Ingest pipelines in Elasticsearch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define a simple ingest pipeline that adds a field.

Elasticsearch

{
  "description": "Add field pipeline",
  "processors": [
    {
      "set": {
        "field": "new_field",
        "value": [1]
      }
    }
  ]
}

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

A"added_value"

Badded_value

C"field_value"

Dfield_value

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting to put quotes around string values.

Using unquoted text which causes JSON errors.

The value must be a string, so it needs to be in quotes.

2fill in blank

medium

Complete the code to add a processor that converts a field to lowercase.

Elasticsearch

{
  "processors": [
    {
      "lowercase": {
        "field": [1]
      }
    }
  ]
}

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

Amessage

B"message"

C"field"

Dfield

Attempts:

3 left

💡 Hint

Common Mistakes

Not putting quotes around the field name.

Using a variable name without quotes.

Field names in JSON must be strings, so use quotes.

3fill in blank

hard

Fix the error in the pipeline that uses a rename processor incorrectly.

Elasticsearch

{
  "processors": [
    {
      "rename": {
        "field": [1],
        "target_field": "new_name"
      }
    }
  ]
}

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

A"old_name"

Bold_name

C"new_name"

Dnew_name

Attempts:

3 left

💡 Hint

Common Mistakes

Using unquoted field names causing JSON errors.

Confusing target_field with field.

The field to rename must be a string with quotes.

4fill in blank

hard

Fill both blanks to create a pipeline that removes a field if it exists.

Elasticsearch

{
  "processors": [
    {
      "remove": {
        "field": [1],
        "ignore_missing": [2]
      }
    }
  ]
}

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

A"obsolete_field"

Btrue

Cfalse

D"missing_field"

Attempts:

3 left

💡 Hint

Common Mistakes

Putting quotes around true or false.

Using wrong field names.

The field name must be a string, and ignore_missing is a boolean true.

5fill in blank

hard

Fill all three blanks to create a pipeline that sets a field only if it does not exist.

Elasticsearch

{
  "processors": [
    {
      "set": {
        "field": [1],
        "value": [2],
        "if": [3]
      }
    }
  ]
}

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

A"status"

B"pending"

C"ctx.status == null"

D"ctx.status != null"

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong condition expression.

Not quoting strings properly.

Set field 'status' to 'pending' only if ctx.status is null (does not exist).

Practice

1. What is the main purpose of an ingest pipeline in Elasticsearch?

easy

A. To create visualizations from data

B. To query documents faster

C. To backup Elasticsearch data

D. To modify documents before they are indexed

Solution

1. Step 1: Understand ingest pipeline role

   An ingest pipeline processes documents before they are stored in Elasticsearch.

2. Step 2: Compare options to pipeline purpose

   Only To modify documents before they are indexed matches this role; others describe unrelated tasks.

3. Final Answer:

   To modify documents before they are indexed -> Option D

4. Quick Check:

   Ingest pipeline = modify before indexing [OK]

Hint: Ingest pipelines change data before saving [OK]

Common Mistakes:

• Confusing pipelines with query optimization
• Thinking pipelines create backups
• Assuming pipelines generate reports

2. Which of the following is the correct way to define a processor that adds a field "source": "web" in an ingest pipeline?

easy

A. "processors": [{"add": {"field": "source", "value": "web"}}]

B. "processors": [{"remove": {"field": "source", "value": "web"}}]

C. "processors": [{"set": {"field": "source", "value": "web"}}]

D. "processors": [{"append": {"field": "source", "value": "web"}}]

Solution

1. Step 1: Identify processor to add or set field

   The set processor assigns or adds a field with a value.

2. Step 2: Check syntax correctness

   "processors": [{"set": {"field": "source", "value": "web"}}] uses set with correct JSON structure; add is not a valid processor name.

3. Final Answer:

   "processors": [{"set": {"field": "source", "value": "web"}}] -> Option C

4. Quick Check:

   Use set to add fields [OK]

Hint: Use 'set' processor to add or update fields [OK]

Common Mistakes:

• Using 'add' instead of 'set' processor
• Confusing 'append' with adding new fields
• Trying to remove field when adding

3. Given this ingest pipeline snippet:

{"processors": [{"rename": {"field": "old_name", "target_field": "new_name"}}]}

What happens to a document {"old_name": "value"} when processed?

medium

A. {"old_name": "value", "new_name": "value"}

B. {"new_name": "value"}

C. {"old_name": null}

D. {"old_name": "value"}

Solution

1. Step 1: Understand rename processor effect

   The rename processor moves the value from old_name to new_name, removing the original field.

2. Step 2: Apply to example document

   Input {"old_name": "value"} becomes {"new_name": "value"} after processing.

3. Final Answer:

   {"new_name": "value"} -> Option B

4. Quick Check:

   Rename moves field, removes old [OK]

Hint: Rename moves field value, deletes old field [OK]

Common Mistakes:

• Thinking rename duplicates field
• Assuming old field remains
• Confusing rename with copy

4. You wrote this pipeline processor:

{"processors": [{"convert": {"field": "age", "type": "integer"}}]}

But when simulating, you get an error. What is the likely cause?

medium

A. The field "age" does not exist in the document

B. The "convert" processor does not exist

C. The "type" value "integer" is invalid

D. The pipeline must have a "description" field

Solution

1. Step 1: Check processor and type validity

   The "convert" processor and type "integer" are valid in Elasticsearch ingest pipelines.

2. Step 2: Identify common error cause

   If the field "age" is missing in the document, conversion fails causing error during simulation.

3. Final Answer:

   The field "age" does not exist in the document -> Option A

4. Quick Check:

   Missing field causes convert error [OK]

Hint: Convert errors if field missing in document [OK]

Common Mistakes:

• Assuming convert processor is invalid
• Thinking 'integer' is wrong type
• Believing description is mandatory

5. You want to create an ingest pipeline that adds a field "status": "new" only if the field "priority" exists. Which processor setup achieves this?

hard

A. "processors": [{"set": {"field": "status", "value": "new", "if": "ctx.priority != null"}}]

B. "processors": [{"set": {"field": "status", "value": "new"}}, {"exists": {"field": "priority"}}]

C. "processors": [{"conditional": {"field": "priority", "processor": {"set": {"field": "status", "value": "new"}}}}]

D. "processors": [{"set": {"field": "status", "value": "new"}, "condition": "priority"}]

Solution

1. Step 1: Understand conditional execution in pipelines

   Processors support an "if" condition using painless scripts to run only when true.

2. Step 2: Identify correct syntax for conditional set

   "processors": [{"set": {"field": "status", "value": "new", "if": "ctx.priority != null"}}] uses "if": "ctx.priority != null" which runs set only if "priority" exists.

3. Final Answer:

   "processors": [{"set": {"field": "status", "value": "new", "if": "ctx.priority != null"}}] -> Option A

4. Quick Check:

   Use "if" with painless script for conditions [OK]

Hint: Use 'if' with painless script to conditionally run processor [OK]

Common Mistakes:

• Using non-existent 'conditional' processor
• Placing condition outside processor block
• Misusing 'exists' as processor