Inverted index data structure in Elasticsearch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create an inverted index mapping terms to documents.

Elasticsearch

PUT /my_index/_doc/1 {
  "content": "apple banana cherry"
}

GET /my_index/_search {
  "query": {
    "match": {
      "content": "[1]"
    }
  }
}

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

Aapple

Bfruit

Corange

Dvegetable

Attempts:

3 left

💡 Hint

Common Mistakes

Searching for a word not in the document returns no results.

Using unrelated terms like 'fruit' or 'vegetable' won't match.

The inverted index maps the term apple to documents containing it. Searching for apple returns matching documents.

2fill in blank

medium

Complete the query to find documents containing the term 'banana'.

Elasticsearch

GET /my_index/_search {
  "query": {
    "match": {
      "content": "[1]"
    }
  }
}

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

Acherry

Bbanana

Capple

Dgrape

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing terms not present in the documents.

Misspelling the term.

Searching for banana returns documents containing that term, using the inverted index.

3fill in blank

hard

Fix the error in the query to correctly search for 'cherry'.

Elasticsearch

GET /my_index/_search {
  "query": {
    "match": {
      "content": [1]
    }
  }
}

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

A'cherry'

Bcherry

C"cherry"

D{cherry}

Attempts:

3 left

💡 Hint

Common Mistakes

Not quoting the search term causes syntax errors.

Using single quotes instead of double quotes.

The term must be a string in quotes. Using "cherry" is correct syntax for Elasticsearch queries.

4fill in blank

hard

Fill both blanks to create a query that searches for documents containing 'apple' or 'cherry'.

Elasticsearch

GET /my_index/_search {
  "query": {
    "bool": {
      "should": [
        { "match": { "content": [1] } },
        { "match": { "content": [2] } }
      ]
    }
  }
}

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

A"apple"

B"banana"

C"cherry"

D"date"

Attempts:

3 left

💡 Hint

Common Mistakes

Using terms not present in the documents.

Not quoting the terms properly.

The bool query with should matches documents containing either apple or cherry.

5fill in blank

hard

Fill all three blanks to create a filtered query that searches for 'banana' and filters documents with 'status' equal to 'active'.

Elasticsearch

GET /my_index/_search {
  "query": {
    "bool": {
      "must": { "match": { "content": [1] } },
      "filter": { "term": { "status": [2] } }
    }
  },
  "_source": [3]
}

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

A"banana"

B"active"

C["content", "status"]

D["content"]

Attempts:

3 left

💡 Hint

Common Mistakes

Not quoting strings properly.

Using wrong field names or values.

Returning all fields instead of limiting with _source.

The query matches documents containing banana and filters those with status equal to active. The _source field limits returned fields to content and status.

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