diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md index 729045b81a8c0851fa36a042d477f843ba7113c4..be8c5c2c1522e6a324174b2834c4bfb96ddec378 100644 --- a/docs/sql-programming-guide.md +++ b/docs/sql-programming-guide.md @@ -1333,9 +1333,9 @@ import org.apache.spark.sql._ <div data-lang="java" markdown="1"> All data types of Spark SQL are located in the package of -`org.apache.spark.sql.api.java`. To access or create a data type, +`org.apache.spark.sql.types`. To access or create a data type, please use factory methods provided in -`org.apache.spark.sql.api.java.DataType`. +`org.apache.spark.sql.types.DataTypes`. <table class="table"> <tr> @@ -1346,109 +1346,110 @@ please use factory methods provided in <td> <b>ByteType</b> </td> <td> byte or Byte </td> <td> - DataType.ByteType + DataTypes.ByteType </td> </tr> <tr> <td> <b>ShortType</b> </td> <td> short or Short </td> <td> - DataType.ShortType + DataTypes.ShortType </td> </tr> <tr> <td> <b>IntegerType</b> </td> <td> int or Integer </td> <td> - DataType.IntegerType + DataTypes.IntegerType </td> </tr> <tr> <td> <b>LongType</b> </td> <td> long or Long </td> <td> - DataType.LongType + DataTypes.LongType </td> </tr> <tr> <td> <b>FloatType</b> </td> <td> float or Float </td> <td> - DataType.FloatType + DataTypes.FloatType </td> </tr> <tr> <td> <b>DoubleType</b> </td> <td> double or Double </td> <td> - DataType.DoubleType + DataTypes.DoubleType </td> </tr> <tr> <td> <b>DecimalType</b> </td> <td> java.math.BigDecimal </td> <td> - DataType.DecimalType + DataTypes.createDecimalType()<br /> + DataTypes.createDecimalType(<i>precision</i>, <i>scale</i>). </td> </tr> <tr> <td> <b>StringType</b> </td> <td> String </td> <td> - DataType.StringType + DataTypes.StringType </td> </tr> <tr> <td> <b>BinaryType</b> </td> <td> byte[] </td> <td> - DataType.BinaryType + DataTypes.BinaryType </td> </tr> <tr> <td> <b>BooleanType</b> </td> <td> boolean or Boolean </td> <td> - DataType.BooleanType + DataTypes.BooleanType </td> </tr> <tr> <td> <b>TimestampType</b> </td> <td> java.sql.Timestamp </td> <td> - DataType.TimestampType + DataTypes.TimestampType </td> </tr> <tr> <td> <b>DateType</b> </td> <td> java.sql.Date </td> <td> - DataType.DateType + DataTypes.DateType </td> </tr> <tr> <td> <b>ArrayType</b> </td> <td> java.util.List </td> <td> - DataType.createArrayType(<i>elementType</i>)<br /> + DataTypes.createArrayType(<i>elementType</i>)<br /> <b>Note:</b> The value of <i>containsNull</i> will be <i>true</i><br /> - DataType.createArrayType(<i>elementType</i>, <i>containsNull</i>). + DataTypes.createArrayType(<i>elementType</i>, <i>containsNull</i>). </td> </tr> <tr> <td> <b>MapType</b> </td> <td> java.util.Map </td> <td> - DataType.createMapType(<i>keyType</i>, <i>valueType</i>)<br /> + DataTypes.createMapType(<i>keyType</i>, <i>valueType</i>)<br /> <b>Note:</b> The value of <i>valueContainsNull</i> will be <i>true</i>.<br /> - DataType.createMapType(<i>keyType</i>, <i>valueType</i>, <i>valueContainsNull</i>)<br /> + DataTypes.createMapType(<i>keyType</i>, <i>valueType</i>, <i>valueContainsNull</i>)<br /> </td> </tr> <tr> <td> <b>StructType</b> </td> <td> org.apache.spark.sql.api.java.Row </td> <td> - DataType.createStructType(<i>fields</i>)<br /> + DataTypes.createStructType(<i>fields</i>)<br /> <b>Note:</b> <i>fields</i> is a List or an array of StructFields. Also, two fields with the same name are not allowed. </td> @@ -1458,7 +1459,7 @@ please use factory methods provided in <td> The value type in Java of the data type of this field (For example, int for a StructField with the data type IntegerType) </td> <td> - DataType.createStructField(<i>name</i>, <i>dataType</i>, <i>nullable</i>) + DataTypes.createStructField(<i>name</i>, <i>dataType</i>, <i>nullable</i>) </td> </tr> </table>