quote string values.

Confusing prefix_length with fuzziness.

The field is "description", the value is "search", and fuzziness is set to "AUTO" for automatic adjustment.

Practice

1. What does the fuzziness parameter control in an Elasticsearch fuzzy query?

easy

A. The maximum length of the search term

B. The number of allowed letter changes to match similar words

C. The minimum number of exact matches required

D. The number of search results returned

Solution

1. Step 1: Understand the role of fuzziness

   The fuzziness parameter sets how many letters can be changed, added, or removed to still count as a match.

2. Step 2: Compare options with definition

   Only The number of allowed letter changes to match similar words correctly describes this as controlling allowed letter changes for similar words.

3. Final Answer:

   The number of allowed letter changes to match similar words -> Option B

4. Quick Check:

   Fuzziness = allowed letter changes [OK]

Hint: Fuzziness = allowed letter changes in matching [OK]

Common Mistakes:

• Confusing fuzziness with result count
• Thinking fuzziness limits search term length
• Mixing fuzziness with prefix_length

2. Which of the following is the correct syntax to add fuzziness in an Elasticsearch query DSL?

easy

A. "match": { "field": { "query": "text", "fuzzify": 2 } }

B. "match": { "field": { "query": "text", "fuzzy": true } }

C. "match": { "field": { "query": "text", "fuzziness": "AUTO" } }

D. "match": { "field": { "query": "text", "fuzzy_level": "high" } }

Solution

1. Step 1: Recall correct fuzziness syntax

   Elasticsearch uses the fuzziness parameter inside the match query with values like "AUTO" or a number.

2. Step 2: Check each option

   Only "match": { "field": { "query": "text", "fuzziness": "AUTO" } } uses the correct key "fuzziness" and proper structure.

3. Final Answer:

   "match": { "field": { "query": "text", "fuzziness": "AUTO" } } -> Option C

4. Quick Check:

   Correct fuzziness syntax = "match": { "field": { "query": "text", "fuzziness": "AUTO" } } [OK]

Hint: Use "fuzziness" key with "AUTO" or number [OK]

Common Mistakes:

• Using incorrect keys like fuzzy or fuzzify
• Setting fuzziness outside the match query
• Using boolean true instead of fuzziness value

3. Given this Elasticsearch fuzzy query snippet:

{ "match": { "name": { "query": "roam", "fuzziness": 0, "prefix_length": 1 } } }

Which of these terms will match the query?

medium

A. "roam"

B. "foam"

C. "roams"

D. "roan"

Solution

1. Step 1: Understand fuzziness and prefix_length

   Fuzziness 0 allows no letter differences (exact match). Prefix_length 1 means first letter must match exactly.

2. Step 2: Check each option against rules

   "roam" matches exactly. "foam" differs in first letter (prefix_length=1), so no. "roams" has extra letter, no exact match. "roan" differs by one letter after prefix ('m' vs 'n'), but fuzziness=0 allows no changes, so no.

3. Final Answer:

   "roam" -> Option A

4. Quick Check:

   Exact match with prefix_length = "roam" [OK]

Hint: Prefix_length fixes first letters; fuzziness=0 requires exact match [OK]

Common Mistakes:

• Ignoring prefix_length effect on first letter
• Assuming all similar words match regardless of prefix
• Confusing fuzziness with allowed extra letters

4. You wrote this fuzzy query:

{ "match": { "title": { "query": "elastic", "fuzziness": "2", "prefix_length": 3 } } }

But it returns no results even though documents with "plastics" and "elustics" exist. What is the likely problem?

medium

A. prefix_length is too high, blocking matches with differences in first 3 letters

B. fuzziness value must be a boolean, not a number

C. query string "elastic" is misspelled

D. match query does not support fuzziness parameter

Solution

1. Step 1: Analyze prefix_length effect

   Prefix_length 3 means first 3 letters must match exactly. If documents differ in those letters, they won't match.

2. Step 2: Check fuzziness and query validity

   Fuzziness accepts numbers; "2" is valid. Query "elastic" is correct. Match query supports fuzziness.

3. Final Answer:

   prefix_length is too high, blocking matches with differences in first 3 letters -> Option A

4. Quick Check:

   High prefix_length blocks fuzzy matches = prefix_length is too high, blocking matches with differences in first 3 letters [OK]

Hint: High prefix_length blocks fuzzy matches early [OK]

Common Mistakes:

• Thinking fuzziness must be boolean
• Ignoring prefix_length effect
• Assuming match query disallows fuzziness

5. You want to find documents with names similar to "johnson" allowing up to 2 letter changes but want to speed up search by requiring the first 2 letters to match exactly. Which query is best?

hard

A. { "match": { "name": { "query": "johnson", "fuzziness": "AUTO", "prefix_length": 3 } } }

B. { "match": { "name": { "query": "johnson", "fuzziness": 1, "prefix_length": 0 } } }

C. { "match": { "name": { "query": "johnson", "fuzziness": 3, "prefix_length": 1 } } }

D. { "match": { "name": { "query": "johnson", "fuzziness": 2, "prefix_length": 2 } } }

Solution

1. Step 1: Match requirements to parameters

   Allow up to 2 letter changes means fuzziness = 2. Speed up by requiring first 2 letters exact means prefix_length = 2.

2. Step 2: Evaluate each option

   { "match": { "name": { "query": "johnson", "fuzziness": 2, "prefix_length": 2 } } } matches both requirements exactly. { "match": { "name": { "query": "johnson", "fuzziness": 1, "prefix_length": 0 } } } allows only 1 change and no prefix. { "match": { "name": { "query": "johnson", "fuzziness": "AUTO", "prefix_length": 3 } } } uses AUTO fuzziness and prefix_length 3, which is more restrictive. { "match": { "name": { "query": "johnson", "fuzziness": 3, "prefix_length": 1 } } } allows 3 changes but only 1 prefix letter.

3. Final Answer:

   { "match": { "name": { "query": "johnson", "fuzziness": 2, "prefix_length": 2 } } } -> Option D

4. Quick Check:

   Fuzziness 2 + prefix_length 2 = { "match": { "name": { "query": "johnson", "fuzziness": 2, "prefix_length": 2 } } } [OK]

Hint: Match fuzziness and prefix_length to requirements exactly [OK]

Common Mistakes:

• Using wrong fuzziness number
• Setting prefix_length too high or too low
• Confusing AUTO with exact fuzziness number