Samar's Blog

Create ElasticSearch cluster on single machine

2015-10-23T13:44:00.000-07:00

I wanted to figure out how to create a multi-node ElasticSearch cluster on single machine. So i followed these instructions

First i did download elasticsearch zip file.
Create 3 folders in like node1, node2 and node3
Unzip elasticsearch.zip in each one of these folders and name the folder node1,node2,node3
Then i opened the node1/config/elasticsearch.yml and i did change value of cluster.name to samarcluster and value of node.name to node1,node2 and node 3 as shown below.

Typical setup done with 3 nodes on a single machine

node1:

cluster.name: samarcluster

node.name: "node1"

node.master: true

node.data: true

node2 :

cluster.name: samarcluster

node.name: "node2"

node.master: false

node.data: true

node3 :

cluster.name: samarcluster

node.name: "node3"

node.master: false

node.data: false

Next step was to install below Plugins

Marvel on each of the nodes by executing bin/plugin -i elasticsearch/marvel/latest

ElasticSearch-HQ on each of the nodes by executing bin/plugin -install royrusso/elasticsearch-HQ

Once all the 3 nodes are started, i could see them in marvel and elasticHQ as shown below.

Elastic Search MongoDB Integration

2015-10-08T20:13:00.000-07:00

Follow below steps to install elastic search, assuming mongoldb is already installed.

1)curl -O https://download.elasticsearch.org/elasticsearch/elasticsearch/elasticsearch-1.7.2.zip

2) export ES_HOME=/Users/samaraarkotti/Documents/elasticsearch-1.7.2

3) $ES_HOME/bin/plugin -install elasticsearch/elasticsearch-mapper-attachments/2.7.1 ( https://github.com/elastic/elasticsearch-mapper-attachments )

4) $ES_HOME/bin/plugin -install com.github.richardwilly98.elasticsearch/elasticsearch-river-mongodb/2.0.9 ( https://github.com/richardwilly98/elasticsearch-river-mongodb/ )

5) $ES_HOME/bin/plugin --install mobz/elasticsearch-head

6) $ES_HOME/bin/plugin -i elasticsearch/marvel/latest

7) start elastic search bin/elasticsearch

Optional Plugin to install

$ES_HOME/bin/plugin --install lukas-vlcek/bigdesk ( To access Inquisitor, open http://localhost:9200/_plugin/bigdesk)

$ES_HOME/bin/plugin -install polyfractal/elasticsearch-inquisitor ( To access Inquisitor, open http://localhost:9200/_plugin/inquisitor/ )

curl -XPUT 'http://localhost:9200/_river/mongodb/_meta' -d '{"type": "mongodb","mongodb": {"db": "analytics","collection": "Article"},"index": {"name": "articleindex","type": "article"}}'

curl -XPUT 'http://localhost:9200/_river/mongodb/_meta' -d '{"type": "mongodb","mongodb": {"db": "analytics","collection": "ViewsAndRatingDetails"},"index": {"name": "viewindex","type": "views"}}'

-- DELETE Plugins using curl or directly on web both articleindex and _river , once done , run above curl command to index again .

curl -XDELETE 'http://localhost:9200/_river/mongodb'

curl -XDELETE 'http://localhost:9200/articleindex'

Reference

http://localhost:9200/_plugin/river-mongodb/

http://localhost:9200/_plugin/head/

http://localhost:9200/_plugin/marvel/sense/index.html

http://localhost:9200/_plugin/calaca/

https://www.elastic.co/guide/en/elasticsearch/reference/1.4/modules-plugins.html

--- if getting any error's converting your standalone mongodb to replicaset , follow below steps

1)start the server in your usual way (single instance)

2)connect to the instance with a similar command : ./mongo --port 27017

3)look at your databases : show dbs

4)if there is a db called local, connect to it: use local

drop that database : db.dropDatabase()

--- if you are getting error saying _mongodb RIVER FAILED to start ,

1) Then delete the _river plugin ( curl -XDELETE 'http://localhost:9200/_river/mongodb' )

2) shutdown ES and restart

-- disable dynamic mapping -- NOT WORKING

curl -XDELETE localhost:9200/articleindex --- First delete the index

curl -XPUT localhost:9200/articleindex -d '{"index.mapper.dynamic": false}'

--added below in elasticsearch.yml under config folder

you will also need to configure elastic search to accept requests from the browser using CORS ( cross origin site scripting). To enable CORS, add the following to elasticsearch's config file. Usually, this file is located near the elasticsearch at config/elasticsearch.yml

http.cors:

enabled: true

allow-origin: /https?:\/\/localhost(:[0-9]+)?/

ElasticSearch and Mongo through river – scalable data store and search engine platform

2015-04-16T13:32:00.003-07:00

1. MONGODB

MongoDB is an open-source document database with built in replication, high availability, auto-sharding and map/reduce mechanisms.Install MongoDB from

http://docs.mongodb.org/manual/tutorial/install-mongodb-on-os-x/

2. ELASTICSEARCH

Elastic search is a powerful open source, real-time search and analytics engine, designed from the ground up to be used in distributed environments with reliability and scalability as a must have. Looks great as a search engine.

Download Elastic Search from: https://www.elastic.co OR Use below command from terminal.

curl -O https://download.elasticsearch.org/elasticsearch/elasticsearch/elasticsearch-1.4.2.zip

Export ES_HOME=/Users/xxx/Downloads/elasticsearch-1.4.2

3. MONGODB RIVER PLUGIN FOR ES

Elastic search provides ability to enhance the basic functionality by plugins, which are easy to use and develop. They can be used for analysis, discovery, monitoring, data synchronization and many others. Rivers is a group of plugins used for data synchronization between database and elastic search

The first is a dependency called Mapper Attachments. You can install via the ES plugin script:

$ES_HOME/bin/plugin -install elasticsearch/elasticsearch-mapper-attachments/2.4.3

The second plugin is the ES 'river' for Mongo. The syntax to install it is slightly different as it's a third-party plugin:

$ES_HOME/bin/plugin -install com.github.richardwilly98.elasticsearch/elasticsearch-river-mongodb/2.0.9

Restart the server

sh elastic search restart

Elastic Search is on board and running – 3 minutes in my case. It’s recommended to use the second machine to avoid sharing resources, but for test deployments a single one is good enough.

Tell elastic search to index the “person” collection in testmongo database by issuing the following command in your terminal.

curl -XPUT 'http://localhost:9200/_river/mongodb/_meta' -d '{

"type": "mongodb",

"mongodb": {

"db": "testmongo",

"collection": "person"

"index": {

"name": "mongoindex",

"type": "person"

}

We’ve got ElasticSearch automatically synchronizing data with MongoDB

2 minutes in my case.

4. Setup MONGODB As Replica Set.

MongoDB -- setting up replica set on the local host( Mac OS X)

mongod --port 27017 --dbpath /data/db --replSet rs0

rs.initiate() -- > this will initiate new replica set.

Create a Mongo Database: testmongo

Create a Mongo Collection under testmongo: person

5. Now finally start the Search.

Use this command to search the data from terminal or go to URL directly to see below response

curl -XGET 'http://localhost:9200/mongoindex/_search?q=firstName:John'

Response from Elastic Search :

{

"took": 42,

"timed_out": false,

"_shards": {

"total": 5,

"successful": 5,

"failed": 0

"hits": {

"total": 1,

"max_score": 1.4054651,

"hits": [

{

"_index": "mongoindex",

"_type": "person",

"_id": "552ee22d9f829d905d5f180f",

"_score": 1.4054651,

"_source": {

"lastName": "Doe",

"_id": "552ee22d9f829d905d5f180f",

"firstName": "John"

}

]

}

After inserting document in MongoDB configured as replica set, it is also stored in oplog collection.The mentioned collection is operations log configured as capped collection, which keeps a rolling record of all operations that modify the data stored in databases. River plugin monitors this collection and forwards new operations to elasticsearch according to its configuration. That means that all insert, update and delete operations are forwarded to elasticsearch automatically..

We can easily check what we have in ES using head plugin, which can be installed with the help of command:

./plugin -install mobz/elasticsearch-head

Some elasticsearch plugins provide web interface that can be reached using endpoint /_plugin:

http://localhost:9200/_plugin/river-mongodb/

http://localhost:9200/_plugin/head/

Summarizing, we have MongoDB configured as replica set, Elasticsearch with River that pulls data from database to index, and finally everything is prepared for sharding and replication.

Singleton Pattern

2015-04-14T23:09:00.001-07:00

Singleton Pattern in Java

Singleton Pattern ensures a class has only one instance and provides a global point of access to it.
The default constructor of the class is made private, which prevents the direct instantiation of the object by other classes.

A static modifier is applied to the instance method that returns the object as it then makes this method a class level method that can be accessed without creating an object.

public class BookingFactory {

  private static BookingFactory instance;

  // An instance attribute.

  private int data = 0;

  private BookingFactory() {

   //initiate any other attributes if needed.

}

  public static BookingFactory getInstance(){

   if(instance == null) 

       instance = new BookingFactory();

   return instance;

}

  public int getData() {

   return data;

}

  public void setData(int data) {

   this.data = data;

}

  // other methods....

}

In future if you get a requirement for having more than one instance then singleton allows multiple instances without affecting a singleton class's clients. Just you need to do is make a small change in Singleton Class, which doesn't effect the client's code.

Note that the singleton instance is only created when needed. This is called lazy instantiation.

public class SingletonDemo {

  public static void main(String args[]) {

  // Get a reference to the single instance of Singleton.

  BookingFactory bookingFactory = BookingFactory.getInstance();

  // Set the data value.

  bookingFactory.setData(34);

  System.out.println("First reference: " + bookingFactory);

  System.out.println("Singleton data value is: " +bookingFactory.getData());

}

}

How can we break Singleton:

1. It could happen that the access method may be called twice from 2 different classes at the same time and hence more than one object being created. This could violate the design patter principle.

Solution :

In order to prevent the simultaneous invocation of the getter method by 2 threads or classes simultaneously we add the synchronized keyword to the method declaration.

Make the Instance access method Synchronized to prevent concurrent thread access.

public static synchronized BookingFactory getInstance()

Synchronization is expensive, however, and is really only needed the first time the unique instance is created.

Do an eager instantiation of the instance rather than a lazy instantiation.

You can also instantiate the Singleton as soon as the class loads. i.e You can place it in static block to ensure that it happens only once.

public class BookingFactory {

  private static BookingFactory instance;

  // An instance attribute.

  private int data = 0;

  static {

   instance = new BookingFactory();

}

  private BookingFactory() {

   //initiate any other attributes if needed.

}

  public static BookingFactory getInstance()

{

   return instance;

}

  public int getData() {

   return data;

}

  public void setData(int data) {

   this.data = data;

}

  // other methods....

}

Instead of synchronizing the whole method you can also make the instance variable as static final. It is thread-safe because static member variables created when declared are guaranteed to be created the first time they are accessed. You get a thread-safe implementation that automatically employs lazy instantiation.

public class BookingFactory {

    private final static BookingFactory instance = new BookingFactory();

    private BookingFactory() {

          // Exists only to defeat instantiation.

}

}

But you loose the flexibility of having more than one instance in future without changing client's code.

2. if you are using multiple class-loaders this could defeat the Singleton implementation and result in multiple instances.

Solution:

Because multiple class-loaders are commonly used in many situations—including servlet containers—you can wind up with multiple singleton instances no matter how carefully you've implemented your singleton classes. If you want to make sure the same class-loader loads your singletons, you must specify the class-loader yourself; for example:

private static Class getClass(String classname) 

        throws ClassNotFoundException {

 ClassLoader classLoader = Thread.currentThread().getContextClassLoader();

 if(classLoader == null)

  classLoader = Singleton.class.getClassLoader();

 return (classLoader.loadClass(classname));

}

}

The preceding method tries to associate the classloader with the current thread; if that classloader is null, the method uses the same classloader that loaded a singleton base class. The preceding method can be used instead of Class.forName().

3. If SingletonClass implements the java.io.Serializable interface, the class's instances can be serialized and deserialized. However, if you serialize a singleton object and subsequently deserialize that object more than once, you will have multiple singleton instances.

Solution:

To avoid the above you need to implement readResolve() method.

private Object readResolve() {

    return INSTANCE;

}

The previous singleton implementation returns the lone singleton instance from the readResolve() method; therefore, whenever the Singleton class is deserialized, it will return the same singleton instance.

4. We will be able to create a copy of the Object by cloning it using the Object’s clone method.

Solution:

Override the Object clone method to prevent cloning, this can be done as shown below

SingletonDemo clonedObject = (SingletonDemo) obj.clone();

This again violates the Singleton Design Pattern’s objective. So to deal with this we need to override the Object’s clone method which throws a CloneNotSupportedException exception.

public Object clone() throws CloneNotSupportedException {

 throw new CloneNotSupportedException();

}

When to use:
We can use this while creating objects of thread pools, caches etc to avoid wasting resources.

Java Server Side Templating using Mustache.

2015-04-14T14:03:00.001-07:00

import java.util.ArrayList;

import java.util.HashMap;

import java.util.Iterator;

import java.util.List;

import java.util.Map;

import org.json.JSONArray;

import org.json.JSONException;

import org.json.JSONObject;

import com.samskivert.mustache.Mustache;

import com.samskivert.mustache.Template;

/**

 * Simple java server side templating

 * @author Samar Aarkotti

*

*/

public class Sample {

 public static void main(String[] args) {

  String template = "{\"products\": \"iPhone\"}";

  String text = "How do I get my {{products}} serviced?";

  Template tmpl = Mustache.compiler().compile(text);

  try {

   JSONObject jsonObj = new JSONObject(template);

   Map<String,Object> map = getTemplateFromJson(jsonObj);

   System.out.println(tmpl.execute(map));

  } catch (JSONException e) {

   e.printStackTrace();

}

}

 private static Map<String, Object> getTemplateFromJson(JSONObject json) throws JSONException {

     Map<String,Object> out = new HashMap<String,Object>();

     Iterator<?> it = json.keys(); 

     while (it.hasNext()) {

         String key = (String)it.next();

         if (json.get(key) instanceof JSONArray) {

             // Copy an array

             JSONArray arrayIn = json.getJSONArray(key);

             List<Object> arrayOut = new ArrayList<Object>();

             for (int i = 0; i < arrayIn.length(); i++) {

                 JSONObject item = (JSONObject)arrayIn.get(i);

                 Map<String, Object> items = getTemplateFromJson(item);

                 arrayOut.add(items);

}

             out.put(key, arrayOut);

}

         else {

             // Copy a primitive string

             out.put(key, json.getString(key));

}

}

     return out;

}

}

Expected Output : How do I get my iPhone serviced?

Restricts the contents of the documents based on information stored in the documents themselves.

2014-04-16T10:21:00.000-07:00

MongoDB 2.6 has an API that Restricts the contents of the documents based on information stored in the documents themselves.

Evaluates Access at Every Document/Sub-Document Level

A test collection contains documents of the following form where the tags field lists the different access values for that document/subdocument level; i.e. a value of [ “public", “internal" ] specifies either “public" or “internal" can access the data:

Sample Example JSON Document below

{

"_id" : 1,

"title" : "Document Formatting",

"tags" : [

"PUBLIC",

"SERVICE_PROVIDER",

"INTERNAL"

"year" : 2014,

"subsections" : [

{

"subtitle" : "Section 1: Overview",

"tags" : [

"PUBLIC",

"SERVICE_PROVIDER"

"content" : "Section 1: This is PUBLIC and SERVICE PROVIDER content of section 1."

{

"subtitle" : "Section 2: SuperScript",

"tags" : [

"SERVICE_PROVIDER"

"content" : "Section 2: This is SERVICE PROVIDER content of section 2."

{

"subtitle" : "Section 3: SubScript",

"tags" : [

"PUBLIC"

"content" : {

"text" : "Section 3: This is INTERNAL content of section3.",

"tags" : [

"INTERNAL"

]

}

]

}

A user has access to view information with either the tag “public" or “internal". To run a query on all documents with year 2014 for this user, include a $redact stage as in the following:

var userAccess = ["INTERNAL","PUBLIC"];

db.test.aggregate(

[

{ $match: { year: 2014 } },

{ $redact:

{

$cond:

{

if: { $gt: [ { $size: { $setIntersection: [ "$tags", userAccess ] } }, 0 ] },

then: "$$DESCEND",

else: "$$PRUNE"

}

]

)

The aggregation operation returns the following “redacted” document, which does not include SERVICE_PROVIDER subsection.

{

"result" : [

{

"_id" : 1,

"title" : "Document Formatting",

"tags" : [

"PUBLIC",

"SERVICE_PROVIDER",

"INTERNAL"

"year" : 2014,

"subsections" : [

{

"subtitle" : "Section 1: Overview",

"tags" : [

"PUBLIC",

"SERVICE_PROVIDER"

"content" : "Section 1: This is PUBLIC and SERVICE PROVIDER content of section 1."

{

"subtitle" : "Section 3: SubScript",

"tags" : [

"PUBLIC"

"content" : {

"text" : "Section 3: This is INTERNAL content of section3.",

"tags" : [

"INTERNAL"

]

}

]

}

"ok" : 1

}

Apache Mahout for Document Similarity.

2014-04-16T10:08:00.003-07:00

Using Apache Mahout for Document Similarity.

Below are steps to run on the text file collection.

sh mahout seqdirectory -c UTF-8 -i /Users/xxxx/myfiles/ -o seqfiles
sh mahout seq2sparse -i seqfiles/ -o vectors/ -ow -chunk 100 -x 90 -seq -ml 50 -n 2 -s 5 -md 5 -ng 3 -nv
sh mahout rowid -i vectors/tfidf-vectors/part-r-00000 -o matrix
sh mahout rowsimilarity -i matrix/matrix -o similarity --similarityClassname SIMILARITY_COSINE -m 10 -ess
sh mahout seqdumper -i similarity > similarity.txt
sh mahout seqdumper -i matrix/docIndex > docIndex.txt

Apache Mahout does following Steps

Tokenize and Transform
Generate word vectors and weights
Find Document similarity based on TF-IDF( Term Frequence - Inverted Document Frequency) using COSINE_SIMILARITY

Tokenization

The first step is to convert the text document into sequence of tokens. Content is tokenized based on single word. All the tokens are then transformed to lower cases so that the content is standardized.

Create N-Grams : A term n-Gram is defined as a series of consecutive tokens of length n. n-Gram consists of all series of consecutive tokens of length n.

Generate Vectors and Weights

Each document is converted to a word vector of n-Grams with weight assigned to each n-Gram. This weight is assigned based on TF-IDF (Term Frequency - Inverse Document Frequency), This is a measure of importance of a term in a document. it is measured by the frequency of the term in the document but is offset by the total frequency of the term in the whole document set. this creates a balance in weighing terms, as some terms can occur more commonly than other and can be less significant in arriving at similarity.

Document Similarity

Each Document word vector is compared to every other document’s vector. Document similarity is based on cosine similarity measure between the word vector’s. two vectors with the same orientation have a cosine similarity of 1 , two vectors at 90 have similarity of 0. A matrix similarity between each document with every other document is generated.

Sample docIndex.txt Below

Key: 0: Value: /File558

Key: 1: Value: /File4340

Key: 2: Value: /File4208

Key: 3: Value: /File471

Sample Similarity.txt Below

Key: 0: Value: {0:1.0000000000000002,3865:0.15434639725421775,318:0.16924612516623572,558:0.24384373237418783,471:0.16826200999114294,4340:0.16651713654958472,7:0.164357811310303,1841:0.15904628827648598,4208:0.16296041411613846,14:0.14043468960009342}

Key: 1: Value: {1615:0.3312716794782159,2181:0.2840451034186393,2126:0.32415666313248037,3188:0.1628119850871482,1496:0.24775558568026784,1:1.0,1575:0.13525396149776772,1269:0.13286526354605824,28:0.45703740702783774,1866:0.3262754564949865}

Key: 2: Value: {2:1.0,4350:0.13571272853930183,348:0.12600225826696973,3210:0.13949921190207168,560:0.15234464042319912,3294:0.2889578044491356,802:0.17942407070282945,1633:0.1964965769704117,3355:0.1298340236494648,495:0.12627029072308343}

Key: 3: Value: {1990:0.17193706865160252,3700:0.1302978723523794,2082:0.16196813164388732,2227:0.12561545966019144,665:0.15584753719122243,1163:0.19345501767136697,6:0.22582692114456704,3:1.0,1555:0.1742692199362734,4:0.1818170186646791}

Key: 4: Value: {1990:0.13213250264185705,3:0.1818170186646791,2082:0.1349661297563062,1163:0.15679941310702006,1555:0.18261523201994426,6:0.1981917938129962,738:0.29646182670818444,1684:0.21050749439902763,4:0.9999999999999999,3150:0.1397676584929176}

you can see above similarity matrix with scores

e;g [ 558:0.24384373237418783,471:0.16826200999114294 ]

docIndex key 0 maps to 0:1.0000000000000002 in similarity.txt output.

Similarly docIndex key 558 maps to 558:0.24384373237418783. in similarity.txt output.

--- Sample

sh mahout seqdumper -i vectors/tfidf-vectors > vectors.txt
sh mahout seqdumper -i vectors/tf-vectors > vectors.txt

MongoDB Real-Time Analytics Part-2

2013-10-11T17:11:00.004-07:00

Here is another schema sample for storing Daily,Hourly and Minutes data 

{
"_id" : "daily", ---> should be unique date for the day
"article" : {
"HT97" : 100,
"HT98" : 100,
"HT99" : 100
},
"daily" : 300,
"hourly" : {
"15" : 200,
"16" : 100
},
"minutely" : {
"957" : 100,
"958" : 100,
"960" : 100
}
}

package com.realtime;

 import java.text.SimpleDateFormat;

import java.util.Date;

import com.mongodb.BasicDBObject;

import com.mongodb.DB;

import com.mongodb.DBCollection;

import com.mongodb.DBObject;

import com.mongodb.Mongo;

public class test {

 public static void main(String[] args) {

      DBCollection collection = getCollection();

      for(int i=0;i<100;i++){

       Date now = new Date();

       String format  = new SimpleDateFormat("yyyy-MM-dd-HH-mm").format(now);

       Request1 r = new Request1(format,"HT"+i);

       upsert(r.getArticleId(),r,collection);

       System.out.println("upsert request: HT"+i);

}

}

 public static void upsert(String id, Request1 request,

            DBCollection collection) {

        BasicDBObject query = new BasicDBObject();

         query.put("_id", "monthly");

        DBObject dbo = createUpsert(request);

        collection.update(query, dbo, true, false);

}

/**

  * increment the stats

  * @param request

  * @return

*/

    public static DBObject createUpsert(Request1 request) {

        DBObject upsert = new BasicDBObject();

        DBObject inc = new BasicDBObject();

         // Count total hits

        inc.put("daily", 1);

        inc.put("minutely."+getMinutes(request),1); 

        inc.put("hourly."+getHour(request), 1);

        inc.put("article."+request.getArticleId(),1);

        upsert.put("$inc", inc);

        return upsert;

}

/**

     * get the current minute in day

     * @param r

     * @return

*/

    public static int getMinutes(Request1 r ){

     String format = r.getTime();

     String sMinutes = format.substring(format.lastIndexOf("-")+1);

     int minutes= Integer.parseInt(sMinutes);

     String sHour = getHour(r);

     int hour = Integer.parseInt(sHour);

     minutes = hour * 60 + minutes;

      return minutes;

}

/**

     * get current hour in a day

     * @param r

     * @return

*/

 public static String getHour(Request1 r){

  String format = r.getTime();

  format = format.substring(format.lastIndexOf("-")-2,format.length()-3);

  return format;

}

    public static DBCollection getCollection() {

        Mongo mongo;

        try {

            mongo = new Mongo();

        } catch (Exception e) {

            throw new RuntimeException(e);

}

        DB db = mongo.getDB("analytics");

        return db.getCollection("metrics");

}

}

MongoDB Real Time Analytics.

2013-09-24T12:07:00.004-07:00

MongoDB makes it super easy to implement real-time analytics, while the natural tendency is to use Map Reduce feature provided my mongoDB to aggregate data, thought on using upsert feature and $inc operator to see how complex aggregation and groupings can be performed in real-time.

we can update total counts , averages and find distinct entities for a given period( per/sec , per/min, per/hour) in a single upsert statement. this data is then immediately available to draw real-time charts.

Let's say we want to obtain the following information every second for our application.

1. Total Hits

2. Unique Users

3. Unique IP Address

4. Average Response time for each URL ..etc

We will start by setting up some sample requests. Here, I am hardcoding them. In real world, we can tail and parse a log file. Alternatively, this information can be sent directly from the application to our analytics system.

     Date d = new Date();

     SimpleDateFormat dt1 = new SimpleDateFormat("yyyyy_mm_dd_hh_mm_ss");

  Request r1 = new Request(dt1.format(d), "127_0_0_1","/apple/support1", "user1", 1);

  Request r2 = new Request(dt1.format(d), "127_0_0_1","/apple/support1", "user2", 2);

  Request r3 = new Request(dt1.format(d), "127_0_0_1","/apple/support2", "user1", 1);

  Request r4 = new Request(dt1.format(d), "127_0_0_1","/apple/support2", "user2", 1);

  Request r5 = new Request(dt1.format(d), "127_0_0_1","/apple/support1", "user1", 1);

  Request r6 = new Request(dt1.format(d), "192_168_1_20","/apple/support1", "user3", 4);

  Request r7 = new Request(dt1.format(d), "127_0_0_1","/apple/support3", "user1", 1);

Note that the periods in IP Address have been replaced with underscores. This is done because we will be using them as the keys in our JSON documents and having periods in there will cause undesirable effects.

Next, we need to decide the aggregation interval. This determines how we choose our document id’s.
In this example, we have decided to aggregate every second, so we can choose our id as the request time that includes second level information(2013_09_23_02_29_28). If we were aggregating at an hourly interval, we could have simply used the id that contains only hour level information; such as ”2013_09_23_02″.

Based on the chosen id, all requests coming within a second will update a single document. While there may be hundreds of request per second, we will end up having one document per second, that will represent the aggregated view for that second.

This has a very nice side effect. MongoDB index sizes are directly propotional to the number of documents. Since we maintain one record per second instead of storing each request as a separate document, we greatly reduce the required index size and its much easier to fit the index in memory.

So, let us see how does aggregation and counts happen. Following is the function that creates the upsert request for each record.

1 public static DBObject createUpsert(Request request) {

2

3        DBObject upsert = new BasicDBObject();

4        DBObject inc = new BasicDBObject();

5        // Count total hits

6        inc.put("hits", 1);

7        // Get distinct IP's & Count hits per IP

8        inc.put("ip." + request.getIp() + ".hits", 1);

9        // Get Distinct Users & Count hits per user

10        inc.put("users." + request.getUser() + ".hits", 1);

11

12        // Get Distinct URL's & Count hits per URL

13        inc.put("urls." + request.getUrl() + ".hits", 1);

14        // Total time taken to process 'n' requests.

15        // Divide it by the count obtained above to get the average processing time for each URL.

16        inc.put("urls." + request.getUrl() + ".totalTime",request.getProcessTime());

17        upsert.put("$inc", inc);

18        return upsert;

19    }

Line Number 6 simply increments the ‘hits’ field, giving us the total hits in a second.
In Line Number 8, we get more creative. For the current request, if the field ip.’ip_address’ (e.g. ip.localhost) exists, then its ‘hits’ field is incremented. Otherwise, the field ip.’ip_address’ get added to the ‘ip’ field. At the end of the second, we have collected all distinct IPs from which the application got the requests as well as the number of requests received from each IP.

We do the same for users and URL’s. Finally, in line number 16, we accumulate the total processing time for all requests for each ‘url’ in the field urls.’url’.totalTime.
By simply dividing the accumulated time by the ‘hits’ count later, we can get the average response time.

Here’s the function that gets invoked for each request, updating/inserting the records in database.

  public static void upsert(String id, Request request,

            DBCollection collection) {

        BasicDBObject query = new BasicDBObject();

        query.put("_id", id);

        DBObject dbo = createUpsert(request);

        collection.update(query, dbo, true, false);

}

As each request is received and upserted, our data keeps on getting aggregated immediately. Below is the final aggregated document at the end of processing requests for the time period represented by ’2013_09_23_02_29_28′.

{

"_id" : "2013_09_23_02_29_28",

"hits" : 7,

"ip" : {

"192_168_1_20" : {

"hits" : 1

"127_0_0_1" : {

"hits" : 6

}

"urls" : {

"/apple/support1" : {

"hits" : 4,

"totalTime" : 8

"/apple/support2" : {

"hits" : 2,

"totalTime" : 2

"/apple/support3" : {

"hits" : 1,

"totalTime" : 1

}

"users" : {

"user1" : {

"hits" : 4

"user2" : {

"hits" : 2

"user3" : {

"hits" : 1

}

In this approach, each request is a single write operation. With each write we do multiple aggregations and generate the latest aggregated view with almost no delay. There is absolutely no need to run any batch processes or expensive Map-Reduce to get this information. It is right there and can be read from the database and presented to the UI in less than a second

If you chose to implement sharding, then the document id’s would have to be chosen differently.

For example, in the current scenario, we might append host name to the time, effectively storing data for each host in a different shard. At runtime, we can do a simple aggregation at the application level to present a unified view, while equally distributing the load to multiple database servers.

Complete Code for below.

Aggregator.java

package com.realtime;

import java.text.SimpleDateFormat;

import java.util.Date;

import com.mongodb.BasicDBObject;

import com.mongodb.DB;

import com.mongodb.DBCollection;

import com.mongodb.DBObject;

import com.mongodb.Mongo;

public class Aggregator {

  public static void main(String[] args) {

  Date d = new Date();

  SimpleDateFormat dt1 = new SimpleDateFormat("yyyy_MM_dd_hh_mm_ss");

  Request r1 = new Request(dt1.format(d), "127_0_0_1","/apple/support1", "user1", 1);

  Request r2 = new Request(dt1.format(d), "127_0_0_1","/apple/support1", "user2", 2);

  Request r3 = new Request(dt1.format(d), "127_0_0_1","/apple/support2", "user1", 1);

  Request r4 = new Request(dt1.format(d), "127_0_0_1","/apple/support2", "user2", 1);

  Request r5 = new Request(dt1.format(d), "127_0_0_1","/apple/support1", "user1", 1);

  Request r6 = new Request(dt1.format(d), "192_168_1_20","/apple/support1", "user3", 4);

  Request r7 = new Request(dt1.format(d), "127_0_0_1","/apple/support3", "user1", 1);

  try {

  Thread.sleep(1000);

  } catch (InterruptedException e) {

}

  Date d1 = new Date();

  SimpleDateFormat dt2 = new SimpleDateFormat("yyyy_MM_dd_hh_mm_ss");

  Request r8 = new Request(dt2.format(d1), "127_0_0_1","/apple/support1", "user4", 2);

        Request requests[] = { r1, r2, r3, r4, r5, r6, r7, r8 };

        DBCollection collection = getCollection();

        for (Request request : requests) {

            upsert(request.getTime(), request, collection);

}

}

  public static void upsert(String id, Request request,

            DBCollection collection) {

        BasicDBObject query = new BasicDBObject();

        query.put("_id", id);

        DBObject dbo = createUpsert(request);

        collection.update(query, dbo, true, false);

}

    public static DBObject createUpsert(Request request) {

        DBObject upsert = new BasicDBObject();

        DBObject inc = new BasicDBObject();

        // Count total hits

        inc.put("hits", 1);

        // Get distinct IP's & Count hits per IP

        inc.put("ip." + request.getIp() + ".hits", 1);

        // Get Distinct Users & Count hits per user

        inc.put("users." + request.getUser() + ".hits", 1);

        // Get Distinct URL's & Count hits per URL

        inc.put("urls." + request.getUrl() + ".hits", 1);

        // Total time taken to process 'n' requests.

        // Divide it by the count obtained above to get the average processing

        // time for each URL.

        inc.put("urls." + request.getUrl() + ".totalTime",

                request.getProcessTime());

        upsert.put("$inc", inc);

        return upsert;

}

    public static DBCollection getCollection() {

        Mongo mongo;

        try {

            mongo = new Mongo();

        } catch (Exception e) {

            throw new RuntimeException(e);

}

        DB db = mongo.getDB("realtime");

        return db.getCollection("requests");

}

}

Below is the code for Request.java

package com.realtime;

public class Request {

private String time;

private String ip;

private String url;

private String user;

private int processTime;

public Request(String time, String ip, String url, String user,

int processTime) {

this.ip = ip;

this.time = time;

this.user = user;

this.url = url;

this.processTime = processTime;

}

public String getTime() {

return time;

}

public String getIp() {

return ip;

}

public String getUrl() {

return url;

}

public String getUser() {

return user;

}

public int getProcessTime() {

return processTime;

}

XmlAdapter - JAXB's Secret Ninja.

2013-08-09T13:30:00.003-07:00

The XmlAdapter mechanism in JAXB ensures that there is no such thing as an unmappable class. However there appears to be some confusion on how to use XmlAdapter, below is the general concept:

Identify the unmappable class
Create an equivalent class that is mappable
Create an XmlAdapter to convert between unmappable and mappable objects
Specify the XmlAdapte

Recently i ran into a problem where i need to Store/Retrieve data from MongoDB using ApacheCXF and Spring-Data for MongoDB.

Storing data was easy i had no complaints when using Map's. As shown below.

@XmlRootElement(name = "article")
publicclass Article implements Serializable{

     

private static final long serialVersionUID = 1L;

private Map<String,Map<String,String>> map = new HashMap<String,Map<String,String>>();

  
public Article(){}
public Article(Map<String,Map<String,String>> m){
 this.map = m;

    }
 public Map<String,Map<String,String>> getMap() {

  return map;
 }
 publicvoid setMap(Map<String,Map<String,String>>  map) {
  this.map = map;
 }

}

Above class was good enough for Create Operation, however when i was trying to retrieve data it was throwing exception that unable to convert Map to XML , JAXB exception all over.

that's when i decided to extend XMLAdapter.

1. Identify the Unmappable Class
In this example the unmappable class is java.util.Map.

2. Create an Equivalent Class that is Mappable
Map could be represented by an object ,that contained a list of objects with two properties: key and value . Below are the classes that i implemented to achieve this.

public class MapType {

public List element = new ArrayList();

}

public class MapEntryType {

@XmlAttribute 

public String name;

@XmlElement

public List<LinkCountMapType> attribute = new ArrayList<LinkCountMapType>();

}

public class LinkCountMapType {

@XmlAttribute

public String name;

@XmlValue 

public String count;

}

3. Create an XmlAdapter to Convert Between Unmappable and Mappable Objects
The XmlAdapter class is responsible for converting between instances of the unmappable and mappable classes. Most people get confused between the value and bound types. The value type is the mappable class, and the bound type is the unmappable class.

public final class MapAdapter extends XmlAdapter<MapType, Map<String, Map<String, String>>> {

@Override

public Map<String, Map<String, String>> unmarshal(MapType v) throws Exception {

    Map<String, Map<String, String>> mainMap = new HashMap<String, Map<String, String>>();

    List<MapEntryType> myMapEntryTypes = v.element;

    for (MapEntryType myMapEntryType : myMapEntryTypes) {

        Map<String, String> linkCountMap = new HashMap<String, String>();

        for (LinkCountMapType myLinkCountMapType : myMapEntryType.attribute) {

            linkCountMap.put(myLinkCountMapType.name, myLinkCountMapType.count);

}

        mainMap.put(myMapEntryType.name, linkCountMap);

}

    return mainMap;

}

@Override

public MapType marshal(Map<String, Map<String, String>> v) throws Exception {

    MapType myMapType = new MapType();

    List<MapEntryType> entry = new ArrayList<MapEntryType>();

    for (String name : v.keySet()) {

        MapEntryType myMapEntryType = new MapEntryType();

        Map<String, String> linkCountMap = v.get(name);

        List<LinkCountMapType> linkCountList = new ArrayList<LinkCountMapType>();

        for (String link : linkCountMap.keySet()) {

            LinkCountMapType myLinkCountMapType = new LinkCountMapType();

            String count = linkCountMap.get(link);

            myLinkCountMapType.count = count;

            myLinkCountMapType.name = link;

            linkCountList.add(myLinkCountMapType);

}

        myMapEntryType.name = name;

        myMapEntryType.attribute = linkCountList;

        entry.add(myMapEntryType);

}

    myMapType.element = entry;

    return myMapType;

}

}

4. Specify the XmlAdapter 

The @XmlJavaTypeAdapter annotation is used to specify the use of the XmlAdapter. Below it is specified on the map field on the Article class. Now during marshal/unmarshal operations the instance of Map is treated as an instance of My MapType.

@XmlRootElement(name = "article")

@XmlAccessorType(XmlAccessType.FIELD)

 public class Article implements Serializable{

private static final long serialVersionUID = 1L;

    @XmlJavaTypeAdapter(MapAdapter.class)

private Map<String,Map<String,String>> map = new HashMap<String,Map<String,String>>();

    public Article(){}

    public Article(Map<String,Map<String,String>> m){

     this.map = m;

}

  public Map<String,Map<String,String>> getMap() {

  return map;

}

 public void setMap(Map<String,Map<String,String>>  map) {

  this.map = map;

}

}

Mac OSX - install mod_jk

2013-05-02T10:04:00.001-07:00

Steps to install mod_jk on OSX

Download source from apache site

http://apache.mirrors.hoobly.com//tomcat/tomcat-connectors/jk/tomcat-connectors-1.2.41-src.tar.gz

Extract file and start building

cd native

make clean

./configure CFLAGS='-arch x86_64' APXSLDFLAGS='-arch x86_64' --with-apxs=/usr/sbin/apxs

make

sudo make install

If you are seeing a compiler issues , follow below steps

The C compiler ("cc") is located inside of that xctoolchain directory.
I created a symlink for OSX10.8.xctoolchain to point to XcodeDefault.xctoolchain
and that fixed the issue of compiler issue.

cd /Applications/Xcode.app/Contents/Developer/Toolchains
sudo ln -s XcodeDefault.xctoolchain OSX10.11.xctoolchain

If internal directory doesn't exist. There was no MacOSX10.11.Internal.sdk intead the directory was MacOSX10.11.sdk. So to create a symlink:

sudo ln -s /Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.11.sdk /Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.11.Internal.sdk

Disable System Integrity by restarting the machine and holding [ Command + R ] until apple logo comes up.

then open the terminal from utilities and enter below command

csrutil disable --> this is done because when installing apache mod_jk.so file is not getting installed in /usr/libexec/apache2 folder, throwing error permission denied.

again to enable enter below command

csrutil enable.

Configure Apache mod_jk.conf ( /etc/apache2/other/mod_jk.conf )

ps=/

LoadModule jk_module /usr/libexec/apache2/mod_jk.so
JkShmFile /var/log/apache2/mod_jk.shm
JkWorkersFile /etc/apache2/workers.properties
JkLogFile /var/log/apache2/mod_jk.log
JkLogLevel info
JkLogStampFormat "[%a %b %d %H:%M:%S %Y] "
JkRequestLogFormat "%w %V %T"
<Location /status>
JkMount status
Order deny,allow
Deny from all
Allow from 127.0.0.1 192.168.2.%
</Location>
# app2 Worker
JkMount /*.jsp worker1
JkMount /* worker1
## lb test - Worker
JkMount /lb lbloadbalancer
JkMount /lb/* lbloadbalancer

workers.properties (cd /etc/apache2/)

ps=/

worker.list=worker1, lbloadbalancer

worker.default.port=8009

worker.default.host=localhost

worker.default.type=ajp13

worker.default.lbfactor=1

# worker1

worker.worker1.port=8009

worker.worker1.host=localhost

worker.worker1.type=ajp13

worker.worker1.lbfactor=1

worker.worker1.socket_connect_timeout=10000

worker.worker1.socket_keepalive=True

worker.worker1.ping_mode=A

worker.worker1.ping_timeout=10000

worker.worker1.connection_pool_minsize=0

worker.worker1.connection_pool_timeout=600

worker.worker1.retries=1

worker.worker1.recovery_options=7

worker.worker1.reply_timeout=10000

# LB - Loadbalancer

worker.lbloadbalancer.type=lb

worker.lbloadbalancer.balance_workers=worker1

worker.lbloadbalancer.sticky_session=True

•Change Tomcat-server config

Edit file:

$TOMCAT_INSTALL/conf/server.xml
Change

Engine name="Catalina" defaultHost="localhost"
Into:
Engine name="Catalina" defaultHost="localhost" jvmRoute="worker1"

That's it.

starting apache
cd /etc/apache2/
sudo apachectl start/stop

logs for mod_jk
cd /var/log/apache2
tail -f mod_jk.log

To enable server status for apache on Mac OSX.
This is the solution if you are running Mac OS X 10.11 El Capitan. Note: You need administrator privileges. (sudo)
In your /etc/apache2/httpd.conf uncomment these lines
LoadModule status_module libexec/apache2/mod_status.so
Include /private/etc/apache2/extra/httpd-info.conf

Now open /etc/apache2/extra/httpd-info.conf and make changes as below.
<Location /server-status>
SetHandler server-status
Require host localhost
</Location>

Now you can open the URL http://localhost/server-status with your web browser and see the apache status.

Include below to see " It Works" when you enter localhost in your browser, however localhost/status page throws error now.

# Virtual hosts
Include /private/etc/apache2/extra/httpd-vhosts.conf

<VirtualHost *:80>
ServerName localhost
DocumentRoot /Library/WebServer/Documents/
</VirtualHost>

Setting up Coherence in Tomcat Clustered Environment

2011-04-24T21:06:00.000-07:00

Update catalina.sh

XXX_OPTS="-Dtangosol.coherence.distributed.localstorage=false -Dtangosol.coherence.cacheconfig=$PROP_PATH/coherence_cache.xml -Dtangosol.coherence.override=$PROP_PATH/coherence_cache_override.xml"

export CATALINA_OPTS="-server -d64 -Xloggc:xxxx/gc.log -XX:+PrintGCDetails -Xms2048m -Xmx2048m -Dfile.encoding=UTF-8 -DKMSERVICES_HOME=$PROP_PATH $XXX_OPTS"

echo "Catalina OPTS " $CATALINA_OPTS

below is the coherence_cache_override.xml

below is the coherence_cache.xml

How to install/Test Coherence*WEB for Weblogic

2011-04-16T20:34:00.000-07:00

Coherence Based Session Management

Assumptions: you have downloaded latest web logic server 10.3.3 and Coherence Web 3.6
   from Oracle

Instructions

First we will create weblogic domains : something like DOMAIN_A and DOMAIN_B.
To configure those domains with coherence based session management, then the
changing of session variable value in one domain will propagate to another domain.

Main Steps

Application Server (WebLogic)

1) Create DOMAIN_A and DOMAIN_B
2) Copy coherence.jar to DOMAIN_A\lib and DOMAIN_B\lib
3) Start both the Domains
4) Deploy coherence-web-spi.war as a shared library

Coherence

1) duplicate cache-server.cmd at the same folder in the coherence and rename
   it to web-cache-server.cmd
2) modify web-cache-server.cmd as shown below
3) set java_opts="-Xms%memory% -Xmx%memory%"

"%java_exec%" -server -showversion "%java_opts%" -cp
c:\coherence\lib\coherence.jar;c:\coherence\lib\coherence-web-spi.war -
Dtangosol.coherence.management.remote=true -Dtangosol.coherence.cacheconfig=WEB-
INF/classes/session-cache-config.xml -Dtangosol.coherence.session.localstorage=true
com.tangosol.net.DefaultCacheServer %1

4) startup web-cache-server.cmd
5) Modify weblogic.xml to add a reference to coherence-web-spi as shown below
   in you application

wls:library-ref

wls:library-name coherence-web-spi wls:library-name

wls:specification-version 1.0.0.0 wls:specification-version

wls:exact true wls:exact

wls:library-ref

deploy the webapp to DOMAIN_A and DOMAIN_B

Now test Session variable value at DOMAIN_A and check wether it is changed at DOMAIN_B, As show in the below figure

Coherence In Action

Setting Up Tomcat Multiple Instances

2011-04-12T20:56:00.000-07:00

Setting up tomcat multiple instances

1) First Original Instance, download apache-tomcat-5.5.33 ( any version) this will be the original
Instance and change nothing here.

2) For the instance 2 ... to N do the following as mentioned below

a) Create a new Folder (TomcatInstance1….N) as many as you instances as you want
b) Copy following folders over to TomcatInstance1… to N
conf
logs
temp
webapps
work
c) Write a script to startup/shutdown the second instance(name it as startup.sh
and shutdown.sh) and place under TomcatInstance1..N folders
d) Add following to the newly created startup.sh

CATALINA_HOME=~/Documents/apache-tomcat-5.5.33
CATALINA_BASE=~/Documents/TomcatInstance1
export CATALINA_HOME CATALINA_BASE

$CATALINA_HOME/bin/catalina.sh start

e) Add the following to the newly created shutdown.sh

CATALINA_HOME=~/Documents/apache-tomcat-5.5.33
CATALINA_BASE=~/Documents/TomcatInstance1
export CATALINA_HOME CATALINA_BASE

$CATALINA_HOME/bin/catalina.sh stop

f) Modify the server.xml file in TomcatInstance1/conf/server.xml and change the port
number to 8180

AND change port number to 8109 for the Connector Port of "AJP/1.3"

That's it now start the server with following command " sh startup.sh" and login to
http://localhost:8180 and you should see the tomcat page, do the same for as many instances as you want

How to install/Test Coherence*WEB for Tomcat

2011-04-12T20:48:00.000-07:00

Steps to Create

First Install Coherence*Web in your local directory

1) Complete the application inspection step by running the following command.
Specify the full path to your application and the name of your server
(replacing the and with them in the command line below):

java -jar webInstaller.jar

-inspect -server:

e;g java -jar WebInstaller.jar c:\MyCoherenceWeb -inspect -server:Tomcat/5.5

The system will create the coherence-web.xml

2) Complete the Coherence Web application installation step by running the following command,
replacing with the full path to your application:

java -jar webInstaller.jar

-install
e;g java -jar webInstaller.jar c:\MyCoherenceWeb -install

The installer requires a valid coherence-web.xml configuration file to reside
in the same directory as the application

checking if this process is correctly installed or not by verifying the application.war file.

1) Make sure you have a coherence-web.xml in you META-INF file.
2) Installer will Add the following directive to each JSP Page that you have in application

3) Installer will modify and add Coherence Web configuration context parameters in web.xml
descriptor and also add's a listener classes at the end of the web.xml file
4) Make sure you classes folder will have "session-cache-config.xml" file generated.
5) Make sure you lib folder contain coherence.jar and coherence-web.jar

Portlet IPC using JBOSS Portal

2009-07-24T17:25:00.000-07:00


Portlet 2.0 is the recently finalized latest version of the Java portlet
specification. One of the shortcomings of the previous version of the spec
(JSR168)was lack of support for inter-portlet communication.As a result, 
developers had to resort to all kinds of fancy workarounds using Dojo Toolkit

I am not going to explain what is JSR286 , but try to 
achieve IPC for JBOSS Portal

Defining events

To define an event, you would have to declare it in
portlet.xml, as shown  below

   <event-definition>
      <qname
      xmlns:mycomp='http://www.something.com/jsr286'>
      something:AppEvent</qname>
      <value-type>com.ceon.ocp.portlet.WrapperEvent</value-type>
      </event-definition>

 Publishing an Event

<portlet>
....
<portlet-name>pubEventPortlet</portlet-name>
<supported-publishing-event>
   <qname 
    xmlns:something='http://www.something.com/jsr286'>
    something:AppEvent</qname>
</supported-publishing-event>
....
</portlet>

Processing an Event

<portlet>
....
<portlet-name>subEventPortlet</portlet-name>
<supported-processing-event>
 <qname xmlns:something='http://www.something.com/jsr286'>
 something:AppEvent</qname>
</supported-processing-event>
....
</portlet>

Each portlet definition can have both publishing and processing tags
and you could define multiple events within each portlet definition

Coding events

An Example event class 

@XmlRootElement
public class WrapperEvent implements Serializable {
    ...
    public static final QName QNAME = new QName(
   "http://www.something.com/jsr286", "AppEvent");
    private String name;
        private String zipcode;
        ...
}

An event class must implement the Serializable interface and be annotated with 
@XmlRootElement, I am using Java 5,so I used jaxb-api-2.1.jar from the JBoss portlet 
container 2.0 lib directory

subscriber ( receiving portlet ) 

@Override
 protected void doView(RenderRequest request, RenderResponse renderResponse)
   throws PortletException, IOException {
  renderResponse.setContentType(request.getResponseContentType());
  // setting the attributes for JSP
  request.setAttribute(QUOTE_ATTR, quoteId);
  getPortletContext().getRequestDispatcher(VIEW_JSP).include(request,renderResponse);
 }
 @Override
 public void processEvent(EventRequest eventRequest, EventResponse response)
   throws PortletException, IOException {
        Event event = eventRequest.getEvent();
        if(event.getQName().equals(WrapperEvent.QNAME))
        {
         com.ceon.ocp.portlet.WrapperEvent
         wrapEvent=(com.ceon.ocp.portlet.WrapperEvent)event.getValue();
         quoteId = wrapEvent.getQuoteID();

        }
       }

Publisher( trigger event portlet) 

@Override
  protected void doView(RenderRequest request, RenderResponse renderResponse)
   throws PortletException, IOException {
   renderResponse.setContentType(request.getResponseContentType());
   getPortletContext().getRequestDispatcher(VIEW_JSP)
   .include(request,renderResponse);
}

@Override
  public void processAction(ActionRequest request, ActionResponse response)
 throws PortletException, IOException {
 String quoteParam = request.getParameter("QuoteID");
 if ( quoteParam == null || quoteParam.trim().equals("")) {
 quoteParam = "No Quote ID Specified";
 }
 com.ceon.ocp.portlet.WrapperEvent event
        = new  com.ceon.ocp.portlet.WrapperEvent();
 event.setQuoteID(quoteParam);
 response.setEvent(com.ceon.ocp.portlet.WrapperEvent.QNAME, event);
 }

And simple JSPs for both subscriber and publisher.

reciever.jsp 

<%@taglib uri="http://java.sun.com/portlet_2_0" prefix="portlet"%>
<portlet:defineObjects />
 Here are the details of Quote State:
QuoteState: <%= renderRequest.getAttribute("QuoteID")%>

publisher.jsp

<%@taglib uri="http://java.sun.com/portlet_2_0" prefix="portlet"%>
<portlet:defineObjects />
Please enter Quote ID and click submit,you should
see the Quote State in OCP Portlet

<form method='post' action="<portlet:actionURL />" >
  QuoteID: <input type=text name=QuoteID>
  <input type=submit> 
  </form>

One final step is go to 

After you have installed and configured the container,look at its core Web 
application, called simple-portal.This Web application holds the framework that 
displays the portlets. You could either add your own page by modifying 
layouts/nav/main.jsp, or modify one of the existing pages. I modified one of the 
existing pages, demo/demo.jsp, by removing its portlets and adding my own custom 
portlets. The JBoss portlet container uses a very simple tag library to include 
portlets, which requires the portlet name as defined in portlet.xml and the
context name of the portlet Web application

<xportal:portlet name="pubEventPortlet" applicationName="JbossSample"/>               
<xportal:portlet name="subEventPortlet" applicationName="JbossSample"/>  

As you can see, it's quite easy for a portlet to receive events from another portlet,
whether the two portlets reside in the same or separate Web applications.
You just have to make sure to include the common event classes in all portlet Web 
applications.If you would like to deploy this application to an other Portlet 2.0 
container, make sure to check that container's requirements for web.xml,as some 
containers expect specific elements in the web.xml files of Portlet 2.0 applications

How to configure a Jboss Datasource?

2009-07-24T12:51:00.000-07:00

Configuring a Datasource in Jboss very easy
Step 1: copy the original oracle-ds.xml from $jboss-home\docs\examples\jca\oracle-ds.xml to 
$jboss-home\server\default\deploy\
Step 2: modify the XML file as follows
<datasources>
 <local-tx-datasource>
 <jndi-name>OracleDS</jndi-name>
 <connection-url>jdbc:oracle:thin:@IP:PORT:SID</connection-url>
<use-java-context>false</use-java-context> 
<!-- this is required if u want to connect to DB remotely  from Main method-- >
<driver-class>oracle.jdbc.driver.OracleDriver</driver-class>
   <user-name>user</user-name>
   <password>password</password>
   <min-pool-size>5</min-pool-size>
   <max-pool-size>100</max-pool-size>
   <query-timeout>60</query-timeout>

   <exception-sorter-class-name>org.jboss.resource.adapter.jdbc.vendor.OracleExceptionSorter</exception-sorter-class-name>
   <metadata>
    <type-mapping>Oracle9i</type-mapping>
   </metadata>
  </local-tx-datasource>
  </datasources>
 
Step 3. Drop the JDBC driver jar into Jboss classpath (easiest approach - drop the jar file in to /server/default/lib)

Invoking Datasource Remotely for JBOSS

2009-07-24T12:16:00.000-07:00

DataSources are not exposed remotely by default.

In JBoss4 and above, you can set the following attribute to false in the datasource 
definition: in oracle-ds.xml to lookup datasource remotely ( typically from external
java class from main method as shown below) <use-java-context>false</use-
java-context> if datasource is not invoked remotely then you can
comment the above line in oracle-ds.xml

 public static void main(String[] args) {
  try {
        Properties props = new Properties();
        props.setProperty("java.naming.factory.initial",
        "org.jnp.interfaces.NamingContextFactory");
        props.setProperty("java.naming.factory.url.pkgs"
        ,"org.jboss.naming");
        props.setProperty("java.naming.provider.url",
        "127.0.0.1:1099");
        
        InitialContext ctx = new InitialContext(props);
        MyBeanRemote bean=(MyBeanRemote)ctx.lookup("MyBean/remote");
        bean.doSomething();
        DataSource ds = (DataSource)ctx.lookup("OracleDS");
        Connection con = ds.getConnection(); 
        ResultSet rs = con.createStatement()
          .executeQuery("SELECT NAME FROM EMPLOYEE");  
        while (rs.next()) {  
          System.out.println("I got " + rs.getString(1));  
        }  
        rs.close();  
        con.close();
        } catch (Exception e) {
            .......
        }
    }

Note : if the datasource is not looked-up 
remotely then the look-up might change to ctx.lookup("java:OracleDS") or 
ctx.lookup("java:/OracleDS") depends on whatever DS is bound to , check the server 
start up log