Inverted index data structure in Elasticsearch

Introduction

An inverted index helps find words quickly in many documents. It works like a book's index, showing where each word appears.

You want to search text fast in many documents.

You need to find all documents containing a specific word.

You want to build a search engine for articles or books.

You want to support quick autocomplete or suggestions.

You want to analyze text data to find common words.

Syntax

Elasticsearch

An inverted index is automatically created by Elasticsearch when you add text data.

It stores:
- Each word (term) as a key.
- A list of documents where the word appears.

You do not write code to create it directly; Elasticsearch builds it behind the scenes.

Elasticsearch creates and updates the inverted index automatically when you add or change documents.

The inverted index allows very fast full-text search queries.

Examples

This adds a document to the 'library' index. Elasticsearch updates the inverted index with words like 'Elasticsearch', 'powerful', 'search', and 'engine'.

Elasticsearch

PUT /library/_doc/1
{
  "title": "Learn Elasticsearch",
  "content": "Elasticsearch is a powerful search engine"
}

This searches for documents containing the word 'search'. Elasticsearch uses the inverted index to find matching documents quickly.

Elasticsearch

GET /library/_search
{
  "query": {
    "match": {
      "content": "search"
    }
  }
}

Sample Program

This example adds two documents to the 'books' index. Then it searches for documents with the word 'inverted' in the description. Elasticsearch uses the inverted index to find document 2 quickly.

Elasticsearch

PUT /books/_doc/1
{
  "title": "Database Basics",
  "description": "Learn about databases and indexing"
}

PUT /books/_doc/2
{
  "title": "Search Engines",
  "description": "How search engines use inverted indexes"
}

GET /books/_search
{
  "query": {
    "match": {
      "description": "inverted"
    }
  }
}

Important Notes

The inverted index stores words, not whole sentences.

It helps find documents fast but uses extra space to store the index.

Elasticsearch manages the index automatically; you just add and search documents.

Summary

An inverted index maps words to documents where they appear.

It is created automatically by Elasticsearch for fast text search.

You use it when you want to search text quickly in many documents.

Practice

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

easy

A. To store documents in the order they were added

B. To map words to the documents where they appear

C. To compress data for storage efficiency

D. To encrypt documents for security

Solution

1. Step 1: Understand the role of inverted index

   An inverted index links each word to the documents containing it, enabling fast search.

2. Step 2: Compare options with definition

   Only To map words to the documents where they appear describes this mapping; others describe unrelated functions.

3. Final Answer:

   To map words to the documents where they appear -> Option B

4. Quick Check:

   Inverted index = word-to-document map [OK]

Hint: Remember: inverted index links words to documents [OK]

Common Mistakes:

• Thinking it stores documents in order
• Confusing with data compression
• Assuming it encrypts data

2. Which of the following is the correct way Elasticsearch uses an inverted index?

easy

A. It stores documents in a tree structure

B. It stores a list of words for each document

C. It stores documents as plain text files

D. It stores a list of documents for each unique word

Solution

1. Step 1: Recall inverted index structure

   Inverted index keeps a list of documents for each unique word found in the data.

2. Step 2: Match options to structure

   It stores a list of documents for each unique word matches this exactly; others describe different or incorrect storage methods.

3. Final Answer:

   It stores a list of documents for each unique word -> Option D

4. Quick Check:

   Inverted index = word to document list [OK]

Hint: Think: word first, then documents list [OK]

Common Mistakes:

• Confusing inverted index with forward index
• Assuming documents are stored as trees
• Thinking documents are stored as plain text only

3. Given these documents indexed in Elasticsearch:
Doc1: "apple banana apple"
Doc2: "banana orange"
What will the inverted index entry for the word banana contain?

medium

A. [Doc1, Doc2]

B. [Doc1]

C. [Doc2]

D. [] (empty list)

Solution

1. Step 1: Identify documents containing 'banana'

   Doc1 contains "banana" once, Doc2 contains "banana" once.

2. Step 2: List documents in inverted index for 'banana'

   Both Doc1 and Doc2 should be listed for the word "banana".

3. Final Answer:

   [Doc1, Doc2] -> Option A

4. Quick Check:

   banana appears in Doc1 and Doc2 [OK]

Hint: Check all docs containing the word, not just one [OK]

Common Mistakes:

• Listing only one document
• Confusing word frequency with document list
• Leaving the list empty

4. You have an inverted index that incorrectly shows the word orange linked only to Doc1, but Doc2 also contains "orange". What is the likely cause?

medium

A. The indexing process missed updating the inverted index for Doc2

B. The word "orange" does not exist in Doc2

C. Elasticsearch does not support multiple documents per word

D. The inverted index only stores the first document per word

Solution

1. Step 1: Verify word presence in documents

   Since "orange" is in Doc2, it should appear in the inverted index for that word.

2. Step 2: Identify indexing error

   If Doc2 is missing, likely the indexing process did not update the inverted index correctly for Doc2.

3. Final Answer:

   The indexing process missed updating the inverted index for Doc2 -> Option A

4. Quick Check:

   Missing doc means indexing error [OK]

Hint: Missing docs usually mean indexing skipped them [OK]

Common Mistakes:

• Assuming word is not in Doc2
• Thinking Elasticsearch limits docs per word
• Believing inverted index stores only one doc

5. You want to optimize search speed for a large text dataset in Elasticsearch. Which approach using the inverted index is best?

hard

A. Disable the inverted index to save storage space

B. Store all documents as plain text and scan each on search

C. Use the inverted index to quickly find documents containing search words

D. Index only the first word of each document

Solution

1. Step 1: Understand inverted index purpose

   It allows fast lookup of documents by words, speeding up search.

2. Step 2: Evaluate options for search speed

   Use the inverted index to quickly find documents containing search words uses the inverted index as intended; others slow search or lose data.

3. Final Answer:

   Use the inverted index to quickly find documents containing search words -> Option C

4. Quick Check:

   Inverted index speeds search by word lookup [OK]

Hint: Use inverted index for fast word-based search [OK]

Common Mistakes:

• Thinking scanning all text is faster
• Disabling inverted index to save space
• Indexing only part of documents