What is KRYO format?

What is KRYO format?

Kryo is a fast and efficient binary object graph serialization framework for Java. The goals of the project are high speed, low size, and an easy to use API. The project is useful any time objects need to be persisted, whether to a file, database, or over the network.

What is KRYO used for?

Overview. Kryo is a fast and efficient object graph serialization framework for Java. The goals of the project are speed, efficiency, and an easy to use API. The project is useful any time objects need to be persisted, whether to a file, database, or over the network.

Why is KRYO faster?

Kryo is significantly faster and more compact than Java serialization (often as much as 10x), but does not support all Serializable types and requires you to register the classes you’ll use in the program in advance for best performance. So it is not used by default because: Not every java.

What is KRYO serialization in Spark?

It provides two serialization libraries: Java serialization: By default, Spark serializes objects using Java’s ObjectOutputStream framework, and can work with any class you create that implements java. Kryo serialization: Spark can also use the Kryo library (version 4) to serialize objects more quickly.

What is KRYO encoder?

kryo(Class clazz) Creates an encoder that serializes objects of type T using Kryo. static Encoder kryo(scala.reflect.ClassTag evidence$1) (Scala-specific) Creates an encoder that serializes objects of type T using Kryo.

Is Java serialization fast?

Unsafe serialization is greater than 23 times faster than standard use of java. Serializable. Use of RandomAccessFile can speed up standard buffered serialization by almost 4 times. Kryo-dynamic serialization is about 35% slower than the hand-implemented direct buffer.

Why is KRYO serialization faster in spark?

If you need a performance boost and also need to reduce memory usage, Kryo is definitely for you. The join operations and the grouping operations are where serialization has an impact on and they usually have data shuffling. Now lesser the amount of data to be shuffled, the faster will be the operation.

Why is KRYO serialization faster in Spark?

What is a spark encoder?

Encoders are part of Spark’s tungusten framework. Being backed by the raw memory, updation or querying of relevant information from the encoded binary text is done via Java Unsafe APIs. Spark provides a generic Encoder interface and a generic Encoder implementing the interface called as ExpressionEncoder .

What is the difference between DataFrame and Dataset?

Conceptually, consider DataFrame as an alias for a collection of generic objects Dataset[Row], where a Row is a generic untyped JVM object. Dataset, by contrast, is a collection of strongly-typed JVM objects, dictated by a case class you define in Scala or a class in Java.

How can we avoid serialization?

To avoid Java serialization you need to implement writeObject() and readObject() method in your Class and need to throw NotSerializableException from those method.

Why is serialization slow?

Some often used classes make use of old slow + outdated serialization features such as putfield/getfield etc. Too much temporary Object allocation. A lot of validation (versioning, implemented interfaces) Slow Java Input/Output streams.

Is there a maintenance release for Kryo 5.1.0?

This is a maintenance release coming with bug fixes for CompatibleFieldSerializer and the versioned artifact. In Kryo 5.1.0, a direct dependency on the unversioned JAR accidentally made it into the POM for the versioned artifact (see #825 ).

Is there backwards compatibility with Kryo 5.2.0?

If you have serialized records with non-final field types that you need to read with Kryo 5.2.0, you can enable backwards compatibility globally or for individual types (recommended): For migration from previous major versions please check out the migration guide.

What do you need to know about the Kryo framework?

Kryo is a framework to facilitate serialization. The framework itself doesn’t enforce a schema or care what or how data is written or read. Serializers are pluggable and make the decisions about what to read and write. Many serializers are provided out of the box to read and write data in various ways.

Is it possible to use Kryo without Maven?

Using Kryo without Maven requires placing the Kryo JAR on your classpath along with the dependency JARs found in lib. Kryo 5 before 5.1.0 ships with Objenesis 3.1 which currently supports Android API >= 26. If you want to use these versions of Kryo with older Android APIs, you need to explicitely depend on Objensis 3.2.