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[SPARK-12195] [SQL] Adding BigDecimal, Date and Timestamp into Encoder #10188

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18 changes: 18 additions & 0 deletions sql/catalyst/src/main/scala/org/apache/spark/sql/Encoder.scala
Original file line number Diff line number Diff line change
Expand Up @@ -97,6 +97,24 @@ object Encoders {
*/
def STRING: Encoder[java.lang.String] = ExpressionEncoder()

/**
* An encoder for nullable decimal type.
* @since 1.6.0
*/
def DECIMAL: Encoder[java.math.BigDecimal] = ExpressionEncoder()

/**
* An encoder for nullable date type.
* @since 1.6.0
*/
def DATE: Encoder[java.sql.Date] = ExpressionEncoder()

/**
* An encoder for nullable timestamp type.
* @since 1.6.0
*/
def TIMESTAMP: Encoder[java.sql.Timestamp] = ExpressionEncoder()

/**
* Creates an encoder for Java Bean of type T.
*
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Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,9 @@
package test.org.apache.spark.sql;

import java.io.Serializable;
import java.math.BigDecimal;
import java.sql.Date;
import java.sql.Timestamp;
import java.util.*;

import scala.Tuple2;
Expand Down Expand Up @@ -385,6 +388,20 @@ public void testNestedTupleEncoder() {
Assert.assertEquals(data3, ds3.collectAsList());
}

@Test
public void testTypeEncoder() {
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testPrimitiveEncoder?

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Sure. Thank you! Let me change it now.

Encoder<Tuple5<Double, BigDecimal, Date, Timestamp, Float>> encoder =
Encoders.tuple(Encoders.DOUBLE(), Encoders.DECIMAL(), Encoders.DATE(), Encoders.TIMESTAMP(),
Encoders.FLOAT());
List<Tuple5<Double, BigDecimal, Date, Timestamp, Float>> data =
Arrays.asList(new Tuple5<Double, BigDecimal, Date, Timestamp, Float>(
1.7976931348623157E308, new BigDecimal("0.922337203685477589"),
Date.valueOf("1970-01-01"), new Timestamp(System.currentTimeMillis()), Float.MAX_VALUE));
Dataset<Tuple5<Double, BigDecimal, Date, Timestamp, Float>> ds =
context.createDataset(data, encoder);
Assert.assertEquals(data, ds.collectAsList());
}

@Test
public void testTypedAggregation() {
Encoder<Tuple2<String, Integer>> encoder = Encoders.tuple(Encoders.STRING(), Encoders.INT());
Expand Down