spark整合elasticsearch两种方式

1.自己生成_id等元数据
2.使用ES默认生成

引入对应依赖

<dependency><groupId>org.elasticsearch</groupId><artifactId>elasticsearch-spark-13_2.10</artifactId><version>5.0.1</version>
</dependency>

生成元数据方式

import org.apache.spark.{SparkConf, SparkContext}
import org.elasticsearch.spark._
import utils.PropertiesUtilsimport scala.collection.immutable
import scala.collection.mutable.ListBuffer
object Spark_ES_WithMeta {val buffer = new ListBuffer[Tuple2[String,immutable.Map[String,String]]]def main(args: Array[String]): Unit = {val conf = new SparkConf().setAppName("Custmer_Statistics").setMaster("local[2]")conf.set("es.nodes","rmhadoop01,rmhadoop02,rmhadoop03");conf.set("es.port","9200");conf.set("es.index.auto.create", "true");val sc = new SparkContext(conf)//读取本地文件val result = sc.textFile("C:/work/ideabench/SparkSQL/data/es/gd_py_corp_sharehd_info.txt").map(_.split("\\t")).foreach(d =>{if(PropertiesUtils.getStringByKey("gd_py_corp_sharehd_info").equals("one2many")){val map = Map("id"->d(0),"batch_seq_num"->d(1),"name"->d(2),"contributiveFund"->d(3),"contributivePercent"->d(4),"currency"->d(5),"contributiveDate"->d(6),"corp_basic_info_id"->d(7),"query_time"->d(8))buffer.append((d(0),map))//buffer}else if(PropertiesUtils.getStringByKey("gd_py_corp_sharehd_info").equals("one2one")){//Map(d(1) ->gd_py_corp_sharehd_info(d(0), d(1), d(2), d(3), d(4), d(5), d(6), d(7), d(8)))}} )sc.makeRDD(buffer).saveToEsWithMeta("spark/guofei_gd_py_corp_sharehd_info")}/*** 使用模板类描述表元数据信息**/case class gd_py_corp_sharehd_info(id:String,batch_seq_num:String,name:String,contributiveFund:String,contributivePercent:String,currency:String,contributiveDate:String,corp_basic_info_id:String,query_time:String)}

ES-UI界面

ES.png

使用ES默认元数据方式

import org.apache.spark.sql.SQLContext
import org.apache.spark.{SparkConf, SparkContext}
import org.elasticsearch.spark.sql._
object SparkSQL_ES {/*** 使用模板类描述表元数据信息* */case class gd_py_corp_sharehd_info(id:String,batch_seq_num:String,name:String,contributiveFund:String,contributivePercent:String,currency:String,contributiveDate:String,corp_basic_info_id:String,query_time:String)def main(args: Array[String]): Unit = {val conf = new SparkConf().setAppName("Custmer_Statistics").setMaster("local[2]")conf.set("es.nodes","192.168.20.128");conf.set("es.port","9200");conf.set("es.index.auto.create", "true");val sc = new SparkContext(conf)val sqlContext = new SQLContext(sc)//RDD隐式转换成DataFrameimport sqlContext.implicits._//读取本地文件val gd_py_corp_sharehd_infoDF = sc.textFile("C:/work/ideabench/SparkSQL/data/es/gd_py_corp_sharehd_info.txt").map(_.split("\\t")).map(d => gd_py_corp_sharehd_info(d(0), d(1), d(2), d(3), d(4), d(5), d(6), d(7), d(8))).toDF()//注册表gd_py_corp_sharehd_infoDF.registerTempTable("gd_py_corp_sharehd_info")/*** */val result = sqlContext.sql("select * from gd_py_corp_sharehd_info limit 10").toDF()result.saveToEs("spark/gd_py_corp_sharehd_info")}}

参考文章

官网：https://www.elastic.co/guide/en/elasticsearch/hadoop/current/spark.html

作者：MichaelFly
链接：https://www.jianshu.com/p/a5c669d0ceba
來源：简书
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