sparksession创建DataFrame方式

spark创建dataFrame方式有很多种，官方API也比较多

公司业务上的个别场景使用了下面两种方式

1.通过List创建dataFrame

  /**
   * Applies a schema to a List of Java Beans.
   *
   * WARNING: Since there is no guaranteed ordering for fields in a Java Bean,
   *          SELECT * queries will return the columns in an undefined order.
   * @since 1.6.0
   */
  def createDataFrame(data: java.util.List[_], beanClass: Class[_]): DataFrame = {
    val attrSeq = getSchema(beanClass)
    val rows = SQLContext.beansToRows(data.asScala.iterator, beanClass, attrSeq)
    Dataset.ofRows(self, LocalRelation(attrSeq, rows.toSeq))
  }

2. 通过JavaRDD创建dataFrame

  /**
   * Applies a schema to an RDD of Java Beans.
   *
   * WARNING: Since there is no guaranteed ordering for fields in a Java Bean,
   * SELECT * queries will return the columns in an undefined order.
   *
   * @since 2.0.0
   */
  def createDataFrame(rdd: JavaRDD[_], beanClass: Class[_]): DataFrame = {
    createDataFrame(rdd.rdd, beanClass)
  }

　　

方式1样例代码：

ArrayList<GciGri> list = new ArrayList<GciGri>();
    GciGri g = new GciGri();
    g.setGci((gci));
    g.setGri((gri));
    list.add(g);

spark.createDataFrame(list, GciGri.class).createOrReplaceTempView("testtesttest");

　　

package cn.com.dtmobile.test;

import java.io.Serializable;

public class GciGri implements Serializable {

	private static final long serialVersionUID = 1L;

    private int Gci;
    private int Gri;

	public int getGci() {
		return Gci;
	}
	public void setGci(int gci) {
		Gci = gci;
	}
	public int getGri() {
		return Gri;
	}
	public void setGri(int gri) {
		Gri = gri;
	}

}

方式2跟方式1差不多一样，就不贴demo了