Avro schema definition in Kafka - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this Avro schema validation?

Given this Avro schema and a JSON record, what will be the result of validating the record against the schema?

Kafka

{
  "type": "record",
  "name": "User",
  "fields": [
    {"name": "name", "type": "string"},
    {"name": "age", "type": "int"}
  ]
}

Record:
{"name": "Alice", "age": "25"}

A Validation fails due to age being a string instead of int

B Validation passes successfully

C Validation fails due to missing required field

D Validation passes but age is converted to int automatically

💡 Hint

Check the data types of each field in the record compared to the schema.

The schema expects 'age' to be an integer, but the record provides it as a string. Avro does not automatically convert types, so validation fails.

🧠 Conceptual

intermediate

Which Avro schema type is best for optional fields?

You want to define a field in an Avro schema that may or may not be present in the data. Which schema type should you use?

A "null"

B ["null", "type"] (a union with null first)

C "nullable"

D "optional"

💡 Hint

Avro uses unions to represent optional fields.

In Avro, optional fields are represented by a union of null and the actual type, with null usually first to indicate the field can be missing.

🔧 Debug

advanced

Why does this Avro schema cause a parsing error?

Identify the error in this Avro schema snippet: { "type": "record", "name": "Product", "fields": [ {"name": "id", "type": "int"}, {"name": "price", "type": ["float", "null"]}, {"name": "tags", "type": "array", "items": "string"} ] }

A The 'items' property should be inside the 'type' array for 'tags'

B The 'type' for 'tags' should be "array" with 'items' as a sibling key, but here 'items' is misplaced

C The 'type' for 'tags' should be an object with 'type' and 'items' keys, not a string

D The 'items' key is correctly placed; the error is in the union type for 'price'

💡 Hint

Check the structure of the 'array' type in Avro schemas.

In Avro, when defining an array type, the 'type' must be an object with 'type': 'array' and an 'items' key. Here, 'type' is a string and 'items' is a sibling key, which is invalid.

📝 Syntax

advanced

Which Avro schema snippet is syntactically correct for a nested record?

Choose the correct Avro schema snippet defining a record with a nested record field.

A

{
  "type": "record",
  "name": "Employee",
  "fields": [
    {"name": "name", "type": "string"},
    {"name": "address", "type": "record",
      "name": "Address",
      "fields": [
        {"name": "street", "type": "string"},
        {"name": "city", "type": "string"}
      ]
    }
  ]
}

B

{
  "type": "record",
  "name": "Employee",
  "fields": [
    {"name": "name", "type": "string"},
    {"name": "address", "type": "record",
      "fields": [
        {"name": "street", "type": "string"},
        {"name": "city", "type": "string"}
      ]
    }
  ]
}

C

{
  "type": "record",
  "name": "Employee",
  "fields": [
    {"name": "name", "type": "string"},
    {"name": "address", "type": ["null", {
      "type": "record",
      "name": "Address",
      "fields": [
        {"name": "street", "type": "string"},
        {"name": "city", "type": "string"}
      ]
    }]}
  ]
}

D

{
  "type": "record",
  "name": "Employee",
  "fields": [
    {"name": "name", "type": "string"},
    {"name": "address", "type": {
      "type": "record",
      "name": "Address",
      "fields": [
        {"name": "street", "type": "string"},
        {"name": "city", "type": "string"}
      ]
    }}
  ]
}

💡 Hint

Nested records must be defined as an object with type 'record' and a name.

Option D correctly defines the nested record as an object with 'type': 'record', a 'name', and 'fields'. Option D and D miss the nested record object structure. Option D is valid but includes a union with null, which is optional but not required here.

🚀 Application

expert

How many fields will the following Avro schema record have after default values are applied?

Consider this Avro schema: { "type": "record", "name": "Event", "fields": [ {"name": "id", "type": "string"}, {"name": "timestamp", "type": "long"}, {"name": "metadata", "type": ["null", "string"], "default": null}, {"name": "priority", "type": "int", "default": 5} ] } If a record is created with only 'id' and 'timestamp' provided, how many fields will the record have after applying defaults?

A 4 fields

B 3 fields

C 5 fields

D 2 fields

💡 Hint

Fields with defaults are added automatically if missing.

The record has 4 fields total. If only 'id' and 'timestamp' are provided, the fields 'metadata' and 'priority' will be added with their default values, making 4 fields in total.