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Editorial Team
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Editorial Team
Asked: May 14, 20262026-05-14T01:06:04+00:00 2026-05-14T01:06:04+00:00

according to Apache AVRO project, Avro is a serialization system. By saying data serialization

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according to Apache AVRO project, “Avro is a serialization system”. By saying data serialization system, does it mean that avro is a product or api?

also, I am not quit sure about what a data serialization system is? for now, my understanding is that it is a protocol that defines how data object is passed over the network. Can anyone help explain it in an intuitive way that it is easier for people with limited distributed computing background to understand?

Thanks in advance!

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  1. Editorial Team
    Editorial Team
    2026-05-14T01:06:05+00:00Added an answer on May 14, 2026 at 1:06 am

    So when Hadoop was being written by Doug Cutting he decided that the standard Java method of serializing Java object using Java Object Serialization (Java Serialization) didn’t meet his requirements for Hadoop. Namely, these requirements were:

    1. Serialize the data into a compact binary format.
    2. Be fast, both in performance and how quickly it allowed data to be transfered.
    3. Interoperable so that other languages plug into Hadoop more easily.

    As he described Java Serialization:

    It looked big and hairy and I though we needed something lean and mean

    Instead of using Java Serialization they wrote their own serialization framework. The main perceived problems with Java Serialization was that it writes the classname of each object being serialized to the stream, with each subsequent instance of that class containing a 5 byte reference to the first, instead of the classname.

    As well as reducing the effective bandwidth of the stream this causes problems with random access as well as sorting of records in a serialized stream. Thus Hadoop serialization doesn’t write the classname or the required references, and makes the assumption that the client knows the expected type.

    Java Serialization also creates a new object for each one that is deserialized. Hadoop Writables, which implement Hadoop Serialization, can be reused. Thus, helping to improve the performance of MapReduce which accentually serializes and deserializes billions of records.

    Avro fits into Hadoop in that it approaches serialization in a different manner. The client and server exchange a scheme which describes the datastream. This helps make it fast, compact and importantly makes it easier to mix languanges together.

    So Avro defines a serialization format, a protocol for clients and servers to communicate these serial streams and a way to compactly persist data in files.

    I hope this helps. I thought a bit of Hadoop history would help understand why Avro is a subproject of Hadoop and what its meant to help with.

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