Well the answers you got there are correct as well. Unfortunately I am not familiar with Neo4j enough to comment any more. Is the Neo4j graph database running externally (outside Spark cluster), or within the driver process, or on all the executors? Can you clarify that?
TD On Thu, Mar 12, 2015 at 12:58 AM, Gautam Bajaj <gautam1...@gmail.com> wrote: > Alright, I have also asked this question in StackOverflow: > http://stackoverflow.com/questions/28896898/using-neo4j-with-apache-spark > > The code there is pretty neat. > > On Thu, Mar 12, 2015 at 4:55 PM, Tathagata Das <t...@databricks.com> > wrote: > >> I am not sure if you realized but the code snipper it pretty mangled up >> in the email we received. It might be a good idea to put the code in >> pastebin or gist, much much easier for everyone to read. >> >> >> On Thu, Mar 12, 2015 at 12:48 AM, d34th4ck3r <gautam1...@gmail.com> >> wrote: >> >>> I'm trying to use Neo4j with Apache Spark Streaming but I am finding >>> serializability as an issue. >>> >>> Basically, I want Apache Spark to parse and bundle my data in real time. >>> After, the data has been bundled it should be stored in the database, >>> Neo4j. >>> However, I am getting this error: >>> >>> org.apache.spark.SparkException: Task not serializable >>> at >>> >>> org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:166) >>> at >>> org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:158) >>> at org.apache.spark.SparkContext.clean(SparkContext.scala:1264) >>> at >>> >>> org.apache.spark.api.java.JavaRDDLike$class.foreach(JavaRDDLike.scala:297) >>> at >>> org.apache.spark.api.java.JavaPairRDD.foreach(JavaPairRDD.scala:45) >>> at twoGrams.Main$4.call(Main.java:102) >>> at twoGrams.Main$4.call(Main.java:1) >>> at >>> >>> org.apache.spark.streaming.api.java.JavaDStreamLike$$anonfun$foreachRDD$2.apply(JavaDStreamLike.scala:282) >>> at >>> >>> org.apache.spark.streaming.api.java.JavaDStreamLike$$anonfun$foreachRDD$2.apply(JavaDStreamLike.scala:282) >>> at >>> >>> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:41) >>> at >>> >>> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:40) >>> at >>> >>> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:40) >>> at scala.util.Try$.apply(Try.scala:161) >>> at org.apache.spark.streaming.scheduler.Job.run(Job.scala:32) >>> at >>> >>> org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:172) >>> at >>> >>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) >>> at >>> >>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) >>> at java.lang.Thread.run(Thread.java:745) >>> Caused by: java.io.NotSerializableException: >>> org.neo4j.kernel.EmbeddedGraphDatabase >>> at >>> java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1183) >>> at >>> >>> java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1547) >>> at >>> java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1508) >>> at >>> >>> java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1431) >>> at >>> java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1177) >>> at >>> >>> java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1547) >>> at >>> java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1508) >>> at >>> >>> java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1431) >>> at >>> java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1177) >>> at >>> >>> java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1547) >>> at >>> java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1508) >>> at >>> >>> java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1431) >>> at >>> java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1177) >>> at >>> java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:347) >>> at >>> >>> org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:42) >>> at >>> >>> org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:73) >>> at >>> >>> org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:164) >>> ... 17 more >>> Here is my code: >>> >>> output a stream of type: JavaPairDStream<String, ArrayList<String>> >>> >>> output.foreachRDD( >>> new >>> Function2<JavaPairRDD<String,ArrayList<String>>,Time,Void>(){ >>> >>> @Override >>> public Void call( >>> JavaPairRDD<String, ArrayList<String>> >>> arg0, >>> Time arg1) throws Exception { >>> // TODO Auto-generated method stub >>> >>> arg0.foreach( >>> new >>> VoidFunction<Tuple2<String,ArrayList<String>>>(){ >>> >>> @Override >>> public void call( >>> Tuple2<String, >>> ArrayList<String>> arg0) >>> throws Exception { >>> // TODO Auto-generated method >>> stub >>> try( Transaction tx = >>> graphDB.beginTx()){ >>> >>> if(Neo4jOperations.getHMacFromValue(graphDB, arg0._1)!=null) >>> >>> System.out.println("Alread >>> in Database:" + arg0._1); >>> else{ >>> >>> Neo4jOperations.createHMac(graphDB, arg0._1); >>> } >>> tx.success(); >>> } >>> } >>> >>> }); >>> return null; >>> } >>> >>> >>> >>> }); >>> Neo4jOperations Class: >>> >>> public class Neo4jOperations{ >>> >>> public static Node getHMacFromValue(GraphDatabaseService graphDB,String >>> value){ >>> try(ResourceIterator<Node> >>> HMacs=graphDB.findNodesByLabelAndProperty(DynamicLabel.label("HMac"), >>> "value", value).iterator()){ >>> return HMacs.next(); >>> } >>> } >>> >>> public static void createHMac(GraphDatabaseService graphDB,String >>> value){ >>> Node HMac=graphDB.createNode(DynamicLabel.label("HMac")); >>> HMac.setProperty("value", value); >>> HMac.setProperty("time", new >>> >>> SimpleDateFormat("yyyyMMdd_HHmmss").format(Calendar.getInstance().getTime())); >>> } >>> } >>> I know that I have to Serialize the class Neo4jOperations, but I'm able >>> to >>> figure out how. Or is there any other way to achieve this? >>> >>> Also, how can I store output of Spark Streaming in a database ? >>> >>> >>> >>> >>> -- >>> View this message in context: >>> http://apache-spark-user-list.1001560.n3.nabble.com/Using-Neo4j-with-Apache-Spark-tp22012.html >>> Sent from the Apache Spark User List mailing list archive at Nabble.com. >>> >>> --------------------------------------------------------------------- >>> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >>> For additional commands, e-mail: user-h...@spark.apache.org >>> >>> >> > > > -- > Gautam >
