The document discusses NoSQL technologies including Cassandra, MongoDB, and ElasticSearch. It provides an overview of each technology, describing their data models, key features, and comparing them. Example documents and queries are shown for MongoDB and ElasticSearch. Popular use cases for each are also listed.
These are the slides I presented at the Nosql Night in Boston on Nov 4, 2014. The slides were adapted from a presentation given by Steve Francia in 2011. Original slide deck can be found here:
http://spf13.com/presentation/mongodb-sort-conference-2011
NoSQL databases are currently used in several applications scenarios in contrast to Relations Databases. Several type of Databases there exist. In this presentation we compare Key Value, Column Oriented, Document Oriented and Graph Databases. Using a simple case study there are evaluated pros and cons of the NoSQL databases taken into account.
These are the slides I presented at the Nosql Night in Boston on Nov 4, 2014. The slides were adapted from a presentation given by Steve Francia in 2011. Original slide deck can be found here:
http://spf13.com/presentation/mongodb-sort-conference-2011
NoSQL databases are currently used in several applications scenarios in contrast to Relations Databases. Several type of Databases there exist. In this presentation we compare Key Value, Column Oriented, Document Oriented and Graph Databases. Using a simple case study there are evaluated pros and cons of the NoSQL databases taken into account.
This Presentation is about NoSQL which means Not Only SQL. This presentation covers the aspects of using NoSQL for Big Data and the differences from RDBMS.
We went over what Big Data is and it's value. This talk will cover the details of Elasticsearch, a Big Data solution. Elasticsearch is an NoSQL-backed search engine using a HDFS-based filesystem.
We'll cover:
• Elasticsearch basics
• Setting up a development environment
• Loading data
• Searching data using REST
• Searching data using NEST, the .NET interface
• Understanding Scores
Finally, I show a use-case for data mining using Elasticsearch.
You'll walk away from this armed with the knowledge to add Elasticsearch to your data analysis toolkit and your applications.
Elasticsearch Arcihtecture & What's New in Version 5Burak TUNGUT
General architectural concepts of Elasticsearch and what's new in version 5? Examples are prepared with our company business therefore these are excluded from presentation.
This Presentation is about NoSQL which means Not Only SQL. This presentation covers the aspects of using NoSQL for Big Data and the differences from RDBMS.
We went over what Big Data is and it's value. This talk will cover the details of Elasticsearch, a Big Data solution. Elasticsearch is an NoSQL-backed search engine using a HDFS-based filesystem.
We'll cover:
• Elasticsearch basics
• Setting up a development environment
• Loading data
• Searching data using REST
• Searching data using NEST, the .NET interface
• Understanding Scores
Finally, I show a use-case for data mining using Elasticsearch.
You'll walk away from this armed with the knowledge to add Elasticsearch to your data analysis toolkit and your applications.
Elasticsearch Arcihtecture & What's New in Version 5Burak TUNGUT
General architectural concepts of Elasticsearch and what's new in version 5? Examples are prepared with our company business therefore these are excluded from presentation.
NoSQL, as many of you may already know, is basically a database used to manage huge sets of unstructured data, where in the data is not stored in tabular relations like relational databases. Most of the currently existing Relational Databases have failed in solving some of the complex modern problems like:
• Continuously changing nature of data - structured, semi-structured, unstructured and polymorphic data.
• Applications now serve millions of users in different geo-locations, in different timezones and have to be up and running all the time, with data integrity maintained
• Applications are becoming more distributed with many moving towards cloud computing.
NoSQL plays a vital role in an enterprise application which needs to access and analyze a massive set of data that is being made available on multiple virtual servers (remote based) in the cloud infrastructure and mainly when the data set is not structured. Hence, the NoSQL database is designed to overcome the Performance, Scalability, Data Modelling and Distribution limitations that are seen in the Relational Databases.
This is a presentation of the popular NoSQL database Apache Cassandra which was created by our team in the context of the module "Business Intelligence and Big Data Analysis".
For our eReader development project, we needed to find a persistent store for our JSON documents. After initial review we zeroed into two products - Amazon's DynamoDB and MonngoDB. These slides probes deeper why I selected one over the other.
For our eReader development project, we had to find a persistent storage for our JSON documents. After initial scanning we zeroed into two products DynamoDB and MongoDB. These slides take a deeper dive in the selection of our JSON data store.
The Indian economy is classified into different sectors to simplify the analysis and understanding of economic activities. For Class 10, it's essential to grasp the sectors of the Indian economy, understand their characteristics, and recognize their importance. This guide will provide detailed notes on the Sectors of the Indian Economy Class 10, using specific long-tail keywords to enhance comprehension.
For more information, visit-www.vavaclasses.com
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
1. NoSQL Technologies
Lecturer: Dr. Nguyen Binh Minh
Students:
- Pham Anh Doi
- Nguyen Quang Huy
- Nguyen Hai Nam
- Luong Anh Tuan
- Pham Duc Thang
- Nguyen Thi Tuyet Trinh
- Emmanuel Nana Ofori
2016-11-24 1
2. Agenda
• Introduction NoSQL
• Three Popular NoSQL: Cassandra, MongoDB,
ElasticSearch
• Compare Cassandra vs MongoDB vs
ElasticSearch
• Some NoSQL Changllengs
2016-11-24 2
7. What is MongoDB ?
• MongoDB is an open-source document
database, and leading NoSQL database.
MongoDB is written in c++
• MongoDB is a cross-platform, document oriented
database that provides, high performance, high
availability, and easy scalability. MongoDB works
on concept of collection and document.
8. MongoDB - Overview
• Database:
Database is a physical container for collections. Each database gets
its own set of files on the file system. A single MongoDB server
typically has multiple databases.
• Collection
Collection is a group of MongoDB documents. It is the equivalent of
an RDBMS table. A collection exists within a single database.
Collections do not enforce a schema. Documents within a collection
can have different fields. Typically, all documents in a collection are of
similar or related purpose.
9. MongoDB - Overview
• Document
A document is a set of key-value pairs. Documents have dynamic
schema. Dynamic schema means that documents in the same
collection do not need to have the same set of fields or structure, and
common fields in a collection's documents may hold different types
of data.
10. MongoDB - Overview
• Below given table shows the relationship of RDBMS
terminology with MongoDB
11. Sample document
• Below given example shows the document structure of a
blog site which is simply a comma separated key value
pair.
12. Sample document
• _id is a 12 bytes hexadecimal number which assures the uniqueness
of every document. You can provide _id while inserting the
document. If you didn't provide then MongoDB provide a unique id
for every document. These 12 bytes first 4 bytes for the current
timestamp, next 3 bytes for machine id, next 2 bytes for process id of
mongodb server and remaining 3 bytes are simple incremental value.
13. Advantages of MongoDB over RDBMS
• Schema less : MongoDB is document database in
which one collection holds different different
documents. Number of fields, content and size of the
document can be differ from one document to
another.
• Structure of a single object is clear
• No complex joins
• Deep query-ability. MongoDB supports dynamic
queries on documents using a document-based query
language that's nearly as powerful as SQL
• Tuning
14. Advantages of MongoDB over RDBMS
• Ease of scale-out: MongoDB is easy to scale
• Conversion / mapping of application objects to database objects not
needed
• Uses internal memory for storing the (windowed) working set,
enabling faster access of data
15. Why should use MongoDB?
• Document Oriented Storage : Data is stored in
the form of JSON style documents
• Index on any attribute
• Replication & High Availability
• Auto-Sharding
• Rich Queries
• Fast In-Place Updates
• Professional Support By MongoDB
16. Where should use MongoDB?
• Big Data
• Content Management and Delivery
• Mobile and Social Infrastructure
• User Data Management
• Data Hub
17. Not use for?
• Highly Transactional Applications.
• Problems requiring SQL.
Some Companies using MongoDB in Production
20. What is Cassandra
• Apache Cassandra is an open source, distributed and
decentralized/distributed storage system (database), for managing very
large amounts of structured data spread out across the world. It provides
highly available service with no single point of failure.
• Notable points of Apache Cassandra:
• It is scalable, fault-tolerant, and consistent.
• It is a column-oriented database.
• Its distribution design is based on Amazon’s Dynamo and its data model on Google’s
Bigtable.
• Created at Facebook, it differs sharply from relational database management
systems.
• Cassandra implements a Dynamo-style replication model with no single point of
failure, but adds a more powerful “column family” data model.
• Cassandra is being used by some of the biggest companies such as Facebook,
Twitter, Cisco, Rackspace, ebay, Twitter, Netflix, and more.
21. Feature of
Cassandra
Elastic
scalability
No Single
Point of
Failure
Scale
Horizontally
(Linear
Availability /
Scale Out)
Flexible data
storage
Easy data
distribution
Peer-to-peer
Architecture
( no primary
secondary)
Fast writes
22. Architecture of Cassandra
Cassandra was built from the ground up with the
understanding that hardware and system failures can
and do occur
Peer-to-peer, distributed system
All nodes are the same
Data partitioned among all modes in the cluster
Custom data replication to ensure fault tolerance
Read/write anywhere design
24. Component of Cassandra
Node − It is the place where data is stored.
Data center − It is a collection of related nodes.
Cluster − A cluster is a component that contains one or more data centers.
Commit log − The commit log is a crash-recovery mechanism in Cassandra.
Every write operation is written to the commit log.
Mem-table − A mem-table is a memory-resident data structure. After
commit log, the data will be written to the mem-table. Sometimes, for a
single-column family, there will be multiple mem-tables.
SSTable − It is a disk file to which the data is flushed from the mem-table
when its contents reach a threshold value.
Bloom filter − These are nothing but quick, nondeterministic, algorithms for
testing whether an element is a member of a set. It is a special kind of
cache. Bloom filters are accessed after every query.
26. • Is an earch engine / real-time search(1)
• Is free and open source distributed inverted index created by
shay banon.
• Build on top ofApache Lucene(2) .
• Developed in Java, so inherently cross-platform.
Mozilla, Quora, SoundCloud, GitHub, StackExchange, Center for Open
Science, Reverb, Netflix….
28. Why Elastic Search?
Easy to scale (Distributed)
Everything is one JSON call away (RESTful API)
Excellent Query DSL
Support for advanced search features (Full Text)
Configurable and Extensible
Document Oriented
Schema free
Conflict management
29. Elastic Search is built to scale horizontally out of
the box. When ever you need to increase
capacity, just add more nodes, and let the cluster
reorganize itself to take advantage of the extra
hardware.
Easy to Scale (Distributed)
RESTful API
ElasticSearch is API driven. Almost any action can be
performed using a simple RESTful API using JSON
over HTTP. .
Responses are always in JSON format.
30. Demo
1. Run elastic search and test in http://localhost:9200/
Response :
{
"status" : 200,
"name" : “elasticsearch",
"version" : {
"number" : "1.3.4",
"build_hash" : "f1585f096d3f3985e73456debdc1a0745f512bbc",
"build_timestamp" : "2015-04-21T14:27:12Z",
"build_snapshot" : false,
"lucene_version" : "4.9"
},
"tagline" : "You Know, for Search"
}
31. Demo
PUT data : curl -XPUT 'http://localhost:9200/twitter/tweet/1' -d '{"user" : "kimchy"}‘
Searching data: curl -XPUT
'http://localhost:9200/blog/post/_search?q=user:dilbert&pretty'
32. Feature Cassandra MongoDB ElasticSearch
Model #1 Wide-column store #1 Search engine #1 Document stores
Developer Apache Software MongoDB, Inc Foundation Elastic
Initial Release 2008 2010 2009
Database as a Service no no no
Server operating systems BSD, Linux, OS X,
Windows
All OS with a Java VM Linux, OS X, Solaris,
Windows
Data Schema free free free
Secondary indexes restricted yes yes
SQL no no no
APIs and other access
methods
Proprietary protocol Java API
RESTful HTTP/JSON API
proprietary protocol
using JSON
Server-side scripts no yes JavaScript
Compare Cassandra vs MongoDB vs ElasticSearch
33. Feature Cassandra MongoDB ElasticSearch
Partitioning methods Sharding Sharding Sharding
Replication methods selectable replication
factor
yes Master-slave replication
MapReduce yes no yes
Consistency concepts Eventual Consistency
Immediate Consistency
Eventual Consistency Eventual Consistency
Immediate Consistency
Foreign keys no no
no typically not used,
however similar
functionality with DBRef
possible
Transaction concepts no no no
Concurrency Support
for concurrent
manipulation of data
yes yes yes
Compare Cassandra vs MongoDB vs ElasticSearch