Creating an index in Elasticsearch - Why You Should Know This

The Big Idea

What if you could find any piece of information instantly, no matter how big your data is?

The Scenario

Imagine you have a huge pile of books scattered all over your room. You want to find a specific book quickly, but there is no order or system to locate it.

The Problem

Searching through every book one by one takes forever and is frustrating. You might lose track or pick the wrong book. It's slow and full of mistakes.

The Solution

Creating an index is like making a neat catalog or table of contents for your books. It organizes information so you can jump straight to what you want without searching everything.

Before vs After

✗ Before

Search all documents one by one to find matches

✓ After

Create an index first, then search quickly using the index

What It Enables

With an index, you can find data instantly, even in huge collections, making your searches fast and reliable.

Real Life Example

Online stores use indexes to quickly show you products matching your search, even if they have millions of items.

Key Takeaways

Manual searching is slow and error-prone.

Indexes organize data for fast access.

Creating an index makes searching efficient and scalable.

Practice

1. What is the main purpose of creating an index in Elasticsearch?

easy

A. To encrypt data for security

B. To delete data permanently

C. To backup data automatically

D. To organize data for fast searching

Solution

1. Step 1: Understand the role of an index

   An index in Elasticsearch is like a folder that organizes documents to make searching fast and efficient.

2. Step 2: Compare options with index purpose

   Deleting, backing up, or encrypting data are not the main functions of an index.

3. Final Answer:

   To organize data for fast searching -> Option D

4. Quick Check:

   Index = Organize data for search [OK]

Hint: Index means organizing data for quick search [OK]

Common Mistakes:

• Confusing index with backup or encryption
• Thinking index deletes data
• Assuming index automatically secures data

2. Which is the correct syntax to create an index named products in Elasticsearch?

easy

A. PUT /products

B. POST /products

C. GET /products

D. DELETE /products

Solution

1. Step 1: Recall HTTP methods for index creation

   Elasticsearch uses the PUT method to create an index with a specific name.

2. Step 2: Match method with index name

   PUT /products correctly creates the index named 'products'. POST is used for adding documents, GET for retrieving, DELETE for removing.

3. Final Answer:

   PUT /products -> Option A

4. Quick Check:

   PUT creates index [OK]

Hint: Use PUT to create an index by name [OK]

Common Mistakes:

• Using POST instead of PUT for index creation
• Confusing GET with creation
• Trying DELETE to create index

3. Given this request to create an index:

{
  "settings": {"number_of_shards": 1},
  "mappings": {
    "properties": {
      "name": {"type": "text"},
      "price": {"type": "float"}
    }
  }
}

What will be the type of the price field in the index?

medium

A. keyword

B. float

C. integer

D. text

Solution

1. Step 1: Read the mapping for the price field

   The mapping defines "price" with "type": "float" which means it stores decimal numbers.

2. Step 2: Understand field types

   Float is a number with decimals, integer is whole number, text is for full text search, keyword is for exact matches.

3. Final Answer:

   float -> Option B

4. Quick Check:

   price type = float [OK]

Hint: Check mapping 'type' for field data type [OK]

Common Mistakes:

• Confusing float with integer
• Assuming text type for numbers
• Mixing keyword with numeric types

4. Identify the error in this index creation request:

PUT /library
{
  "settings": {
    "number_of_shards": "two"
  },
  "mappings": {
    "properties": {
      "title": {"type": "text"}
    }
  }
}

medium

A. number_of_shards should be a number, not a string

B. title field type should be keyword, not text

C. PUT method cannot be used to create index

D. Missing index name in URL

Solution

1. Step 1: Check the settings syntax

   number_of_shards must be a numeric value, but "two" is a string, causing an error.

2. Step 2: Validate other parts

   Field type 'text' is valid for title, PUT is correct method, index name 'library' is present.

3. Final Answer:

   number_of_shards should be a number, not a string -> Option A

4. Quick Check:

   number_of_shards = number [OK]

Hint: Settings values must match expected data types [OK]

Common Mistakes:

• Using string instead of number for shards
• Confusing field types for text fields
• Using wrong HTTP method for index creation

5. You want to create an index users with a field age that should only accept whole numbers and be searchable. Which mapping is correct?

hard

A. { "mappings": { "properties": { "age": { "type": "float" } } } }

B. { "mappings": { "properties": { "age": { "type": "text" } } } }

C. { "mappings": { "properties": { "age": { "type": "integer" } } } }

D. { "mappings": { "properties": { "age": { "type": "keyword" } } } }

Solution

1. Step 1: Understand the data type needed for age

   Age is a whole number, so integer type is appropriate to store numeric whole values.

2. Step 2: Check searchability and field types

   Text is for full text search, float allows decimals, keyword is for exact matches but not numeric operations.

3. Final Answer:

   { "mappings": { "properties": { "age": { "type": "integer" } } } } -> Option C

4. Quick Check:

   Whole number field = integer type [OK]

Hint: Use integer type for whole number searchable fields [OK]

Common Mistakes:

• Using text type for numeric fields
• Choosing float when decimals not needed
• Using keyword for numeric data