本文整理汇总了Java中org.apache.spark.sql.types.DataTypes.BinaryType方法的典型用法代码示例。如果您正苦于以下问题：Java DataTypes.BinaryType方法的具体用法？Java DataTypes.BinaryType怎么用？Java DataTypes.BinaryType使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类org.apache.spark.sql.types.DataTypes的用法示例。
在下文中一共展示了DataTypes.BinaryType方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: getDataTypeFromReturnType
import org.apache.spark.sql.types.DataTypes; //导入方法依赖的package包/类
private static DataType getDataTypeFromReturnType(Method method) {
String typeName = method.getReturnType().getSimpleName();
switch (typeName) {
case "int":
case "Integer":
return DataTypes.IntegerType;
case "long":
case "Long":
return DataTypes.LongType;
case "float":
case "Float":
return DataTypes.FloatType;
case "boolean":
case "Boolean":
return DataTypes.BooleanType;
case "double":
case "Double":
return DataTypes.DoubleType;
case "String":
return DataTypes.StringType;
case "Date":
case "date":
return DataTypes.DateType;
case "Timestamp":
return DataTypes.TimestampType;
case "short":
case "Short":
return DataTypes.ShortType;
case "Object":
return DataTypes.BinaryType;
default:
log.debug("Using default for type [{}]", typeName);
return DataTypes.BinaryType;
}
}
示例2: parseDataType
import org.apache.spark.sql.types.DataTypes; //导入方法依赖的package包/类
private static DataType parseDataType(Config fieldsConfig) {
String type = fieldsConfig.getString(FIELD_TYPE_CONFIG);
switch (type) {
case "string":
return DataTypes.StringType;
case "byte":
return DataTypes.ByteType;
case "short":
return DataTypes.ShortType;
case "int":
return DataTypes.IntegerType;
case "long":
return DataTypes.LongType;
case "float":
return DataTypes.FloatType;
case "double":
return DataTypes.DoubleType;
case "decimal":
ConfigUtils.assertConfig(fieldsConfig, DECIMAL_SCALE_CONFIG);
ConfigUtils.assertConfig(fieldsConfig, DECIMAL_PRECISION_CONFIG);
return DataTypes.createDecimalType(
fieldsConfig.getInt(DECIMAL_SCALE_CONFIG),
fieldsConfig.getInt(DECIMAL_PRECISION_CONFIG));
case "boolean":
return DataTypes.BooleanType;
case "binary":
return DataTypes.BinaryType;
case "date":
return DataTypes.DateType;
case "timestamp":
return DataTypes.TimestampType;
case "array":
case "map":
case "struct":
throw new RuntimeException("Schema check does not currently support complex types");
default:
throw new RuntimeException("Unknown type: " + type);
}
}
示例3: testToRowValueBinary
import org.apache.spark.sql.types.DataTypes; //导入方法依赖的package包/类
@Test
public void testToRowValueBinary() {
DataType field = DataTypes.BinaryType;
byte[] byteArray = "Test".getBytes();
ByteBuffer byteBuffer = ByteBuffer.wrap(byteArray);
assertEquals("Invalid byte[]", byteArray, RowUtils.toRowValue(byteArray, field));
assertEquals("Invalid ByteBuffer", byteArray, RowUtils.toRowValue(byteBuffer, field));
thrown.expect(RuntimeException.class);
RowUtils.toRowValue(123, field);
}