0
我试图使用MongoDB连接器的Hadoop与Spark查询MongoDB中的一个集合，并插入所有文件检索到另一个集合。 MongoUpdateWritable类用于RDD的值来更新MongoDB中的集合，并且它有一个upsert标志。不幸的是，upsert标志似乎对执行没有影响。代码正在执行，没有错误，就像upsert标志被设置为false一样。 （Scala）代码连接到本地主机mongod进程，使用mongo客户端写入一些数据，然后尝试读取该数据并使用spark将其写入同一数据库中的另一个集合。在写入没有完成之后，代码通过具有相同ID的mongo客户端将文档写入目标表，并运行相同的spark工作，以显示upsert的更新部分工作正常。mongo-hadoop包装upsert与火花似乎并没有工作
火花版本：1.6.0-cdh5.7.0
hadoop的版本：2.6.0-cdh5.4.7
蒙戈版本：3.2.0
蒙戈-的hadoop核版本：2.0 .2
import com.mongodb.client.{FindIterable, MongoCollection, MongoDatabase}
import com.mongodb.{BasicDBObject, DBCollection, MongoClient}
import com.mongodb.hadoop.io.MongoUpdateWritable
import org.apache.hadoop.conf.Configuration
import org.bson.{BSONObject, BasicBSONObject, Document}
import com.mongodb.hadoop.{MongoInputFormat, MongoOutputFormat}
import org.apache.spark.rdd.RDD
import org.apache.spark.{SparkConf, SparkContext}
object sparkTest extends App {
//setting up mongo
val mongo: MongoDatabase = new MongoClient("localhost",27017).getDatabase("test")
var source: MongoCollection[Document] = mongo.getCollection("source")
val target: MongoCollection[Document] = mongo.getCollection("target")
source.drop()
target.drop()
//inserting document
val sourceDoc = new Document()
sourceDoc.put("unchanged","this field should not be changed")
sourceDoc.put("_id","1")
source.insertOne(sourceDoc)
//setting up spark
val conf = new SparkConf().setAppName("test mongo with spark").setMaster("local")
val mongoConfig = new Configuration()
val sc = new SparkContext(conf)
mongoConfig.set("mongo.input.uri",
"mongodb://localhost:27017/test.source")
mongoConfig.set("mongo.output.uri",
"mongodb://localhost:27017/test.target")
//setting up read
val documents = sc.newAPIHadoopRDD(
mongoConfig, // Configuration
classOf[MongoInputFormat], // InputFormat
classOf[Object], // Key type
classOf[BSONObject]) // Value type
//building updates with no document matching the query in the target collection
val upsert_insert_rdd: RDD[(Object, MongoUpdateWritable)] = documents.mapValues(
(value: BSONObject) => {
val query = new BasicBSONObject
query.append("_id", value.get("_id").toString)
val update = new BasicBSONObject(value.asInstanceOf[BasicBSONObject])
update.append("added","this data will be added")
println("val:"+value.toString)
println("query:"+query.toString)
println("update:"+update.toString)
new MongoUpdateWritable(
query, // Query
update, // Update
true, // Upsert flag
false, // Update multiple documents flag
true // Replace flag
)}
)
//saving updates
upsert_insert_rdd.saveAsNewAPIHadoopFile(
"",
classOf[Object],
classOf[MongoUpdateWritable],
classOf[MongoOutputFormat[Object, MongoUpdateWritable]],
mongoConfig)
// At this point, there should be a new document in the target database, but there is not.
val count = target.count()
println("count after insert: "+count+", expected: 1")
//adding doc to display working update. This code will throw an exception if there is a
//document with a matching _id field in the collection, so if this breaks that means the upsert worked!
val targetDoc = new Document()
targetDoc.put("overwritten","this field should not be changed")
targetDoc.put("_id","1")
target.insertOne(targetDoc)
//building updates when a document matching the query exists in the target collection
val upsert_update_rdd: RDD[(Object, MongoUpdateWritable)] = documents.mapValues(
(value: BSONObject) => {
val query = new BasicBSONObject
query.append("_id", value.get("_id").toString)
val update = new BasicBSONObject(value.asInstanceOf[BasicBSONObject])
update.append("added","this data will be added")
println("val:"+value.toString)
println("query:"+query.toString)
println("update:"+update.toString)
new MongoUpdateWritable(
query, // Query
update, // Update
true, // Upsert flag
false, // Update multiple documents flag
true // Replace flag
)}
)
//saving updates
upsert_update_rdd.saveAsNewAPIHadoopFile(
"",
classOf[Object],
classOf[MongoUpdateWritable],
classOf[MongoOutputFormat[Object, MongoUpdateWritable]],
mongoConfig)
//checking that the update succeeded. should print:
//contains new field:true, contains overwritten field:false
val ret = target.find().first
if (ret != null)
println("contains new field:"+ret.containsKey("added")+", contains overwritten field:"+ret.containsKey("overwritten"))
else
println("no documents found in target")
}
任何洞察我所缺少的将有所帮助。我曾尝试将输出格式更改为MongoUpdateWritable，但这对行为没有影响。我知道这可能是一个配置问题，但它似乎是mongo hadoop适配器的一个bug，因为使用它们的输入和输出格式编写文档以及MongoUpdateWritable类可以成功读写文档。
POM为了方便：
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>test</groupId>
<artifactId>spark_mongo_upsert_test</artifactId>
<version>1.0-SNAPSHOT</version>
<properties>
<spark.version>1.6.0-cdh5.7.0</spark.version>
<mongo.version>3.2.0</mongo.version>
<mongo.hadoop.version>2.0.2</mongo.hadoop.version>
</properties>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.10</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.10</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.mongodb.mongo-hadoop</groupId>
<artifactId>mongo-hadoop-core</artifactId>
<version>2.0.2</version>
</dependency>
<dependency>
<groupId>org.mongodb.</groupId>
<artifactId>mongo-java-driver</artifactId>
<version>${mongo.version}</version>
</dependency>
</dependencies>
<build>
<plugins>
<!-- Plugin to compile Scala code -->
<plugin>
<groupId>net.alchim31.maven</groupId>
<artifactId>scala-maven-plugin</artifactId>
<version>3.2.1</version>
</plugin>
</plugins>
</build>
</project>