{"id":21926,"date":"2018-07-18T16:20:34","date_gmt":"2018-07-18T10:50:34","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=21926"},"modified":"2023-08-16T08:10:36","modified_gmt":"2023-08-16T02:40:36","slug":"avro-tutorial","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/avro-tutorial\/","title":{"rendered":"Apache Avro Tutorial For Beginners | Learn Avro"},"content":{"rendered":"

Today, we will start our new journey with Apache Avro tutorial. A language-neutral data serialization system<\/em>, which is developed by the father of Hadoop<\/strong>, \u201cDoug Cutting<\/em>\u201d, is what we call Apache Avro. While it comes to serialize data in Hadoop(Data Serialization)<\/em>, Avro is the most preferred tool. <\/span><\/p>\n

So, in this Avro tutorial, we will learn the whole concept of Apache Avro in detail. Apache Avro Tutorial includes Avro schemas, features as well as its uses to understand well. Moreover, we will see the need for Avro, Avro pros & Cons and Avro example. <\/span><\/p>\n

Also, we will discuss datatypes and comparisons in Avro. However, Avro performs Data Serialization. So, let\u2019s begin with the brief introduction of Data Serialization, then we will move to Apache Avro.<\/span><\/p>\n

What is Data Serialization?<\/span><\/h3>\n

The act of transforming complicated data structures or objects into a format that is simple to store, transport, or reconstruct later on is known as data serialisation. To enable effective utilisation in a variety of scenarios, such as data storage, network communication, or inter-process communication, it entails translating data into a standardised, compact binary or textual representation.<\/p>\n

Data serialization’s main goals are to enable data storage on disc drives or databases, facilitate data transmission across networks or systems, support versioning and evolution of data formats without compromising backward compatibility, and promote application interoperability. JSON, XML, Protocol Buffers, Apache Avro, and MessagePack are examples of popular data serialisation formats; each has unique benefits and use cases.<\/p>\n

Modern data-driven applications and distributed systems, where effective data transmission and storage are necessary for smooth data processing and communication, use data serialisation as a core idea.<\/p>\n

What is Avro?<\/span><\/h3>\n

Avro Tutorial – A language-neutral data serialization system is what we call Avro. Basically, It was developed by the father of Hadoop, Doug Cutting. Previously there was a lack of language portability in Hadoop writable classes. <\/span><\/p>\n

So, Avro becomes quite helpful at that place. It is because Avro deals with data formats that can be further processed by multiple languages. Moreover, we can say, to serialize data in Hadoop, Avro is the most preferred tool.<\/span><\/p>\n

In addition, it has a schema-based system. And, there are several reads and write operations of this language-independent schema. <\/span><\/p>\n

Especially, the data which has a built-in schema is that Avro serializes. Also, the data which can be deserialized by any application, Avro serializes that data into a compact binary format.<\/span><\/p>\n

And, in order to declare the data structures, Avro uses JSON format. Avro supports various languages like Java, C, C++, C#, Python<\/strong>, as well as Ruby.<\/span><\/p>\n

a. Key Points About Apache Avro<\/strong>
\nSome key points of Avro in Apache Avro Tutorial are:<\/p>\n