@@ -1057,6 +1057,7 @@ Spark SQL supports the vast majority of Hive features, such as:
1057
1057
* ` STRING `
1058
1058
* ` BINARY `
1059
1059
* ` TIMESTAMP `
1060
+ * ` DATE `
1060
1061
* ` ARRAY<> `
1061
1062
* ` MAP<> `
1062
1063
* ` STRUCT<> `
@@ -1157,6 +1158,7 @@ evaluated by the SQL execution engine. A full list of the functions supported c
1157
1158
* Datetime type
1158
1159
- ` TimestampType ` : Represents values comprising values of fields year, month, day,
1159
1160
hour, minute, and second.
1161
+ - ` DateType ` : Represents values comprising values of fields year, month, day.
1160
1162
* Complex types
1161
1163
- ` ArrayType(elementType, containsNull) ` : Represents values comprising a sequence of
1162
1164
elements with the type of ` elementType ` . ` containsNull ` is used to indicate if
@@ -1264,6 +1266,13 @@ import org.apache.spark.sql._
1264
1266
TimestampType
1265
1267
</td >
1266
1268
</tr >
1269
+ <tr >
1270
+ <td > <b >DateType</b > </td >
1271
+ <td > java.sql.Date </td >
1272
+ <td >
1273
+ DateType
1274
+ </td >
1275
+ </tr >
1267
1276
<tr >
1268
1277
<td > <b >ArrayType</b > </td >
1269
1278
<td > scala.collection.Seq </td >
@@ -1390,6 +1399,13 @@ please use factory methods provided in
1390
1399
DataType.TimestampType
1391
1400
</td >
1392
1401
</tr >
1402
+ <tr >
1403
+ <td > <b >DateType</b > </td >
1404
+ <td > java.sql.Date </td >
1405
+ <td >
1406
+ DataType.DateType
1407
+ </td >
1408
+ </tr >
1393
1409
<tr >
1394
1410
<td > <b >ArrayType</b > </td >
1395
1411
<td > java.util.List </td >
@@ -1537,6 +1553,13 @@ from pyspark.sql import *
1537
1553
TimestampType()
1538
1554
</td >
1539
1555
</tr >
1556
+ <tr >
1557
+ <td > <b >DateType</b > </td >
1558
+ <td > datetime.date </td >
1559
+ <td >
1560
+ DateType()
1561
+ </td >
1562
+ </tr >
1540
1563
<tr >
1541
1564
<td > <b >ArrayType</b > </td >
1542
1565
<td > list, tuple, or array </td >
0 commit comments