Apache Avro is a data serialization format. It is similar to Thrift and Protocol Buffers, but uses a different approach to specify schemas: instead of using interface definitions, Avro uses a JSON format. This allows for dynamic typing, which is useful for data that doesn't have a fixed schema.
Avro schemas are defined in a JSON file, and each file can contain multiple schemas. Each schema has a name, and a set of fields. Fields have a name, a type, and an optional default value. Avro schemas can be nested, and fields can be either optional or required.
When data is serialized using Avro, it is first converted into binary form, which is then compressed using either the Snappy or Deflate compression codecs. The binary data can then be deserialized back into its original form.
Avro is used in a number of projects, including Apache Hadoop, Apache Hive, and Apache Kafka. It is also used by a number of languages, including Java, Python, and C++.
When should I use Apache Avro?
There is no definitive answer to this question, as the decision of when to use Apache Avro depends on a variety of factors specific to your organization's needs. However, some general guidelines that may help you make this decision include:
- If you need a compact, fast, binary data format with a very small footprint, then Avro may be a good choice.
- If you need a data format that supports rich data structures and supports evolution of these structures over time, then Avro may be a good choice.
- If you need a data format that is easy to use and understand, then Avro may not be the best choice.
Who uses Apache Avro?
Apache Avro is a data serialization system that is widely used in the Hadoop ecosystem. It is a popular choice for many Hadoop users because it supports a wide range of data types and has good performance.
Avro is used by many projects in the Hadoop ecosystem, including Apache Hive, Apache HBase, Apache Kafka, and Apache Drill.
What are Avro schemas?
An Avro schema is a JSON document that defines the structure of an Avro data record. An Avro schema can be used to serialize and deserialize Avro data from a variety of programming languages.
The Avro schema defines the data type of each field in the record, as well as the order of the fields. Avro schemas also support field names and docstrings.
Avro schemas are typically stored in files with a ".avsc" extension.
Is Avro same as JSON?
No, Avro is not the same as JSON.
Avro is a binary serialization format that uses a compact, fast, binary encoding to exchange data between systems, while JSON is a text serialization format that uses a human-readable format to exchange data.
Avro is typically faster and more compact than JSON, but it is not as human-readable.
What does Avro stand for?
The Apache Avro data format is a binary file format that allows data to be serialized and deserialized in a very efficient way. It was developed by Doug Cutting, the creator of Hadoop, and is now used by a number of big data processing frameworks, including Hadoop, Spark, and Hive.