trait Encoder[T] extends Serializable
Used to convert a JVM object of type T to and from the internal Spark SQL representation.
Scala
Encoders are generally created automatically through implicits from a SparkSession, or can be
explicitly created by calling static methods on Encoders.
import spark.implicits._ val ds = Seq(1, 2, 3).toDS() // implicitly provided (spark.implicits.newIntEncoder)
Java
Encoders are specified by calling static methods on Encoders.
List<String> data = Arrays.asList("abc", "abc", "xyz"); Dataset<String> ds = context.createDataset(data, Encoders.STRING());
Encoders can be composed into tuples:
Encoder<Tuple2<Integer, String>> encoder2 = Encoders.tuple(Encoders.INT(), Encoders.STRING()); List<Tuple2<Integer, String>> data2 = Arrays.asList(new scala.Tuple2(1, "a"); Dataset<Tuple2<Integer, String>> ds2 = context.createDataset(data2, encoder2);
Or constructed from Java Beans:
Encoders.bean(MyClass.class);Implementation
- Encoders should be thread-safe.
- Annotations
- @implicitNotFound()
- Source
- Encoder.scala
- Since
- 1.6.0 
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-   abstract  def clsTag: ClassTag[T]A ClassTag that can be used to construct an Array to contain a collection of T.
-   abstract  def schema: StructTypeReturns the schema of encoding this type of object as a Row. 
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- (Since version 9)