数据源Parquet之使用编程方式加载数据

/**
* Parquet数据源之使用编程方式加载数据
* @author Administrator
*
*/
public class ParquetLoadData {

​public static void main(String[] args) {
​​SparkConf conf = new SparkConf()​​​​.setAppName("ParquetLoadData");  
​​JavaSparkContext sc = new JavaSparkContext(conf);
​​SQLContext sqlContext = new SQLContext(sc);
// 读取Parquet文件中的数据，创建一个DataFrame
​​DataFrame usersDF = sqlContext.read().parquet(​​​​"hdfs://spark1:9000/spark-study/users.parquet");
​​// 将DataFrame注册为临时表，然后使用SQL查询需要的数据
​​usersDF.registerTempTable("users");  
​​DataFrame userNamesDF = sqlContext.sql("select name from users");  
// 对查询出来的DataFrame进行transformation操作，处理数据，然后打印出来
List<String> userNames = userNamesDF.javaRDD().map(new Function<Row, String>() {

​​​private static final long serialVersionUID = 1L;

​​​@Override
​​​public String call(Row row) throws Exception {
​​​​return "Name: " + row.getString(0);
​​​}
​​}).collect();

for(String userName : userNames) {
​​​System.out.println(userName);  
​​}
​}
}

import org.apache.spark.sql.SQLContext
import org.apache.spark.SparkConf
import org.apache.spark.SparkContext

class ParquetLoadData {  
def main(args: Array[String]): Unit = {
val conf = new SparkConf().setAppName("ParquetLoadData")  
val sc = new SparkContext(conf)
val sqlContext = new SQLContext(sc)
val usersDF = sqlContext.read.parquet("hdfs://spark1:9000/spark-study/users.parquet") 
usersDF.registerTempTable("users")
val userNamesDF = sqlContext.sql("select name from users")  
userNamesDF.rdd.map { row => "Name: " + row(0) }.collect()
   .foreach { userName => println(userName) }  
}
}