标签：[] ret gty from hive var turn blog nbsp
读一张表，对其进行二值化特征转换。可以二值化要求输入类型必须double类型，类型怎么转换呢？
直接利用spark column 就可以进行转换：
DataFrame dataset = hive.sql("select age,sex,race from hive_race_sex_bucktizer ");
/**
* 类型转换
*/
dataset = dataset.select(dataset.col("age").cast(DoubleType).as("age"),dataset.col("sex"),dataset.col("race"));
是不是很简单。想起之前的类型转换做法，遍历并创建另外一个满足类型要求的RDD，然后根据RDD创建Datafame，好复杂！！！！
JavaRDD<Row> parseDataset = dataset.toJavaRDD().map(new Function<Row,Row>() {
@Override
public Row call(Row row) throws Exception {
System.out.println(row);
long age = row.getLong(row.fieldIndex("age"));
String sex = row.getAs("sex");
String race =row.getAs("race");
double raceV = -1;
if("white".equalsIgnoreCase(race)){
raceV = 1;
} else if("black".equalsIgnoreCase(race)) {
raceV = 2;
} else if("yellow".equalsIgnoreCase(race)) {
raceV = 3;
} else if("Asian-Pac-Islander".equalsIgnoreCase(race)) {
raceV = 4;
}else if("Amer-Indian-Eskimo".equalsIgnoreCase(race)) {
raceV = 3;
}else {
raceV = 0;
}
return RowFactory.create(age,("male".equalsIgnoreCase(sex)?1:0),raceV);
}
});
StructType schema = new StructType(new StructField[]{
createStructField("_age", LongType, false),
createStructField("_sex", IntegerType, false),
createStructField("_race", DoubleType, false)
});
DataFrame df = hive.createDataFrame(parseDataset, schema);
不断探索，不断尝试！
标签：[] ret gty from hive var turn blog nbsp
原文地址：http://www.cnblogs.com/likehua/p/6203520.html
