12 Best Apache Avro Features | Reasons Why Avro is Popular?
1. Apache Avro Features – Objective
In this Apache Avro tutorial, we will discuss Avro Features. These Avro features are the basic reasons which make it so popular. So, in this article of Features of Avro, we will see the reasons for Avro Popularity in detail.
So, let’s start exploring Avro Features.
2. Features of Avro
So, here is the list of the reasons why Avro is a good choice. Let’s discuss these Avro Features one by one:
a. Schema Evolution
While data is written or read, Avro does requires schemas. However, the best part is we can use different schemas for serialization and deserialization purpose. Though Avro handles the missing/extra/modified fields.
b. Code Generation
Avro has the ability to generate code although it is not mandatory make Avro works.
Due to serialization schemas in Avro, it is easy to achieve versioning by defining correctly read schema.
d. Untagged Data
As Avro offers a schema with binary data it permits that it is possible to write each datum without the overhead. So, that results in more compact data encoding, as well as faster data processing.
e. Language Support
f. Transparent Compression
We don’t need to compress Avro files manually because the framework itself does some size optimizations.
g. Dynamic Typing
Basically, serialization and deserialization occur without even code generation. So, Dynamic typing complements the code generation, which is present in Avro especially for statically typed languages as an optional optimization.
Avro files are Splittable in nature, it is possible because of synchronization markers which are used between blocks. Basically, these blocks allow efficient splitting of files for MapReduce processing.
i. Native Support in MapReduce
As input, output or intermediate files, we can use Avro files in each step of MapReduce jobs. Moreover, all useful classes, like readers or reducers, are in the package: org.apache.avro.mapred.
j. Avro Schema Provides Future-Proof Robustness
Avro Schemas offers future proof of our data and also make it more robust by supporting all past (older Consumers), future (Big Data) as well as current use cases. Basically, for making the data robust for streaming architectures, the schema with its support for evolution is essential.
k. JSON Libraries
In all the languages those already have JSON libraries, Avro has the facility for implementation, due to its JSON defined Avro schemas.
l. Rich Data Structures
Apache Avro provides rich data structures along with compact, fast, binary data format. Because of its rich data structures, it can create a record which may consist of an array, an enumerated type, and a sub-record.
So, this was all in Avro features. Hope you like our explanation.
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3. Conclusion: Avro Features
Hence, we have seen 12 best Avro features, those make it stand out from the crowd and also makes it Popular. However, to learn Avro in more detail, stay tuned at Data Flair. Learn more Learn well!
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