This is a stack program where the algorithm works on Last in First Out (LIFO) concept. This is a typical stack program with insertion complexity as O(1) i.e constant.


/**
*
*/
package java8pract.datastructures;

A simple linked list program where insertion complexity is O(1) order of one i.e independent of data size.

Here is the code for the same

Here is the Node/Element/Data object of linked list

Note: This program has been written with minimum code so that users can copy and experiment with it. This is not a full fledged program, hence not recommended for production use.


public class Node {

Node previous;
T element;
Node next;

public Node(Node previous, T element, Node next) {
this.previous=previous;
this.element=element;
this.next=next;

}

@Override
public String toString() {
return “Node [element=” + element + “]”;
}

}

And here is the linked list implementation,

package java8pract.linkedlist_custom;
/**
* An implementation of linked list. Entire linked list is dependent on first element in the list.
*/
import java.util.ArrayList;
import java.util.List;

public class CustomLinkedList {

Node firstNode;
Node tempNode;
Node lastNode;
/**
* Add an element to the linked list
* +/—————————————-
* + 1. if first node is null, create a node and assign it to first node.
* + 2. and assign the newly created node to a temp Node;
* + 3. for consecutive additions, get the temp node into a middle methods level node
* + 4. Create new node and assign previous node as middle node.
* + 5.update the last node.
* + 6. middle node.next to newly created node
* + 7. and update temp node with newly created node.
* @param element
*/

public void add(T element) {
Node node = null;
if (null == firstNode) {
node = new Node(null, element, null);
firstNode = node;

} else {
Node middleNode = tempNode;
node = new Node(middleNode, element, null);
lastNode = node;
middleNode.next = node;

}
tempNode = node;
}

/**
* Get all the elements in linked list
*
* @return
*/
public List getAll() {
List list = new ArrayList();
Node temp = firstNode;
while (temp != null) {
list.add(temp);
System.out.println(temp.element);
temp = temp.next;

}
return list;
}

/**
* Get all the elements in the linked list in reverse order.
*
* @return
*/
public List getAllReverse() {
List list = new ArrayList();
Node temp = lastNode;
while (temp != null) {
list.add(temp);
System.out.println(temp.element);
temp = temp.previous;

}
return list;

}

public Node get(T t) {

Node temp = firstNode;
while (temp != null) {

if (temp.element !=null && temp.element.compareTo(t)==0) {
break;
} else {
temp = temp.next;
}
}

return temp;

}
/**
* Get the first node (HEAD) in the linked list
* @return
*/
public Node getFirstNode(){
return firstNode;
}
/**
* Get the last node in the linked list.
* @return
*/
public Node getLastNode(){
return lastNode;
}

}


An easiest way to create mongodb cluster in MacOs environment.

These steps can be executed one after the other in Mac Terminal.
Note: Make sure that the folders paths are correct before running these commands.

Create Initial directories required for mongo db cluter

cd /Users/prabhu/Documents/softwares/mongodb-osx-x86_64-4.0.6/bin/data

mkdir replica1 replica2 replica3 replica4 replica5 replica6 replica7 replica8 replica9 config1 config2 config3

Sudo chmod –R 777 repl*

Sudo chmod –R 777 conf*

shard1

./mongod –dbpath=/Users/prabhu/Documents/softwares/mongodb-osx-x86_64-4.0.6/bin/data/replica1 –port=27011 –bind_ip_all –replSet=replica1 –shardsvr

./mongod –dbpath=/Users/prabhu/Documents/softwares/mongodb-osx-x86_64-4.0.6/bin/data/replica2 –port=27012 –bind_ip_all –replSet=replica1 –shardsvr

./mongod –dbpath=/Users/prabhu/Documents/softwares/mongodb-osx-x86_64-4.0.6/bin/data/replica3 –port=27013 –bind_ip_all –replSet=replica1 –shardsvr

rs.initiate({_id:”replica1″,members:[{“_id”:1,”host”:”localhost:27011″}]})

rs.add(“localhost:27012”)

rs.add(“localhost:27013”)

shard2

./mongod –dbpath=/Users/prabhu/Documents/softwares/mongodb-osx-x86_64-4.0.6/bin/data/replica4 –port=27021 –bind_ip_all –replSet=replica2 –shardsvr

./mongod –dbpath=/Users/prabhu/Documents/softwares/mongodb-osx-x86_64-4.0.6/bin/data/replica5 –port=27022 –bind_ip_all –replSet=replica2 –shardsvr

./mongod –dbpath=/Users/prabhu/Documents/softwares/mongodb-osx-x86_64-4.0.6/bin/data/replica6 –port=27023 –bind_ip_all –replSet=replica2 –shardsvr

rs.initiate({_id:”replica2″,members:[{“_id”:1,”host”:”localhost:27021″}]})

rs.add(“localhost:27022”)

rs.add(“localhost:27023”)

Shard 3

./mongod –dbpath=/Users/prabhu/Documents/softwares/mongodb-osx-x86_64-4.0.6/bin/data/replica7 –port=27031 –bind_ip_all –replSet=replica3 –shardsvr

./mongod –dbpath=/Users/prabhu/Documents/softwares/mongodb-osx-x86_64-4.0.6/bin/data/replica8 –port=27032 –bind_ip_all –replSet=replica3 –shardsvr

./mongod –dbpath=/Users/prabhu/Documents/softwares/mongodb-osx-x86_64-4.0.6/bin/data/replica9 –port=27033 –bind_ip_all –replSet=replica3 –shardsvr

rs.initiate({_id:”replica3″,members:[{“_id”:1,”host”:”localhost:27031″}]})

rs.add(“localhost:27032”)

rs.add(“localhost:27033”)

config

./mongod –dbpath=/Users/prabhu/Documents/softwares/mongodb-osx-x86_64-4.0.6/bin/data/config1 –port=27018 –bind_ip_all –replSet=config1 –configsvr

./mongod –dbpath=/Users/prabhu/Documents/softwares/mongodb-osx-x86_64-4.0.6/bin/data/config2 –port=27019 –bind_ip_all –replSet=config1 –configsvr

./mongod –dbpath=/Users/prabhu/Documents/softwares/mongodb-osx-x86_64-4.0.6/bin/data/config3 –port=27020 –bind_ip_all –replSet=config1 –configsvr

rs.initiate({_id:”config1″,members:[{“_id”:1,”host”:”localhost:27018″}]})

rs.add(“localhost:27019”)

rs.add(“localhost:27020”)

Start Mongos with config cluster
./mongos –configdb=”config1/localhost:27018,localhost:27019,localhost:27020″ –port=27017 –bind_ip_all

Connect to Mongos Server
./mongod –port 27017

sh.addShard(“replica1/localhost27011”)

sh.addShard(“replica2/localhost27021”)

sh.addShard(“replica3/localhost27031”)

sharding Collection

sh.enableSharding(“shoppingdb”); // enable sharding for db

sh.shardCollection(“shoppingdb.Orders”,{_id:1},true); // shard the collection

There are lot of articles which talks about domain driven design, Event Driven and CQRS architectural practices. However,In this blog post, an effort to put domain driven design (DDD), Event Driven and Command Query Responsibility Segregation in a simple application which will explain all of above concepts. This application has been developed using spring boot, axon ,axon db server, java programming language, maven for build and eclipse etc.
In this application we are just trying to create an order with some order items (Command) and retrieve the same (Query) using order id. This is a very common scenario in any e commerce application and also a good example to explain above concepts.
Here is the out line of flow,

And here is the git hub url for code

https://github.com/prabhukvn/axon-springboot-poc.git

Here is en example where iterating over an array is much faster than iterating over a list directly. This we can apply if we have to iterate a list over multiple time in a single thread.

private static void checkArrayList() {
ArrayList listOne = new ArrayList();

long startTime = System.nanoTime();
for (int i = 0; i <span id="mce_SELREST_start" style="overflow:hidden;line-height:0;">&#65279;</span>&lt; 1000; i++) {
listOne.add(i);
}
// Total time taken to construct an array list with 1000 elements
System.out.println(&quot;Total Time 1:&quot; + (System.nanoTime() - startTime));

// Iterate entire list
startTime = System.nanoTime();
for (int k : listOne) {

}
// total time to iterate over 1000 elements
System.out.println(&quot;Total Time 2:&quot; + (System.nanoTime() - startTime));

Integer a[] = new Integer[1000];
// Convert list into array
startTime = System.nanoTime();
listOne.toArray(a);
// time to convert list into array
System.out.println(&quot;Total Time 3:&quot; + (System.nanoTime() - startTime));
// Iterate entire array
startTime = System.nanoTime();
for (int k : a) {

}
// total time taken to iterate over array
System.out.println(&quot;Total Time 4:&quot; + (System.nanoTime() - startTime));
}