Spark解析JSON文件，写入hdfs

一、用Sparkcontext读入文件，map逐行用Gson解析，输出转成一个caseclass类，填充各字段，输出。

解析JSON这里没有什么问题。

RDD覆盖写的时候碰到了一些问题 ：

1.直接saveAsTextFile没有覆盖true参数；

2.转dataframe时，还得一个一个字段显化才能转成dataframe；

3.write时，一开始打算写text，说字段里不能含有long和int，换成string后，说不能有多个字段，只能有一个string。刚好用parquet存储省空间，就存parquet了。

跑通代码如下：

package XXX

import com.google.gson.JsonParser
import org.apache.spark.sql.SparkSession
import schema.caseClass1

object ParsecaseClass1Json {
  def main(args: Array[String]): Unit = {
    val inputPath = args(0)
    val outputPath = args(1)
    val sparkSession = SparkSession.builder().appName(this.getClass.getSimpleName).getOrCreate()
    import sparkSession.implicits._

    val lines = sparkSession.sparkContext.textFile(inputPath)
    val result = lines.map(=> parseJsonStr(str))

    val df = result.map(
      x => (
        x.adId
        , x.campaignId
        , x.settlementType
        , x.billingType
        , x.billingTypeCode
        , x.packageName
      ))
      .toDF()
    df.coalesce(1).write.format("parquet").mode("overwrite").save(outputPath)

  }

  def parseJsonStr(str: String): caseClass1 = {
      val inputJson = new JsonParser().parse(str).getAsJsonObject
      val object = new caseClass1

      //1.campaignId
      if (inputJson.has("campaign")) {
        val campaign = inputJson.getAsJsonObject("campaign")
        var campaignId: Long = 0
        if (campaign.has("id"))
          campaignId = campaign.getAsJsonPrimitive("id").getAsLong
        else if (campaign.has("campaignId")) {
          campaignId = campaign.getAsJsonPrimitive("campaignId").getAsLong
        }
        else {
          System.err.println("No campaignId, inputJson: {}", str)
        }
        object.campaignId = campaignId
      }

      //2.creativeId
      if (inputJson.has("creative")) {
        val creative = inputJson.getAsJsonObject("creative")
        var adId: Long = 0
        if (creative.has("id"))
          adId = creative.getAsJsonPrimitive("id").getAsLong
        else if (creative.has("creativeId"))
          adId = creative.getAsJsonPrimitive("creativeId").getAsLong
        else
          System.err.println("No adId, inputJson: {}", str)
        object.adId = adId

      }

      /*
      3.settlementType
      4.billingType
      5.billingTypeCode
      6.appId -> packageName
      */
      if (inputJson.has("group")) {
        val group = inputJson.getAsJsonObject("group")

        object.settlementType = group.getAsJsonPrimitive("settlementType").getAsString
        object.billingType = group.getAsJsonPrimitive("billingType").getAsString
        object.billingTypeCode = group.getAsJsonPrimitive("billingTypeCode").getAsInt
        object.packageName = group.getAsJsonPrimitive("appId").getAsString
      }
    System.err.println(object.toString)
    object
  }

}

caseClass如下

package XXX;

import java.io.Serializable;

public class caseClass1 implements Serializable {

    private static final long serialVersionUID = ***;

    public long adId = 0;
    public long campaignId = 0;
    public String settlementType;
    public String billingType;
    public Integer billingTypeCode;
    public String packageName;

    @Override
    public String toString() {
        return "caseClass1{" +
                "adId=" + adId +
                ", campaignId=" + campaignId +
                ", settlementType='" + settlementType + '\'' +
                ", billingType='" + billingType + '\'' +
                ", billingTypeCode=" + billingTypeCode +
                ", packageName='" + packageName + '\'' +
                '}';
    }
    public caseClass1() {

    }
}