Enrich processor in Elasticsearch - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this enrich processor simulation?

Given the enrich processor configuration below, what will be the value of the field user_info.name after enrichment?

Elasticsearch

{
  "enrich": {
    "policy_name": "user_policy",
    "field": "user_id",
    "target_field": "user_info"
  }
}

// Assume the enrich index contains a document with user_id=42 and name="Alice"

A "Alice"

B "user_id"

C null

D "user_info"

💡 Hint

The enrich processor copies matching fields from the enrich index document to the target field.

The enrich processor looks up the document with user_id=42 in the enrich index and copies the 'name' field into 'user_info.name'. So the value is 'Alice'.

🧠 Conceptual

intermediate

Which field does the enrich processor use to match documents?

In an enrich processor configuration, which field is used to find matching documents in the enrich index?

A The <code>field</code> specified in the enrich processor

B The <code>target_field</code> specified in the enrich processor

C The <code>policy_name</code> specified in the enrich processor

D The <code>index</code> name of the enrich index

💡 Hint

Look for the field that identifies the key to match on.

The field in the enrich processor is the field in the incoming document used to find a matching document in the enrich index.

🔧 Debug

advanced

Why does this enrich processor fail with a missing field error?

This enrich processor configuration causes an error when the field to enrich on is missing in some documents. What is the cause?

Elasticsearch

{
  "enrich": {
    "policy_name": "city_policy",
    "field": "city_id",
    "target_field": "city_info"
  }
}

// Some documents do not have 'city_id' field

A The enrich processor cannot handle null values in the enrich index.

B The <code>target_field</code> is incorrectly named and causes the error.

C The enrich policy <code>city_policy</code> is not created, causing the error.

D The enrich processor requires the <code>field</code> to exist in every document; missing fields cause failure.

💡 Hint

Check what happens if the field used for matching is missing in the document.

If the field specified in field is missing in a document, the enrich processor cannot perform the lookup and throws an error.

📝 Syntax

advanced

Which enrich processor configuration is syntactically correct?

Choose the syntactically correct enrich processor configuration snippet.

A { "enrich": { "policy_name": "user_policy", "field": "user_id" "target_field": "user_info" } }

B { "enrich": { "policy_name": "user_policy", "field": "user_id", "target_field": "user_info" } }

C { "enrich": { "policy_name": "user_policy", "field": "user_id", "target_field" } }

D { "enrich": { "policy_name": "user_policy", "field": , "target_field": "user_info" } }

💡 Hint

Look for missing commas or missing values.

Option B has all required fields with correct JSON syntax. Options A, C, and D have missing commas, missing values, or incomplete fields causing syntax errors.

🚀 Application

expert

How many fields will be added to the document after enrichment?

An enrich policy indexes documents with fields city_id, name, and population. The enrich processor is configured with field": "city_id" and target_field": "city_info". After enrichment, how many new fields will be added under city_info in the original document?

A 3

B 1

C 2

D 0

💡 Hint

The enrich processor copies all fields except the matching key into the target field.

The enrich documents have three fields: city_id (the matching key), name, and population. The enrich processor copies all fields from the matched document except the match field (city_id) into the city_info object. Thus, two fields are added: city_info.name and city_info.population.