spark对elasticsearch增删查改

时间:2023-03-10 04:57:31
spark对elasticsearch增删查改

新建一个 dataframe ,插入到索引 _index/_type ,直接调用 saveToEs ,让 _id 为自己设定的 id

import org.elasticsearch.spark.sql._
def main(args: Array[String]): Unit = { val spark = getSparkSession()
val dataFrame = spark.createDataFrame(Seq(
(1, 1, "2", "5"),
(2, 2, "3", "6"),
(3, 2, "36", "69")
)).toDF("id", "label", "col1", "col2")
dataFrame.saveToEs("_index/_type",Map("es.mapping.id" -> "id"))
} //配置spark
def getSparkSession(): SparkSession = {
val masterUrl = "local"
val appName = "ttyb"
val sparkconf = new SparkConf()
.setMaster(masterUrl)
.setAppName(appName)
.set("es.nodes", "es的IP")
.set("es.port", "9200")
val Spark = SparkSession.builder().config(sparkconf).getOrCreate()
Spark
}

目前 spark 没有开放删除的 API ,所以删除只能用命令行:

curl -XDELETE 'http://es的IP:9200/_index/_type/_id'

根据时间范围查询,其中 query 可以为空,代表不以任何查询条件查询:

val startTime = "1519660800000"
val endTime = "1519747200000"
val query = "{\"query\":{\"range\":{\"recordtime\":{\"gte\":" + startTime + ",\"lte\":" + endTime + "}}}}"
val tableName = "_index/_type"
val botResultData = spark.esDF(tableName, query)

例如需要将 id=3col1 改成 4col2 改成 7,可以新建一个 dataframe ,按照 id 储存,这样 elasticsearch 就会自动覆盖相同 id 下的数据:

val dataFrame1 = spark.createDataFrame(Seq(
(3, 2, "4", "7")
)).toDF("id", "label", "col1", "col2")
dataFrame1.saveToEs("_index/_type",Map("es.mapping.id" -> "id"))