Avro MCQs and Answers With Explanation: If you are looking to test your knowledge on Avro, a data serialization system used by Apache Hadoop, then the Avro MCQs and Quiz is an excellent way to do so. This quiz comprises the top 55 Avro MCQs and Answers, covering various aspects of Avro such as data types, serialization, schema evolution, and more.
Avro MCQs and Answers
The Avro Multiple Choice Questions and Answers are designed to test your understanding of Avro, and each question is accompanied by a detailed explanation to help you learn more about the topic. So, if you want to test your knowledge of Avro, take the Avro Quiz now and see how well you fare!
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Avro Multiple Choice Questions and Answers
| Name | Avro |
| Exam Type | MCQ (Multiple Choice Questions) |
| Category | Technical Quiz |
| Mode of Quiz | Online |
Top 55 Avro MCQs | Avro Quiz
1. What is Avro?
A. A programming language
B. A data serialization system
C. An operating system
D. A database management system
Answer: B
Explanation: Avro is a data serialization system that is used to exchange data between systems written in different programming languages.
2. What is the primary purpose of Avro?
A. To store data in a database
B. To exchange data between systems
C. To create user interfaces
D. To develop web applications
Answer: B
Explanation: Avro’s primary purpose is to provide a compact and efficient way to exchange data between systems, particularly in distributed systems where different programming languages and platforms are used.
3. Which of the following is a characteristic of Avro?
A. Avro supports only Java programming language
B. Avro provides built-in support for schema evolution
C. Avro is designed for storing unstructured data
D. Avro is slower than other serialization systems
Answer: B
Explanation: Avro provides built-in support for schema evolution, which means that changes to the schema of a dataset can be made over time without breaking compatibility with existing data.
4. Which of the following is NOT a benefit of using Avro?
A. Avro provides a compact and efficient binary encoding format
B. Avro allows for schema evolution
C. Avro is supported only by a few programming languages
D. Avro supports rich data structures
Answer: C
Explanation: Avro is supported by many programming languages including Java, Python, C++, and Ruby, among others.
5. What is a schema in Avro?
A. A data structure that defines the format of data
B. A programming language
C. A database management system
D. An operating system
Answer: A
Explanation: A schema in Avro is a data structure that defines the format of the data that is being serialized or deserialized.
6. Which of the following is NOT a data type supported by Avro?
A. Boolean
B. String
C. Date
D. Float
Answer: C
Explanation: Avro supports a wide range of data types, including boolean, string, integer, float, double, and more.
7. What is the difference between Avro and other serialization systems like JSON and XML?
A. Avro is faster and more efficient
B. Avro is a programming language
C. Avro does not support schema evolution
D. Avro can only be used with Java
Answer: A
Explanation: Avro is faster and more efficient than other serialization systems like JSON and XML because it uses a compact binary encoding format.
8. Which of the following is a limitation of Avro?
A. Avro can only be used with Java
B. Avro does not support schema evolution
C. Avro has a steep learning curve
D. Avro cannot handle large datasets
Answer: C
Explanation: Avro has a steep learning curve and can be challenging to use, particularly for developers who are new to data serialization.
9. How does Avro support schema evolution?
A. By allowing changes to be made to the schema over time without breaking compatibility
B. By requiring a complete rewrite of the schema every time a change is made
C. By creating a new schema for each version of the data
D. By only allowing changes to be made to the schema before data is serialized
Answer: A
Explanation: Avro supports schema evolution by allowing changes to be made to the schema over time without breaking compatibility with existing data.
10. How does Avro handle data validation?
A. By allowing any data to be serialized and deserialized without validation
B. By providing built-in data validation functionality
C. By relying on external validation libraries
D. By requiring manual validation of data before serialization and deserialization
Answer: B
Explanation: Avro provides built-in data validation functionality to ensure that data conforms to the schema.
11. What is the default encoding format used by Avro?
A. JSON
B. XML
C. Binary
D. YAML
Answer: C
Explanation: The default encoding format used by Avro is a compact binary format that is faster and more efficient than JSON or XML.
12. Which of the following is NOT a component of Avro?
A. Data serialization
B. RPC framework
C. Database management system
D. Schema definition language
Answer: C
Explanation: Avro is a data serialization system and includes components such as a schema definition language and an RPC framework.
13. Which of the following is a benefit of using Avro over other serialization systems?
A. Avro is slower and less efficient than other serialization systems
B. Avro supports only a limited number of programming languages
C. Avro provides built-in support for schema evolution
D. Avro requires manual schema definition for each dataset
Answer: C
Explanation: Avro provides built-in support for schema evolution, which allows changes to be made to the schema over time without breaking compatibility with existing data.
14. What is a container file in Avro?
A. A file format that contains serialized data and metadata
B. A file format that contains code for a Java program
C. A file format that contains database tables and records
D. A file format that contains only schema information
Answer: A
Explanation: A container file in Avro is a file format that contains serialized data and metadata, including the schema used to serialize the data.
15. Which of the following is NOT a feature of Avro?
A. Data compression
B. Rich data types
C. Automatic schema definition
D. RPC framework
Answer: C
Explanation: Avro requires manual schema definition, but provides features such as data compression, rich data types, and an RPC framework.
16. How does Avro handle schema evolution?
A. By requiring a complete rewrite of the schema every time a change is made
B. By creating a new schema for each version of the data
C. By allowing changes to be made to the schema over time without breaking compatibility
D. By only allowing changes to be made to the schema before data is serialized
Answer: C
Explanation: Avro supports schema evolution by allowing changes to be made to the schema over time without breaking compatibility with existing data.
17. What is an RPC framework in Avro?
A. A framework for managing databases
B. A framework for creating user interfaces
C. A framework for defining APIs for remote procedure calls
D. A framework for creating web applications
Answer: C
Explanation: An RPC framework in Avro is a framework for defining APIs for remote procedure calls, allowing different systems to communicate with each other over a network.
18. What is a codec in Avro?
A. A data structure that defines the format of data
B. A component of the RPC framework
C. A module that provides data compression or decompression
D. A container file that contains serialized data and metadata
Answer: C
Explanation: A codec in Avro is a module that provides data compression or decompression, allowing serialized data to be transmitted more efficiently.
18. Which of the following is a benefit of using Avro for distributed systems?
A. Avro is slower and less efficient than other serialization systems
B. Avro provides built-in support for schema evolution
C. Avro only supports a limited number of programming languages
D. Avro requires manual schema definition for each dataset
Answer: B
Explanation: Avro provides built-in support for schema evolution, allowing changes to be made to the schema over time without breaking compatibility with existing data. This is especially useful for distributed systems where different systems may be using different versions of the schema.
20. Which of the following is NOT a data type in Avro?
A. Int
B. Float
C. Timestamp
D. String
Answer: C
Explanation: Avro supports a wide variety of data types, including int, float, string, and many others. However, timestamp is not a built-in data type in Avro.
21. Which of the following is a benefit of using Avro for data serialization?
A. Avro is slower and less efficient than other serialization systems
B. Avro supports only a limited number of programming languages
C. Avro provides a compact binary format that is faster and more efficient than other formats
D. Avro requires manual schema definition for each dataset
Answer: C
Explanation: Avro provides a compact binary format that is faster and more efficient than other serialization formats like JSON or XML.
22. What is a writer schema in Avro?
A. A schema used for deserializing data
B. A schema used for serializing data
C. A schema used for validating data
D. A schema used for compressing data
Answer: B
Explanation: A writer schema in Avro is a schema used for serializing data, allowing the data to be written to a file or transmitted over a network.
23. What is a reader schema in Avro?
A. A schema used for deserializing data
B. A schema used for serializing data
C. A schema used for validating data
D. A schema used for compressing data
Answer: A
Explanation: A reader schema in Avro is a schema used for deserializing data, allowing the data to be read from a file or received over a network.
24. What is the role of a codec in Avro?
A. To define the schema used for serializing and deserializing data
B. To provide data compression or decompression
C. To validate data against a schema
D. To provide a container format for serialized data
Answer: B
Explanation: A codec in Avro provides data compression or decompression, allowing serialized data to be transmitted more efficiently.
25. What is the difference between a primitive data type and a complex data type in Avro?
A. A primitive data type is built-in to Avro, while a complex data type is user-defined
B. A primitive data type is a simple data type like int or string, while a complex data type is a more complex data structure like an array or record
C. A primitive data type is only used for serialization, while a complex data type is used for both serialization and deserialization
D. There is no difference between a primitive data type and a complex data type in Avro
Answer: B
Explanation: A primitive data type in Avro is a simple data type like int or string, while a complex data type is a more complex data structure like an array or record. Complex data types can be user-defined, while primitive data types are built-in to Avro.
26. Which of the following is NOT a complex data type in Avro?
A. Record
B. Enum
C. Union
D. Float
Answer: D
Explanation: Float is a primitive data type in Avro, while record, enum, and union are complex data types.
27. What is an Avro container file?
A. A file format used for storing serialized Avro data
B. A file format used for storing uncompressed Avro data
C. A file format used for storing Avro schema definitions
D. A file format used for storing compressed Avro data
Answer: A
Explanation: An Avro container file is a file format used for storing serialized Avro data, including both the data and the schema used to serialize it.
28. Which of the following is NOT a supported serialization format in Avro?
A. JSON
B. XML
C. Binary
D. CSV
Answer: D
Explanation: While Avro supports a variety of serialization formats, including JSON, XML, and binary, it does not support CSV as a serialization format.
29. What is a logical type in Avro?
A. A type that is defined by the user rather than built-in to Avro
B. A type that is only used for serialization and not deserialization
C. A type that is used to validate data against a schema
D. A type that provides additional constraints or functionality beyond a simple data type
Answer: D
Explanation: A logical type in Avro provides additional constraints or functionality beyond a simple data type, such as a decimal or timestamp type.
30. What is a schema registry in Avro?
A. A tool used to validate Avro schemas
B. A service that manages and stores Avro schemas for distributed systems
C. A tool used to convert Avro schemas to other schema formats
D. A tool used to visualize Avro schema hierarchies
Answer: B
Explanation: A schema registry in Avro is a service that manages and stores Avro schemas for distributed systems, allowing different systems to use a common schema for serialization and deserialization.
31. What is the purpose of an Avro IDL file?
A. To define the schema for an Avro dataset
B. To generate code for serializing and deserializing Avro data
C. To provide a specification for a distributed system that uses Avro
D. To define logical types that can be used in Avro schemas
Answer: C
Explanation: An Avro IDL (Interface Definition Language) file provides a specification for a distributed system that uses Avro, defining the messages that can be sent and received using Avro.
32. What is the purpose of an Avro protocol?
A. To define the schema for an Avro dataset
B. To generate code for serializing and deserializing Avro data
C. To provide a specification for a distributed system that uses Avro
D. To define logical types that can be used in Avro schemas
Answer: C
Explanation: An Avro protocol provides a specification for a distributed system that uses Avro, defining the messages that can be sent and received using Avro.
33. What is the Avro schema resolution strategy?
A. A set of rules for resolving conflicts between different versions of a schema
B. A set of rules for validating data against a schema
C. A set of rules for compressing Avro data
D. A set of rules for converting Avro data to other formats
Answer: A
Explanation: The Avro schema resolution strategy is a set of rules for resolving conflicts between different versions of a schema, allowing for evolution of schemas over time while still ensuring backward compatibility.
34. Which of the following is NOT a schema evolution operation supported by Avro?
A. Adding a new field to a record
B. Removing a field from a record
C. Renaming a field in a record
D. Changing the data type of a field in a record
Answer: B
Explanation: Avro supports schema evolution operations like adding a new field to a record, renaming a field in a record, and changing the data type of a field in a record, but it does not support removing a field from a record.
35. What is the purpose of an Avro encoder?
A. To convert Avro data to a binary format for transmission or storage
B. To convert Avro data to a JSON format for transmission or storage
C. To validate Avro data against a schema
D. To convert Avro data to another serialization format
Answer: A
Explanation: An Avro encoder is used to convert Avro data to a binary format for transmission or storage, allowing it to be efficiently serialized and deserialized.
36. What is the purpose of an Avro decoder?
A. To convert Avro data from a binary format back to its original format
B. To convert Avro data from a JSON format back to its original format
C. To validate Avro data against a schema
D. To convert Avro data to another serialization format
Answer: A
Explanation: An Avro decoder is used to convert Avro data from a binary format back to its original format, allowing it to be efficiently deserialized.
37. What is a logical schema in Avro?
A. A schema that describes the structure and types of Avro data
B. A schema that describes the rules for validating Avro data
C. A schema that provides additional constraints or functionality beyond a simple data type
D. A schema that is defined by the user rather than built-in to Avro
Answer: D
Explanation: A logical schema in Avro is a schema that is defined by the user rather than built-in to Avro, allowing for custom data types and structures to be used.
38. Which of the following is NOT an example of an Avro complex data type?
A. Record
B. Array
C. Union
D. Int
Answer: D
Explanation: Int is not an example of an Avro complex data type, as it is a primitive data type. Avro complex data types include records, arrays, unions, and maps.
39. Which of the following is NOT a valid Avro data type?
A. Null
B. Double
C. Long.Long
D. Bytes
Answer: C
Explanation: Long.Long is not a valid Avro data type. Valid Avro data types include null, boolean, int, long, float, double, bytes, and string, as well as complex data types like records, arrays, unions, and maps.
40. Which of the following is a valid Avro schema definition for a simple record?
A. {“type”: “record”, “fields”: [{“name”: “field1”, “type”: “int”}]}
B. {“type”: “int”}
C. {“name”: “record1”, “fields”: [{“name”: “field1”, “type”: “int”}]}
D. {“name”: “record1”, “type”: “record”, “fields”: [{“name”: “field1”, “type”: “int”}]}
Answer: D
Explanation: A valid Avro schema definition for a simple record includes the record name, the type “record”, and the fields of the record. The correct schema definition is {“name”: “record1”, “type”: “record”, “fields”: [{“name”: “field1”, “type”: “int”}]}.
41. Which of the following is a valid Avro schema definition for a union of two data types?
A. {“type”: “union”, “types”: [“int”, “long”]}
B. [“int”, “long”]
C. {“type”: [“int”, “long”]}
D. {“name”: “union1”, “type”: “union”, “types”: [“int”, “long”]}
Answer: A
Explanation: A valid Avro schema definition for a union of two data types includes the type “union” and an array of the possible data types. The correct schema definition is {“type”: “union”, “types”: [“int”, “long”]}.
42. Which of the following is a valid Avro schema definition for a field that can have multiple data types?
A. {“name”: “field1”, “type”: [“int”, “string”]}
B. {“name”: “field1”, “type”: “union”, “types”: [“int”, “string”]}
C. {“name”: “field1”, “type”: “multi”, “types”: [“int”, “string”]}
D. {“name”: “field1”, “type”: “choice”, “types”: [“int”, “string”]}
Answer: B
Explanation: A valid Avro schema definition for a field that can have multiple data types includes the type “union” and an array of the possible data types. The correct schema definition is {“name”: “field1”, “type”: “union”, “types”: [“int”, “string”]}.
43. What is the purpose of an Avro IDL?
A. To define Avro schemas using a simple text-based syntax
B. To validate Avro data against a schema
C. To provide a user-friendly interface
D. To generate Avro code in various programming languages
Answer: A
Explanation: An Avro IDL (Interface Definition Language) is used to define Avro schemas using a simple text-based syntax. It allows developers to define and document schemas in a way that is easy to read and understand, and it can be used to generate Avro code in various programming languages.
44. Which of the following is a valid Avro IDL definition for a simple record?
A. @record record1 { int field1; }
B. record record1 { int field1; }
C. { “type”: “record”, “name”: “record1”, “fields”: [{“name”: “field1”, “type”: “int”}]}
D. record1: { field1: int }
Answer: A
Explanation: A valid Avro IDL definition for a simple record includes the @record keyword, the record name, and the fields of the record. The correct definition is “@record record1 { int field1; }”.
45. Which of the following is a valid Avro IDL definition for a union of two data types?
A. union { int, long } union1;
B. union1: { int | long }
C. @union union1 { int, long }
D. union1 = { int, long }
Answer: C
Explanation: A valid Avro IDL definition for a union of two data types includes the @union keyword, the union name, and the possible data types. The correct definition is “@union union1 { int, long }”.
46. Which of the following is a valid Avro IDL definition for a field that can have multiple data types?
A. field1: int | string;
B. field1 = int | string;
C. @field field1 { int | string }
D. { “name”: “field1”, “type”: [“int”, “string”] }
Answer: A
Explanation: A valid Avro IDL definition for a field that can have multiple data types includes the field name and the possible data types separated by the “|” symbol. The correct definition is “field1: int | string;”.
47. Which of the following is a valid Avro protocol definition for a simple request-response message?
A. @protocol protocol1 { request-response int method1(int arg1); }
B. protocol protocol1 { request-response { int method1(int arg1); } }
C. { “namespace”: “ns1”, “protocol”: “protocol1”, “messages”: {“method1”: {“request”: [{“name”: “arg1”, “type”: “int”}], “response”: “int”}}}
D. protocol1: { method1: request-response int arg1 }
Answer: A
Explanation: A valid Avro protocol definition for a simple request-response message includes the @protocol keyword, the protocol name, and the method details, including the method name, request parameters, and response type. The correct definition is “@protocol protocol1 { request-response int method1(int arg1); }”.
48. Which of the following is a valid Avro protocol definition for a notification message?
A. @protocol protocol1 { void method1(int arg1); }
B. protocol protocol1 { notification { void method1(int arg1); } }
C. { “namespace”: “ns1”, “protocol”: “protocol1”, “messages”: {“method1”: {“request”: [{“name”: “arg1”, “type”: “int”}]}}}
D. protocol1: { method1: notification int arg1 }
Answer: A
Explanation: A valid Avro protocol definition for a notification message includes the @protocol keyword, the protocol name, and the method details, including the method name and parameters. The return type should be “void” to indicate that no response is expected. The correct definition is “@protocol protocol1 { void method1(int arg1); }”.
49. Which of the following is NOT a valid Avro logical type?
A. decimal
B. timestamp-millis
C. email
D. date
Answer: C
Explanation: The Avro specification defines several logical types that can be used in addition to the basic Avro data types. These include “decimal”, “timestamp-millis”, and “date”. “email” is not a valid Avro logical type.
50. Which of the following is a valid Avro schema for a union of two data types?
A. { “type”: “union”, “name”: “union1”, “fields”: [“int”, “string”] }
B. { “type”: “union”, “name”: “union1”, “fields”: [{“type”: “int”}, {“type”: “string”}] }
C. { “type”: “union”, “name”: “union1”, “fields”: {“int”, “string”} }
D. { “type”: “union”, “name”: “union1”, “fields”: [{“name”: “int”, “type”: “int”}, {“name”: “string”, “type”: “string”}] }
Answer: B
Explanation: A valid Avro schema for a union of two data types includes the “union” type, the union name, and an array of the possible data types. Each data type should be specified as a JSON object with a “type” field. The correct definition is “{ “type”: “union”, “name”: “union1”, “fields”: [{“type”: “int”}, {“type”: “string”}] }”.
51. Which of the following is a valid Avro schema for a fixed-length binary data type?
A. { “type”: “fixed”, “name”: “fixed1”, “size”: 10 }
B. { “type”: “binary”, “name”: “fixed1”, “size”: 10 }
C. { “type”: “fixed”, “name”: “fixed1”, “length”: 10 }
D. { “type”: “bytes”, “name”: “fixed1”, “size”: 10 }
Answer: A
Explanation: A fixed-length binary data type in Avro is defined using the “fixed” type. The schema should include the name of the fixed data type and the size of the fixed data, specified as an integer. The correct definition is “{ “type”: “fixed”, “name”: “fixed1”, “size”: 10 }”.
52. Which of the following is a valid Avro schema for a map of string to int?
A. { “type”: “map”, “values”: “int” }
B. { “type”: “map”, “values”: {“type”: “int”} }
C. { “type”: “map”, “values”: “string”, “keys”: “int” }
D. { “type”: “map”, “values”: “int”, “keys”: “string
Answer: B
Explanation: A map in Avro is defined using the “map” type, with the “values” field specifying the data type of the map values. In this case, the map values are integers, so the “values” field should be a JSON object with a “type” field set to “int”. The correct definition is “{ “type”: “map”, “values”: {“type”: “int”} }”.
53. Which of the following is a valid Avro schema for a record with a required string field named “name” and an optional int field named “age”?
A. { “type”: “record”, “name”: “person”, “fields”: [{“name”: “name”, “type”: “string”, “required”: true}, {“name”: “age”, “type”: “int”, “optional”: true}] }
B. { “type”: “record”, “name”: “person”, “fields”: [{“name”: “name”, “type”: “string”}, {“name”: “age”, “type”: “int”}] }
C. { “type”: “record”, “name”: “person”, “fields”: [{“name”: “name”, “type”: “string”}, {“name”: “age”, “type”: [“int”, “null”]}] }
D. { “type”: “record”, “name”: “person”, “fields”: [{“name”: “name”, “type”: “string”}, {“name”: “age”, “type”: “int”, “nullable”: true}] }
Answer: B
Explanation: A valid Avro schema for a record includes the “record” type, the record name, and an array of fields. Each field should be specified as a JSON object with a “name” field, a “type” field, and optional flags for whether the field is required or optional. For this schema, the correct definition is “{ “type”: “record”, “name”: “person”, “fields”: [{“name”: “name”, “type”: “string”}, {“name”: “age”, “type”: “int”}] }”.
54. Which of the following is NOT a valid Avro logical operator?
A. and
B. or
C. not
D. xor
Answer: D
Explanation: Avro supports several logical operators for combining multiple boolean expressions, including “and”, “or”, and “not”. “Xor” is not a valid logical operator in Avro.
55. Which of the following is a valid Avro schema for an enum with three possible values: “RED”, “GREEN”, and “BLUE”?
A. { “type”: “enum”, “name”: “colors”, “values”: [“RED”, “GREEN”, “BLUE”] }
B. { “type”: “enum”, “name”: “colors”, “values”: [{“name”: “RED”}, {“name”: “GREEN”}, {“name”: “BLUE”}] }
C. { “type”: “enum”, “name”: “colors”, “values”: [“string”, “string”, “string”], “symbols”: [“RED”, “GREEN”, “BLUE”] }
D. { “type”: “enum”, “name”: “colors”, “values”: [{“type”: “string”, “value”: “RED”}, {“type”: “string”, “value”: “GREEN”}, {“type”: “string”, “value”: “BLUE”}] }
Answer: A
Explanation: A valid Avro schema for an enum includes the “enum” type, the enum name, and an array of the possible enum values. The values should be specified as strings in this case. The correct definition is { “type”: “enum”, “name”: “colors”, “values”: [“RED”, “GREEN”,
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