Apache spark with akka couchbase code example

1. Bhawani Nandan Prasad – Bhawani_nandan@yahoo.com 0091 – 9717570222 (India)
Hadoop Technology Stack SME - Using Spark , Spray and Couchbase for lightening fast REST Api
1
Apache Spark™ is a fast and general engine for large-scale data processing, and Couchbase is
in-memory no-sql database. So by connecting these two we can get a lightening fast speed.
In this blog we are focusing on how to make CRUD operations on couchbase
with Spark’s speed.
I am assuming that you have a basic Spark’s installation and couchbase installation on your
system.
So for using Couchbase API’s with RDD’s we need to make a build.sbt file and add this line to
it.
"com.couchbase.client" %% "spark-connector" % "1.1.0"
So basically your build.sbt should look like.
name := "spark-spray-couchbase-example1"
version := "1.0"
scalaVersion := "2.10.4"
organization := "com.MoonLightIT"
libraryDependencies ++= Seq(
"org.apache.spark" %% "spark-core" % "1.4.1",
"io.spray" %% "spray-can" % "1.3.3",
"io.spray" %% "spray-routing" % "1.3.3",
"org.apache.spark" %% "spark-sql" % "1.4.1",
"io.spray" %% "spray-testkit" % "1.3.3",
"org.specs2" %% "specs2" % "2.4.7",
"com.couchbase.client" %% "spark-connector" % "1.1.0"
)
assembleArtifact in packageScala := false // We don't need the Scala library,
Spark already includes it

2. Bhawani Nandan Prasad – Bhawani_nandan@yahoo.com 0091 – 9717570222 (India)
Hadoop Technology Stack SME - Using Spark , Spray and Couchbase for lightening fast REST Api
2
mergeStrategy in assembly := {
case m if m.toLowerCase.endsWith("manifest.mf") => MergeStrategy.discard
case m if m.toLowerCase.matches("meta-inf.*.sf$") => MergeStrategy.discard
case "reference.conf" => MergeStrategy.concat
case _ => MergeStrategy.first
}
fork in run := true
Now you can access the Couchbase’s API’s for RDD’s in your code.
So now the next part is making building a service and binding it to the port.
package com.MoonLightIT.sprayservices
import akka.actor.{ActorSystem, Props}
import akka.io.IO
import spray.can.Http
import scala.concurrent.duration.DurationInt
object StartSpark extends App {
// we need an ActorSystem to host our application in
implicit val actorSystem = ActorSystem("spark-services")
implicit val timeout = 30 seconds
// create and start our service actor
val service = actorSystem.actorOf(Props[SparkServices], "spark-services")
// start a new HTTP server on port 8080 with our service actor as the handler
IO(Http) ! Http.Bind(service, "0.0.0.0", port = 8080)
}
Here we are just using the spray server for building the REST Api and binding it to
the 8080 port.

3. Bhawani Nandan Prasad – Bhawani_nandan@yahoo.com 0091 – 9717570222 (India)
Hadoop Technology Stack SME - Using Spark , Spray and Couchbase for lightening fast REST Api
3
Now comes the main part of implementing the couchbase CRUD operation using Spark and
spray. So for performing this we need to set the spark conf so that it may know where to insert
the data.
val sparkConf: SparkConf = new SparkConf().setAppName("couchbase-
spark-spray-starter-kit").setMaster("local")
.set("com.couchbase.nodes",
"127.0.0.1").set("com.couchbase.bucket.userBucket", "")
val sc: SparkContext = new SparkContext(sparkConf)
Here we are giving the node 127.0.0.1 and the bucket name here is userBucket. Using this
configuration we are making the Spark Context(sc).
Now we are going to implement the CRUD operations using the Couchbase’s API for RDD’s.
</pre>
<pre>package com.MoonLightIT.sprayservices
import java.util.UUID
import akka.actor.{Actor, ActorContext}
import com.couchbase.client.java.document.JsonDocument
import com.couchbase.client.java.document.json.JsonObject
import com.couchbase.client.java.query.N1qlQuery
import com.couchbase.client.java.view.ViewQuery
import com.couchbase.spark._
import org.apache.spark.{SparkConf, SparkContext}
import spray.http.StatusCodes._
import spray.http._
import spray.routing.Directive.pimpApply
import spray.routing.HttpService
import scala.util.Try

4. Bhawani Nandan Prasad – Bhawani_nandan@yahoo.com 0091 – 9717570222 (India)
Hadoop Technology Stack SME - Using Spark , Spray and Couchbase for lightening fast REST Api
4
trait SparkService extends HttpService {
val sparkConf: SparkConf = new SparkConf().setAppName("spark-spray-
starter").setMaster("local")
.set("com.couchbase.nodes",
"127.0.0.1").set("com.couchbase.bucket.userBucket", "")
val sc: SparkContext = new SparkContext(sparkConf)
val sparkRoutes =
path("insert" / "name" / Segment / "email" / Segment) { (name: String,
email: String) =>
get {
complete {
val documentId = "user::" + UUID.randomUUID().toString
val jsonObject = JsonObject.create().put("name", name).put("email",
email)
val jsonDocument = JsonDocument.create(documentId, jsonObject)
val savedData = sc.parallelize(Seq(jsonDocument))
val issaved =
Try(savedData.saveToCouchbase()).toOption.fold(false)(x => true)
issaved match {
case true => HttpResponse(OK, s"Data is successfully persisted
with id $documentId")
case false => HttpResponse(InternalServerError, s"Data is not
persisted and something went wrong")
}
}
}
} ~
path("updateViaKV" / "name" / Segment / "email" / Segment / "id" /
Segment) { (name: String, email: String, id: String) =>
get {
complete {
val documentId = id
val jsonObject = JsonObject.create().put("name",
name).put("email", email)
val jsonDocument = JsonDocument.create(documentId, jsonObject)
val savedData = sc.parallelize(Seq(jsonDocument))
val issaved =
Try(savedData.saveToCouchbase()).toOption.fold(false)(x => true)
issaved match {

5. Bhawani Nandan Prasad – Bhawani_nandan@yahoo.com 0091 – 9717570222 (India)
Hadoop Technology Stack SME - Using Spark , Spray and Couchbase for lightening fast REST Api
5
case true => HttpResponse(OK, s"Data is successfully persisted
with id $documentId")
case false => HttpResponse(InternalServerError, s"Data is not
persisted and something went wrong")
}
}
}
} ~
path("getViaKV" / "id" / Segment) { (id: String) =>
get {
complete {
val idAsRDD = sc.parallelize(Seq(id))
val fetchedDocument =
Try(idAsRDD.couchbaseGet[JsonDocument]().map(_.content.toString).collect).toO
ption
fetchedDocument match {
case Some(data) => HttpResponse(OK, data(0))
case None => HttpResponse(InternalServerError, s"Data is not
fetched and something went wrong")
}
}
}
} ~

6. Bhawani Nandan Prasad – Bhawani_nandan@yahoo.com 0091 – 9717570222 (India)
Hadoop Technology Stack SME - Using Spark , Spray and Couchbase for lightening fast REST Api
6
path("getViaView" / "name" / Segment) { (name: String) =>
get {
complete {
val viewRDDData = Try(sc.couchbaseView(ViewQuery.from("userDdoc",
"emailtoName").startKey(name)).collect()).toOption
val emailFetched = viewRDDData.map(_.map(a => a.value.toString))
emailFetched match {
case Some(data) => HttpResponse(OK, data(0))
case None => HttpResponse(InternalServerError, s"Data is not
fetched and something went wrong")
}
}
}
} ~
path("getViaN1Ql" / "name" / Segment) { (name: String) =>
get {
complete {
val n1qlRDD = Try(sc.couchbaseQuery(N1qlQuery.simple(s"SELECT *
FROM `userBucket` WHERE name LIKE '$name%'")).collect()).toOption
val emailFetched = n1qlRDD.map(_.map(a => a.value.toString))
emailFetched match {
case Some(data) => HttpResponse(OK, data(0))
case None => HttpResponse(InternalServerError, s"Data is not
fetched and something went wrong")
}
}
}
}
}

7. Bhawani Nandan Prasad – Bhawani_nandan@yahoo.com 0091 – 9717570222 (India)
Hadoop Technology Stack SME - Using Spark , Spray and Couchbase for lightening fast REST Api
7
class SparkServices extends Actor with SparkService {
def actorRefFactory: ActorContext = context
def receive: Actor.Receive = runRoute(sparkRoutes)
}</pre>
<pre>
The methods saveToCouchbase(), couchbaseGet(), couchbaseView(),couchbaseQuery() are
provided by couchbase so that we can perform the functionality on RDD’s .
This is a basic implementation of how to perform CRUD operation on couchbase using the
Spark.
We can also use the power of N1QL in this too by using the SQLContext, and they are said to be
highly compatible too.