The collections framework provides a unified architecture for representing and manipulating collections. It includes interfaces that define common functionality for collections as well as implementations of these interfaces that provide concrete data structures. The framework reduces programming effort, increases performance, and fosters reuse. It is based on over a dozen collection interfaces and their implementations, as well as algorithms for manipulating the collections.
The Collection in Java is a framework that provides an architecture to store and manipulate the group of objects.
All the operations that you perform on a data such as searching, sorting, insertion, manipulation, deletion, etc. can be achieved by Java Collections.
Java Collection means a single unit of objects. Java Collection framework provides many interfaces (Set, List, Queue, Deque, etc.) and classes (ArrayList, Vector, LinkedList, PriorityQueue, HashSet, LinkedHashSet, TreeSet, etc.).
To learn important concept of Collection and its handling plus its advantages and different class & child class of Collection and their implementations. Important interview questions of the collection.
( ** Java Certification Training: https://www.edureka.co/java-j2ee-soa-training ** )
This Edureka tutorial on “Java ArrayList” (Java blog series: https://goo.gl/osrGrS) will give you a brief insight about ArrayList in Java and its various constructors and methods along with an example. Through this tutorial, you will learn the following topics:
Collections Framework
Hierarchy of ArrayList
What is ArrayList
Internal Working of ArrayList
Constructors of ArrayList
Constructors Example
ArrayList Methods
Methods Example and Demo
Advantages of ArrayList over Arrays
Check out our Java Tutorial blog series: https://goo.gl/osrGrS
Check out our complete Youtube playlist here: https://goo.gl/CRbgFann
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Collections and its types in C# (with examples)Aijaz Ali Abro
Learn step by step c# collections with easy examples. Learn generic, non-generic and specialized collections along with easy and great examples. Learn about arraylist, queue class,stack class and more. Difference between generic and non-generic collections. Difference between arraylist and simple array.
The Collections Framework (java.util)- Collections overview, Collection Interfaces, The Collection classes- Array List, Linked List, Hash Set, Tree Set, Priority Queue, Array Deque. Accessing a Collection via an Iterator, Using an Iterator, The For-Each alternative, Map Interfaces and Classes, Comparators, Collection algorithms, Arrays, The Legacy Classes and Interfaces- Dictionary, Hashtable ,Properties, Stack, Vector More Utility classes, String Tokenizer, Bit Set, Date, Calendar, Random, Formatter, Scanner
The Collection in Java is a framework that provides an architecture to store and manipulate the group of objects.
All the operations that you perform on a data such as searching, sorting, insertion, manipulation, deletion, etc. can be achieved by Java Collections.
Java Collection means a single unit of objects. Java Collection framework provides many interfaces (Set, List, Queue, Deque, etc.) and classes (ArrayList, Vector, LinkedList, PriorityQueue, HashSet, LinkedHashSet, TreeSet, etc.).
To learn important concept of Collection and its handling plus its advantages and different class & child class of Collection and their implementations. Important interview questions of the collection.
( ** Java Certification Training: https://www.edureka.co/java-j2ee-soa-training ** )
This Edureka tutorial on “Java ArrayList” (Java blog series: https://goo.gl/osrGrS) will give you a brief insight about ArrayList in Java and its various constructors and methods along with an example. Through this tutorial, you will learn the following topics:
Collections Framework
Hierarchy of ArrayList
What is ArrayList
Internal Working of ArrayList
Constructors of ArrayList
Constructors Example
ArrayList Methods
Methods Example and Demo
Advantages of ArrayList over Arrays
Check out our Java Tutorial blog series: https://goo.gl/osrGrS
Check out our complete Youtube playlist here: https://goo.gl/CRbgFann
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Collections and its types in C# (with examples)Aijaz Ali Abro
Learn step by step c# collections with easy examples. Learn generic, non-generic and specialized collections along with easy and great examples. Learn about arraylist, queue class,stack class and more. Difference between generic and non-generic collections. Difference between arraylist and simple array.
The Collections Framework (java.util)- Collections overview, Collection Interfaces, The Collection classes- Array List, Linked List, Hash Set, Tree Set, Priority Queue, Array Deque. Accessing a Collection via an Iterator, Using an Iterator, The For-Each alternative, Map Interfaces and Classes, Comparators, Collection algorithms, Arrays, The Legacy Classes and Interfaces- Dictionary, Hashtable ,Properties, Stack, Vector More Utility classes, String Tokenizer, Bit Set, Date, Calendar, Random, Formatter, Scanner
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
2. COLLECTION
FRAMEWORK
The collections framework is a unified architecture for
representing and manipulating collections, enabling
them to be manipulated independently of the details
of their representation. It reduces programming effort
while increasing performance. It enables
interoperability among unrelated APIs, reduces effort
in designing and learning new APIs, and fosters
software reuse. The framework is based on more than
a dozen collection interfaces. It includes
implementations of these interfaces and algorithms to
manipulate them.
3. CONTENTS
What is Collection?
Collections Framework
Collections Hierarchy
Collections Implementations
Set
List
Map
4. OBJECTIVES
Define a collection
Describe the collections framework
Describe the collections hierarchy
Demonstrate each collection implementation
5. WHAT IS A COLLECTION?
A Collection (also known as container) is an object that contains a
group of objects treated as a single unit.
Any type of objects can be stored, retrieved and manipulated as
elements of collections.
6. COLLECTIONS FRAMEWORK
Collections Framework is a unified architecture for
managing collections
Main Parts of Collections Framework
1. Interfaces
Core interfaces defining common functionality exhibited by
collections
1. Implementations
Concrete classes of the core interfaces providing data structures
1. Operations
Methods that perform various operations on collections
7. COLLECTIONS FRAMEWORK
INTERFACES
Core Interface Description
Collection specifies contract that all collections should implement
Set defines functionality for a set of unique elements
SortedSet defines functionality for a set where elements are sorted
List defines functionality for an ordered list of non- unique elements
Map defines functionality for mapping of unique keys to values
SortedMap defines functionality for a map where its keys are sorted
8. COLLECTIONS FRAMEWORK
IMPLEMENTATIONS
Set List Map
HashSet ArrayList HashMap
LinkedHashSet LinkedList LinkedHashMap
TreeSet Vector Hashtable
Tree Map
Note: Hashtable uses a lower-case “t”
9. OPERATIONS
Basic collection operations:
Check if collection is empty
Check if an object exists in collection.
Retrieve an object from collection
Add object to collection
Remove object from collection
Iterate collection and inspect each object
Each operation has a corresponding method implementation for
each collection type
10. COLLECTIONS
CHARACTERISTICS
Ordered
Elements are stored and accessed in a specific
order
Sorted
Elements are stored and accessed in a sorted
order
Indexed
Elements can be accessed using an index
Unique
Collection does not allow duplicates
11. ITERATOR
An iterator is an object used to mark a position in a
collection of data and to move from item to item within
the collection
Syntax:
Iterator <variable> = <CollectionObject>.iterator();
12. COLLECTIONS HIERARCHY
SET AND LIST
HashSet
Collection
SortedSet
List
Set
LinkedHashSet TreeSet LinkedList Vector ArrayList
implements
implements
implements
implements extends
extends
14. COLLECTION IMPLEMENTATIONS
Set : Unique things (classes that implement Set)
Map : Things with a unique ID (classes that implement Map)
List : Lists of things (classes that implement List)
15. LIST
A List cares about the index.
“Paul”
“Paul” “Mark”
“Mark” “John”
“John” “Paul”
“Paul” “Luke”
“Luke”
value
index 0 1 2 3 4
LinkedList
LinkedList
Vector
Vector
ArrayList
ArrayList
16. LIST IMPLEMENTATIONS
ARRAY LIST
import java.util.ArrayList;
public class MyArrayList {
public static void main(String args[ ]) {
ArrayList alist = new ArrayList( );
alist.add(new String("One"));
alist.add(new String("Two"));
alist.add(new String("Three"));
System.out.println(alist.get(0));
System.out.println(alist.get(1));
System.out.println(alist.get(2));
}
}
One
Two
Three
17. LIST IMPLEMENTATIONS
VECTOR
import java.util.Vector;
public class MyVector {
public static void main(String args[ ]) {
Vector vecky = new Vector( );
vecky.add(new Integer(1));
vecky.add(new Integer(2));
vecky.add(new Integer(3));
for(int x=0; x<3; x++) {
System.out.println(vecky.get(x));
}
}
}
1
2
3
18. LIST IMPLEMENTATIONS
LINKED LIST
import java.util.LinkedList;
public class MyLinkedList {
public static void main(String args[ ]) {
LinkedList link = new LinkedList( );
link.add(new Double(2.0));
link.addLast(new Double(3.0));
link.addFirst(new Double(1.0));
Object array[ ] = link.toArray( );
for(int x=0; x<3; x++) {
System.out.println(array[x]);
}
}
}
1.0
2.0
3.0
19. SET
A Set cares about uniqueness, it doesn’t allow duplicates.
“Paul”
“Paul”
“Mark”
“Mark”
“John”
“John”
“Luke”
“Luke”
“Fred”
“Fred”
“Peter”
“Peter”
TreeSet
TreeSet
LinkedHashSet
LinkedHashSet
HashSet
HashSet
20. SET IMPLEMENTATIONS
HASH SET
import java.util.*;
public class MyHashSet {
public static void main(String args[ ]) {
HashSet hash = new HashSet( );
hash.add("a");
hash.add("b");
hash.add("c");
hash.add("d");
Iterator iterator = hash.iterator( );
while(iterator.hasNext( )) {
System.out.println(iterator.next( ));
}
}
}
d
a
c
b
21. SET IMPLEMENTATIONS
LINKED HASH SET
import java.util.LinkedHashSet;
public class MyLinkedHashSet {
public static void main(String args[ ]) {
LinkedHashSet lhs = new LinkedHashSet();
lhs.add(new String("One"));
lhs.add(new String("Two"));
lhs.add(new String("Three"));
Object array[] = lhs.toArray( );
for(int x=0; x<3; x++) {
System.out.println(array[x]);
}
}
}
One
Two
Three
22. SET IMPLEMENTATIONS
TREE SET
import java.util.TreeSet;
import java.util.Iterator;
public class MyTreeSet {
public static void main(String args[ ]) {
TreeSet tree = new TreeSet();
tree.add("Jody");
tree.add("Remiel");
tree.add("Reggie");
tree.add("Philippe");
Iterator iterator = tree.iterator( );
while(iterator.hasNext( )) {
System.out.println(iterator.next( ).toString( ));
}
}
}
Jody
Philippe
Reggie
Remiel
25. MAP IMPLEMENTATIONS
HASH TABLE
import java.util.Hashtable;
public class MyHashtable {
public static void main(String args[ ]) {
Hashtable table = new Hashtable( );
table.put("name", "Jody");
table.put("id", new Integer(1001));
table.put("address", new String("Manila"));
System.out.println("Table of Contents:" + table);
}
}
Table of Contents:
{address=Manila, name=Jody, id=1001}
26. MAP IMPLEMENTATIONS
LINKED HASH MAP
import java.util.*;
public class MyLinkedHashMap {
public static void main(String args[ ]) {
int iNum = 0;
LinkedHashMap myMap = new LinkedHashMap( );
myMap.put("name", "Jody");
myMap.put("id", new Integer(446));
myMap.put("address", "Manila");
myMap.put("type", "Savings");
Collection values = myMap.values( );
Iterator iterator = values.iterator( );
while(iterator.hasNext()) {
System.out.println(iterator.next( ));
}
}
}
Jody
446
Manila
Savings
27. MAP IMPLEMENTATIONS
TREE MAP
import java.util.*;
public class MyTreeMap {
public static void main(String args[]) {
TreeMap treeMap = new TreeMap( );
treeMap.put("name", "Jody");
treeMap.put("id", new Integer(446));
treeMap.put("address", "Manila");
Collection values = treeMap.values()
Iterator iterator = values.iterator( );
System.out.println("Printing the VALUES....");
while (iterator.hasNext()) {
System.out.println(iterator.next( ));
}
}
}
Printing the VALUES....
Manila
446
Jody
28. COLLECTION CLASSES SUMMARY
No
By index
X
LinkedList
No
By index
X
Vector
No
By index
X
ArrayList
No
By insertion order or
last access order
X
LinkedHashSet
By natural order or
custom comparison rules
Sorted
X
TreeSet
No
No
X
HashSet
No
By insertion order or
last access order
X
LinkedHashMap
By natural order or
custom comparison rules
Sorted
X
TreeMap
No
No
X
Hashtable
No
No
X
HashMap
Sorted
Ordered
List
Set
Map
Class
29. KEY POINTS
Collections Framework contains:
1. Interfaces
2. Implementations
3. Operations
A list cares about the index.
A set cares about uniqueness, it does not allow
duplicates.
A map cares about unique identifiers.
30. THANK YOU
CPD TECHNOLOGIES
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Metro Pillar No-397
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