[英]how to Connect to NEO4J in Spark worker nodes?
我需要在火花映射函數中獲得一個小的子圖。 我曾嘗試使用AnormCypher和NEO4J-SPARK-CONNECTOR,但均無效。 AnormCypher將導致Java IOException錯誤(我在mapPartition函數中建立連接,在本地服務器上測試)。 而且Neo4j-spark-connector將導致下面的任務“不可序列化例外”。
是否有一種好方法可以在Spark worker節點中獲取子圖(或連接至圖數據庫,如neo4j)?
Exception in thread "main" org.apache.spark.SparkException: Task not serializable
at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:298)
at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:288)
at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:108)
at org.apache.spark.SparkContext.clean(SparkContext.scala:2094)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1.apply(RDD.scala:793)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1.apply(RDD.scala:792)
at ....
我的代碼段使用neo4j-spark-connector 2.0.0-m2:
val neo = Neo4j(sc) // this runs on the driver
// this runs by a map function
def someFunctionToBeMapped(p: List[Long]) = {
val metaGraph = neo.cypher("match p = (a:TourPlace) -[r:could_go_to] -> (b:TourPlace)" +
"return a.id ,r.distance, b.id").loadRowRdd.map( row => ((row(0).asInstanceOf[Long],row(2).asInstanceOf[Long]), row(1).asInstanceOf[Double]) ).collect().toList
AnromCypher代碼為:
def partitionMap(partition: Iterator[List[Long]]) = {
import org.anormcypher._
import play.api.libs.ws._
// Provide an instance of WSClient
val wsclient = ning.NingWSClient()
// Setup the Rest Client
// Need to add the Neo4jConnection type annotation so that the default
// Neo4jConnection -> Neo4jTransaction conversion is in the implicit scope
implicit val connection: Neo4jConnection = Neo4jREST("127.0.0.1", 7474, "neo4j", "000000")(wsclient)
//
// Provide an ExecutionContext
implicit val ec = scala.concurrent.ExecutionContext.global
val res = partition.filter( placeList => {
val startPlace = Cypher("match p = (a:TourPlace) -[r:could_go_to] -> (b:TourPlace)" +
"return p")().flatMap( row => row.data )
})
wsclient.close()
res
}
我已使用Spark獨立模式並能夠連接neo4j數據庫
使用的版本:
火花2.1.0
neo4j-spark-connector 2.1.0-m2
我的代碼:-
val sparkConf = new SparkConf().setAppName("Neo$j").setMaster("local")
val sc = new SparkContext(sparkConf)
println("***Getting Started ****")
val neo = Neo4j(sc)
val rdd = neo.cypher("MATCH (n) RETURN id(n) as id").loadDataFrame
println(rdd.count)
Spark提交:-spark-submit --class package.classname --jars pathofneo4jsparkconnectoryJAR --conf spark.neo4j.bolt.password = ***** targetJarFile.jar
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