Boolean and binary types in Elasticsearch - Time & Space Complexity

Time Complexity: Boolean and binary types

O(n)

Understanding Time Complexity

When working with Boolean and binary types in Elasticsearch, it's important to understand how the time to process queries grows as data size increases.

We want to know how the cost of searching or filtering on these types changes when we have more documents.

Scenario Under Consideration

Analyze the time complexity of the following Elasticsearch query filtering on a Boolean field.

GET /my_index/_search
{
  "query": {
    "term": {
      "is_active": true
    }
  }
}
    

This query searches for documents where the Boolean field is_active is true.

Identify Repeating Operations

In this query, Elasticsearch checks each document's is_active field to see if it matches true.

• Primary operation: Checking the Boolean field value for each document.
• How many times: Once per document in the index.

How Execution Grows With Input

As the number of documents grows, Elasticsearch must check more Boolean values.

Input Size (n)	Approx. Operations
10	10 checks
100	100 checks
1000	1000 checks

Pattern observation: The number of checks grows directly with the number of documents.

Final Time Complexity

Time Complexity: O(n)

This means the time to filter documents grows in a straight line as the number of documents increases.

Common Mistake

[X] Wrong: "Filtering on Boolean fields is instant no matter how many documents there are."

[OK] Correct: Even though Boolean fields have only two values, Elasticsearch uses inverted indexes to quickly find matching documents, so filtering is generally faster than checking each document individually.

Interview Connect

Understanding how simple filters like Boolean checks scale helps you explain how search engines handle large data efficiently and shows your grasp of query performance.

Self-Check

"What if we changed the Boolean filter to a binary field filter? How would the time complexity change?"

Practice

1. What type of data does the boolean type in Elasticsearch store?

easy

A. True or false values

B. Text strings

C. Numbers with decimals

D. Base64 encoded files

Solution

1. Step 1: Understand the boolean type purpose

   The boolean type is designed to store values that represent true or false states.

2. Step 2: Compare with other data types

   Text strings, numbers, and base64 encoded files are stored in different types like text, float, or binary, not boolean.

3. Final Answer:

   True or false values -> Option A

4. Quick Check:

   Boolean = true/false [OK]

Hint: Boolean means true or false only [OK]

Common Mistakes:

• Confusing boolean with text or number types
• Thinking boolean stores encoded files
• Assuming boolean can hold multiple values

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

easy

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

B. {
"my_field": {"type": "boolean"}
}

C. {
"my_field": {"type": "binary"}
}

D. {
"my_field": {"type": "integer"}
}

Solution

1. Step 1: Identify the binary type syntax

   In Elasticsearch, a binary field is defined with "type": "binary" inside the mapping.

2. Step 2: Check other options

   Options A, B, and D define other types (text, boolean, integer) which are not binary.

3. Final Answer:

   { "my_field": {"type": "binary"} } -> Option C

4. Quick Check:

   Binary type uses "type": "binary" [OK]

Hint: Binary type always uses "type": "binary" in mapping [OK]

Common Mistakes:

• Using boolean or text instead of binary
• Missing quotes around type name
• Incorrect JSON structure

3. Given this Elasticsearch document mapping and data:

{
  "mappings": {
    "properties": {
      "is_active": {"type": "boolean"},
      "file_data": {"type": "binary"}
    }
  }
}

Document:
{
  "is_active": true,
  "file_data": "SGVsbG8gd29ybGQ="
}

What will be the value of is_active when retrieved?

medium

A. null

B. true

C. false

D. "SGVsbG8gd29ybGQ="

Solution

1. Step 1: Understand the boolean field value

   The field "is_active" is boolean and set to true in the document.

2. Step 2: Confirm retrieval value

   When retrieved, the boolean field returns the stored true value, not the binary data or null.

3. Final Answer:

   true -> Option B

4. Quick Check:

   Boolean field returns true/false as stored [OK]

Hint: Boolean fields return true or false as stored [OK]

Common Mistakes:

• Confusing binary field value with boolean
• Expecting base64 string for boolean field
• Assuming null if not explicitly queried

4. You have this Elasticsearch mapping snippet:

{
  "properties": {
    "flag": {"type": "boolean"},
    "data": {"type": "binary"}
  }
}

Which of the following is a mistake that will cause an error when indexing a document?

medium

A. {"flag": "yes", "data": "dGVzdA=="}

B. {"flag": true, "data": "dGVzdA=="}

C. {"flag": false, "data": ""}

D. {"flag": false, "data": "dGVzdA=="}

Solution

1. Step 1: Check boolean field value types

   The boolean field "flag" must be true or false, not strings like "yes".

2. Step 2: Validate binary field values

   The binary field "data" expects base64 encoded strings, which "dGVzdA==" is valid for.

3. Final Answer:

   {"flag": "yes", "data": "dGVzdA=="} -> Option A

4. Quick Check:

   Boolean must be true/false, not string [OK]

Hint: Boolean fields accept only true or false, not strings [OK]

Common Mistakes:

• Using string 'yes' or 'no' for boolean
• Passing non-base64 strings to binary fields
• Leaving binary field empty without quotes

5. You want to store user profile pictures in Elasticsearch using the binary type and also keep a flag if the user is verified using boolean. Which of the following mapping and document pairs is correct and efficient?

hard

A. {
"mappings": {
"properties": {
"profile_pic": {"type": "text"},
"verified": {"type": "boolean"}
}
}
}

Document:
{
"profile_pic": "iVBORw0KGgoAAAANSUhEUgAAAAUA",
"verified": "yes"
}

B. {
"mappings": {
"properties": {
"profile_pic": {"type": "binary"},
"verified": {"type": "boolean"}
}
}
}

Document:
{
"profile_pic": "not_base64_data",
"verified": true
}

C. {
"mappings": {
"properties": {
"profile_pic": {"type": "binary"},
"verified": {"type": "text"}
}
}
}

Document:
{
"profile_pic": "iVBORw0KGgoAAAANSUhEUgAAAAUA",
"verified": false
}

D. {
"mappings": {
"properties": {
"profile_pic": {"type": "binary"},
"verified": {"type": "boolean"}
}
}
}

Document:
{
"profile_pic": "iVBORw0KGgoAAAANSUhEUgAAAAUA",
"verified": true
}

Solution

1. Step 1: Check mapping types for fields

   The profile picture should be stored as binary type with base64 data, and verified as boolean true/false.

2. Step 2: Validate document values

   { "mappings": { "properties": { "profile_pic": {"type": "binary"}, "verified": {"type": "boolean"} } } } Document: { "profile_pic": "iVBORw0KGgoAAAANSUhEUgAAAAUA", "verified": true } uses binary type with base64 string and boolean true, which is correct and efficient.

3. Step 3: Identify errors in other options

   { "mappings": { "properties": { "profile_pic": {"type": "text"}, "verified": {"type": "boolean"} } } } Document: { "profile_pic": "iVBORw0KGgoAAAANSUhEUgAAAAUA", "verified": "yes" } uses text for binary and string "yes" for boolean, which is incorrect.
   { "mappings": { "properties": { "profile_pic": {"type": "binary"}, "verified": {"type": "text"} } } } Document: { "profile_pic": "iVBORw0KGgoAAAANSUhEUgAAAAUA", "verified": false } uses text for boolean field.
   { "mappings": { "properties": { "profile_pic": {"type": "binary"}, "verified": {"type": "boolean"} } } } Document: { "profile_pic": "not_base64_data", "verified": true } has invalid base64 data for binary field.

4. Final Answer:

   Mapping and document with binary and boolean types correctly used -> Option D

5. Quick Check:

   Binary = base64, Boolean = true/false [OK]

Hint: Binary needs base64 data; boolean must be true or false [OK]

Common Mistakes:

• Using text type for binary data
• Passing non-base64 strings to binary fields
• Using strings like 'yes' for boolean fields