今天就跟大家聊聊有关Spark2.2.0中RDD转DataFrame的方式是什么，可能很多人都不太了解，为了让大家更加了解，小编给大家总结了以下内容，希望大家根据这篇文章可以有所收获。
Spark SQL如何将现有的RDDs转换为数据集。
方法：通过编程接口，该接口允许您构造一个模式，然后将其应用于现有的RDD。虽然此方法更详细，但它允许您在列及其类型直到运行时才知道时构造数据集。
数据准备studentData.txt
1001,20,zhangsan1002,17,lisi1003,24,wangwu1004,16,zhaogang
代码实例：
package com.unicom.ljs.spark220.study;import org.apache.spark.SparkConf;import org.apache.spark.SparkContext;import org.apache.spark.api.java.JavaRDD;import org.apache.spark.api.java.JavaSparkContext;import org.apache.spark.api.java.function.Function;import org.apache.spark.rdd.RDD;import org.apache.spark.sql.*;import org.apache.spark.sql.types.*;import java.util.ArrayList;import java.util.List;/*** @author: Created By lujisen* @company ChinaUnicom Software JiNan* @date: 2020-01-21 13:42* @version: v1.0* @description: com.unicom.ljs.spark220.study*/public class RDD2DataFrameProgramatically {public static void main(String[] args) {SparkConf sparkConf = new SparkConf().setMaster("local[*]").setAppName("RDD2DataFrameProgramatically");JavaSparkContext sc = new JavaSparkContext(sparkConf);SQLContext sqlContext = new SQLContext(sc);JavaRDD<String> lineRDD =sc.textFile("C://Users//Administrator//Desktop//studentData.txt");JavaRDD<Row> rowJavaRDD = lineRDD.map(new Function<String, Row>() {@Overridepublic Row call(String line) throws Exception {String[] splitLine = line.split(",");return RowFactory.create(Integer.valueOf(splitLine[0]),Integer.valueOf(splitLine[1]),splitLine[2]);}});List<StructField> structFields=new ArrayList<StructField>();/*StructField structField1=new StructField("id", DataTypes.IntegerType,true);*/structFields.add(DataTypes.createStructField("id",DataTypes.IntegerType,true));structFields.add(DataTypes.createStructField("age",DataTypes.IntegerType,true));structFields.add(DataTypes.createStructField("name",DataTypes.StringType,true));StructType structType=DataTypes.createStructType(structFields);Dataset<Row> dataFrame = sqlContext.createDataFrame(rowJavaRDD, structType);dataFrame.registerTempTable("studentInfo");Dataset<Row> resultDataSet = sqlContext.sql("select * from studentInfo where age > 17");List<Row> collect = resultDataSet.javaRDD().collect();for(Row row: collect){System.out.println(row);}sc.close();}}
pom.xml关键依赖：
<spark.version>2.2.0</spark.version>
<scala.version>2.11.8</scala.version><dependency> <groupId>org.apache.spark</groupId> <artifactId>spark-sql_2.11</artifactId> <version>${spark.version}</version></dependency><dependency> <groupId>org.apache.spark</groupId> <artifactId>spark-core_2.11</artifactId> <version>${spark.version}</version></dependency>
看完上述内容，你们对Spark2.2.0中RDD转DataFrame的方式是什么有进一步的了解吗？如果还想了解更多知识或者相关内容，请关注亿速云行业资讯频道，感谢大家的支持。
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