Data Structures and algoithms Unit - 1.pptxmexiuro901
it is about data structures and algorithms. this ppt has all data structures like linkedlist, trees, graph,it is about data structures and algorithms. this ppt has all data structures like linkedlist, trees, graph,it is about data structures and algorithms. this ppt has all data structures like linkedlist, trees, graph,
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.
Data structure is an arrangement of data in computer's memory. It makes the data quickly available to the processor for required operations.It is a software artifact which allows data to be stored, organized and accessed.
Data Structures and algoithms Unit - 1.pptxmexiuro901
it is about data structures and algorithms. this ppt has all data structures like linkedlist, trees, graph,it is about data structures and algorithms. this ppt has all data structures like linkedlist, trees, graph,it is about data structures and algorithms. this ppt has all data structures like linkedlist, trees, graph,
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.
Data structure is an arrangement of data in computer's memory. It makes the data quickly available to the processor for required operations.It is a software artifact which allows data to be stored, organized and accessed.
Array is a container which can hold a fix number of items and these items should be of the same type. Most of the data structures make use of arrays to implement their algorithms. Following are the important terms to understand the concept of array.
Adjusting OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).
Array is a container which can hold a fix number of items and these items should be of the same type. Most of the data structures make use of arrays to implement their algorithms. Following are the important terms to understand the concept of array.
Adjusting OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
Unleashing the Power of Data_ Choosing a Trusted Analytics Platform.pdfEnterprise Wired
In this guide, we'll explore the key considerations and features to look for when choosing a Trusted analytics platform that meets your organization's needs and delivers actionable intelligence you can trust.
6. Array
Array: An ordered collection of values with two
distinguishing characters:
Ordered and fixed length
Homogeneous. Every value in the array must be of the same
type
The individual values in an array are called elements.
The number of elements is called the length of the
array
7. Stack
It is an ordered group of homogeneous items of elements.
Elements are added to and removed from the top of the
stack (the most recently added items are at the top of the
stack).
The last element to be added is the first to be removed
(LIFO: Last In, First Out).
8. Stack Specification
Definitions: (provided by the user)
MAX_ITEMS: Max number of items that might be
on the stack
ItemType: Data type of the items on the stack
Operations
MakeEmpty
Boolean IsEmpty
Boolean IsFull
Push (ItemType newItem)
Pop (ItemType& item) (or pop and top)
9. Queue
It is an ordered group of homogeneous items
of elements.
Queues have two ends:
Elements are added at one end.
Elements are removed from the other end.
The element added first is also removed first
(FIFO: First In, First Out).
queue
elements
enter
no changes of order
elements
exit
2
3
4 1
tail head
10. Queue Specification
Definitions: (provided by the user)
MAX_ITEMS: Max number of items that might be
on the queue
ItemType: Data type of the items on the queue
• Operations
– MakeEmpty
– Boolean IsEmpty
– Boolean IsFull
– Enqueue (ItemType newItem)
– Dequeue (ItemType & item) (serve and retrieve)
11. Linked List
A linked list is a linear data structure, in which the
elements are not stored at contiguous memory
locations. The elements in a linked list are linked
using pointers