In this Java data structures tutorial your will learn the different ways that you can store and manipulate data using: Arrays, 2D Arrays, Lists, Set and Maps.
⭐ Table Of Contents ⭐
00:00 - Intro
01:18 - IntelliJ
03:26 - Arrays
17:37 - 2D Arrays
25:04 - Lists and ArrayList
37:12 - Stack
46:16 - Queue
54:06 - Linked List
01:07:05 - Sets
01:16:03 - Map Interface
01:18:06 - Map
01:27:59 - Hash Functions and HashCode
01:38:52 - Outro
Continuing on the Quick Revision of Important Questions for My Interviews. These Are Good Puzzles or Questions Related to Data Structures.
My Article Series on Algorithms and Data Structures in a Sort of ‘Programming Language Agnostic Way’. Few of the Algorithms and Data Structures in C, Few in C++, and Others in Core Java. Assorted Collection for Learning, Revising, Revisiting, Quick Refresh, and a Quick Glance for Interviews. You May Even Include them Directly for Professional or Open Source Efforts. Have Included Explanation Only for Few of These! Hope these turn out to be Really Helpful as per the Author’s Intention.
#java #core java #data structures #dijkstra #core java basics #data structure using java #algorithms and data structures #java code examples #linked list in java #circular linked list
OpenJDk or Open Java Development Kit is a free, open-source framework of the Java Platform, Standard Edition (or Java SE). It contains the virtual machine, the Java Class Library, and the Java compiler. The difference between the Oracle OpenJDK and Oracle JDK is that OpenJDK is a source code reference point for the open-source model. Simultaneously, the Oracle JDK is a continuation or advanced model of the OpenJDK, which is not open source and requires a license to use.
In this article, we will be installing OpenJDK on Centos 8.
#tutorials #alternatives #centos #centos 8 #configuration #dnf #frameworks #java #java development kit #java ee #java environment variables #java framework #java jdk #java jre #java platform #java sdk #java se #jdk #jre #open java development kit #open source #openjdk #openjdk 11 #openjdk 8 #openjdk runtime environment
If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.
If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.
In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.
#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition
The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.
This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.
As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).
This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.
#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management
Great Learning brings you this live session on “Data Structures and Algorithms For Tech”. In this session, we’ll be understanding the concept of data structures followed by understanding its different types. The session begins with the discussion of linear data structure - Array, its implementation, application, advantages and disadvantages. Post this, we will look at Linked List, Stack, and Queue along with their implementations, applications, advantages and disadvantages. In this session, you will also learn about a couple of Searching Algorithms such as Linear Search and Binary Search, along with their algorithms, implementation and analysis based on time & space complexity. We will also be discussing basic sorting algorithms such as Bubble Sort, etc. Finally, we will take you through the Divide and Conquer approach wherein you will learn about Merge Sort, its algorithm along with a demonstration, its implementation and analysis based on time complexity, space complexity, number of comparisons, etc. and will also analyse it in terms of the Divide and Conquer paradigm. This session will be an interactive one where you can ask relevant questions throughout the live stream!
#algorithms #java #data-structures