For more training on AWS, visit: https://www.qa.com/amazon
AWS Loft | London - Deep Dive: Amazon DynamoDB by Dean Bryen, Solutions Architect, 18 April 2016
Amazon DynamoDB is a fully managed, highly scalable NoSQL database service. We will deep dive into how DynamoDB scaling and partitioning works, how to do data modeling based on access patterns using primitives such as hash/range keys, secondary indexes, conditional writes and query filters. We will also discuss how to use DynamoDB Streams to build cross-region replication and integrate with other services (such as Amazon S3, Amazon CloudSearch, Amazon ElastiCache, Amazon Redshift) to enable logging, search, analytics and caching. You will learn design patterns and best practices on how to use DynamoDB to build highly scalable applications, with the right performance characteristics at the right cost.
AWS July Webinar Series - Getting Started with Amazon DynamoDBAmazon Web Services
This webinar provides an overview of Amazon DynamoDB, a fast, flexible, and fully managed NoSQL database service for Mobile, Web, AdTech, IOT and Gaming applications that need consistent, single-digit millisecond latency at any scale.The webinar will cover key topics around general architecture of DynamoDB, data types, throughput provisioning, querying and indexing, and recent features.
The webinar includes a live demo of the basic operations used to read and write data to a DynamoDB table, and how the concept of provisioned IO affects the throughput of these operations.
Learning Objectives:
Enable users to understand how DynamoDB works so that they can evaluate and use DynamoDB as the data store for their application
In this session, we explore Amazon DynamoDB capabilities and benefits in detail and discusses how to get the most out of your DynamoDB database. We go over schema design best practices with DynamoDB across multiple use cases, including gaming, AdTech, IoT, and others. We also explore designing efficient indexes, scanning, and querying, and go into detail on a number of recently released features, including JSON document support, Streams, and more.
Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. You can use Amazon DynamoDB to create a database table that can store and retrieve any amount of data, and serve any level of request traffic. Amazon DynamoDB automatically spreads the data and traffic for the table over a sufficient number of servers to handle the request capacity specified by the customer and the amount of data stored, while maintaining consistent and fast performance.
For more training on AWS, visit: https://www.qa.com/amazon
AWS Loft | London - Deep Dive: Amazon DynamoDB by Dean Bryen, Solutions Architect, 18 April 2016
Amazon DynamoDB is a fully managed, highly scalable NoSQL database service. We will deep dive into how DynamoDB scaling and partitioning works, how to do data modeling based on access patterns using primitives such as hash/range keys, secondary indexes, conditional writes and query filters. We will also discuss how to use DynamoDB Streams to build cross-region replication and integrate with other services (such as Amazon S3, Amazon CloudSearch, Amazon ElastiCache, Amazon Redshift) to enable logging, search, analytics and caching. You will learn design patterns and best practices on how to use DynamoDB to build highly scalable applications, with the right performance characteristics at the right cost.
AWS July Webinar Series - Getting Started with Amazon DynamoDBAmazon Web Services
This webinar provides an overview of Amazon DynamoDB, a fast, flexible, and fully managed NoSQL database service for Mobile, Web, AdTech, IOT and Gaming applications that need consistent, single-digit millisecond latency at any scale.The webinar will cover key topics around general architecture of DynamoDB, data types, throughput provisioning, querying and indexing, and recent features.
The webinar includes a live demo of the basic operations used to read and write data to a DynamoDB table, and how the concept of provisioned IO affects the throughput of these operations.
Learning Objectives:
Enable users to understand how DynamoDB works so that they can evaluate and use DynamoDB as the data store for their application
In this session, we explore Amazon DynamoDB capabilities and benefits in detail and discusses how to get the most out of your DynamoDB database. We go over schema design best practices with DynamoDB across multiple use cases, including gaming, AdTech, IoT, and others. We also explore designing efficient indexes, scanning, and querying, and go into detail on a number of recently released features, including JSON document support, Streams, and more.
Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. You can use Amazon DynamoDB to create a database table that can store and retrieve any amount of data, and serve any level of request traffic. Amazon DynamoDB automatically spreads the data and traffic for the table over a sufficient number of servers to handle the request capacity specified by the customer and the amount of data stored, while maintaining consistent and fast performance.
SQL to NoSQL Best Practices with Amazon DynamoDB - AWS July 2016 Webinar Se...Amazon Web Services
Applications have traditionally stored data in a relational database management system (RDBMS) and have used a Structured Query Language (SQL) to retrieve and update that data. The growth of “internet scale” apps, such as e-commerce, social media, mobile apps, and the rise of big data have increased data throughput demands beyond the range of traditional relational databases. Non-relational (NoSQL) databases enables your application to scale more cost effectively, even for extraordinarily high demand. Amazon DynamoDB is a fully managed NoSQL database service that lets you focus on your app so you don’t have to worry about hardware acquisition or database management and lets you scale down your costs for off-peak periods. In this webinar, we’ll describe common database tasks, then compare and contrast SQL with equivalent DynamoDB operations.
Learning Objectives:
• Why consider the switch from SQL to NoSQL?
• Benefits of Amazon’s NoSQL database service
• Common SQL database operations and their DynamoDB equivalents
SmugMug: From MySQL to Amazon DynamoDB (DAT204) | AWS re:Invent 2013Amazon Web Services
SmugMug.com is a popular hosting and commerce platform for photo enthusiasts with hundreds of thousands of subscribers and millions of viewers. Learn now SmugMug uses Amazon DynamoDB to provide customers detailed information about millions of daily image and video views. Smugmug shares code and information about their stats stack, which includes an HTTP interface to Amazon DynamoDB and also interfaces with their internal PHP stack and other tools such as Memcached. Get a detailed picture of lessons learned and the methods SmugMug uses to create a system that is easy to use, reliable, and high performing.
Amazon DynamoDB is a fully managed, highly scalable distributed database service. In this technical talk, we will deep dive on how to: Use DynamoDB to build high-scale applications like social gaming, chat, and voting. - Model these applications using DynamoDB, including how to use building blocks such as conditional writes, consistent reads, and batch operations to build the higher-level functionality such as multi-item atomic writes and join queries. - Incorporate best practices such as index projections, item sharding, and parallel scan for maximum scalability
Amazon DynamoDB is a fully managed NoSQL database service for applications that need consistent, single-digit millisecond latency at any scale. This talk explores DynamoDB capabilities and benefits in detail and discusses how to get the most out of your DynamoDB database. We go over schema design best practices with DynamoDB across multiple use cases, including gaming, AdTech, IoT, and others. We also explore designing efficient indexes, scanning, and querying, and go into detail on a number of recently released features, including JSON document support, Streams, and more.
by Edin Zulich, NoSQL Solutions Architect, AWS
Explore Amazon DynamoDB capabilities and benefits in detail and learn how to get the most out of your DynamoDB database. We go over best practices for schema design with DynamoDB across multiple use cases, including gaming, IoT, and others. We explore designing efficient indexes, scanning, and querying, and go into detail on a number of recently released features, including DynamoDB Accelerator (DAX), DynamoDB Time-to-Live, and more. We also provide lessons learned from operating DynamoDB at scale, including provisioning DynamoDB for IoT. Level: 200
Explore DynamoDB capabilities and benefits in detail and learn how to get the most out of your DynamoDB database. We go over schema design best practices with DynamoDB across multiple use cases, including gaming, AdTech, IoT, and others.
DynamoDB is a NoSQL database service built for fast, scalable, consistent performance. This presentation introduces DynamoDB and discusses how to get started, provision throughput, design for the DynamoDB data model, query and scan tables and scale reads and writes without downtime.
AWS re:Invent 2016: Deep Dive on Amazon DynamoDB (DAT304)Amazon Web Services
Explore Amazon DynamoDB capabilities and benefits in detail and learn how to get the most out of your DynamoDB database. We go over best practices for schema design with DynamoDB across multiple use cases, including gaming, AdTech, IoT, and others. We explore designing efficient indexes, scanning, and querying, and go into detail on a number of recently released features, including JSON document support, DynamoDB Streams, and more. We also provide lessons learned from operating DynamoDB at scale, including provisioning DynamoDB for IoT.
Learn how Amazon Redshift, our fully managed, petabyte-scale data warehouse, can help you quickly and cost-effectively analyze all your data using your existing business intelligence tools. Get an introduction to how Amazon Redshift uses massively parallel processing and scale-out architecture to ensure compute resources grow with your dataset size, and columnar, direct-attached storage to dramatically reduce I/O time. Learn how top online retailer RetailMeNot moved their largest Vertica cluster on Amazon EC2 to Amazon Redshift. See how they gain insights from clickstream, location, merchant, marketing, and operational data across desktop and mobile properties.
Learning Objectives:
- Learn the capabilities of Amazon DynamoDB in detail
- Learn best practices for schema design with DynamoDB
- Learn use cases for Non-relational (NoSQL) Databases
by Edin Zulich, NoSQL Solutions Architect, AWS
Following the DynamoDB Deep Dive session, this workshop is a design session (no computer needed) in which we will work through several real world DynamoDB use cases. For each one, we will go over the requirements, propose and analyze possible solutions and their pros and cons, with an eye for performance efficiency, scalability, and cost optimization. Level: 300
Amazon DynamoDB is a fully managed, highly scalable distributed database service. In this technical talk, we show you how to use Amazon DynamoDB to build high-scale applications like social gaming, chat, and voting. We show you how to use building blocks such as secondary indexes, conditional writes, consistent reads, and batch operations to build the higher-level functionality such as multi-item atomic writes and join queries. We also discuss best practices such as index projections, item sharding, and parallel scan for maximum scalability.
Speakers:
Philip Fitzsimons, AWS Solutions Architect
Richard Freeman, PhD, Senior Data Scientist/Architect, JustGiving
This session will begin with an introduction to non-relational (NoSQL) databases and compare them with relational (SQL) databases. Learn the fundamentals of Amazon DynamoDB, a fully managed NoSQL database service, and see the DynamoDB console first-hand. See a walk-through demo of building a serverless web application using this high-performance key-value and JSON document store.
Learn best practices for taking advantage of Amazon Redshift's columnar technology and parallel processing capabilities to improve your data warehouse performance.
Amazon DynamoDB is a fully managed NoSQL database service for applications that need consistent, single-digit millisecond latency at any scale. This talk explores DynamoDB capabilities and benefits in detail and discusses how to get the most out of your DynamoDB database. We go over schema design best practices with DynamoDB across multiple use cases, including gaming, AdTech, IoT, and others. We also explore designing efficient indexes, scanning, and querying, and go into detail on a number of recently released features, including JSON document support, Streams, and more.
Analyzing big data quickly and efficiently requires a data warehouse optimized to handle and scale for large datasets. Amazon Redshift is a fast, petabyte-scale data warehouse that makes it simple and cost-effective to analyze all of your data for a fraction of the cost of traditional data warehouses. In this webinar, we take an in-depth look at data warehousing with Amazon Redshift for big data analytics. We cover best practices to take advantage of Amazon Redshift's columnar technology and parallel processing capabilities to deliver high throughput and query performance.
Learning Objectives:
• Get an inside look at Amazon Redshift's columnar technology and parallel processing capabilities
• Learn how to design schemas and load data efficiently
• Learn best practices for workload management, distribution and sort keys, and optimizing queries
DAT102 Introduction to Amazon DynamoDB - AWS re: Invent 2012Amazon Web Services
Learn why Amazon DynamoDB is the fastest-growing service in AWS history. DynamoDB is a NoSQL database service that lets you scale from one to hundreds of thousands of I/Os per second (and beyond) with the push of a button. It's designed to give you scalability and high performance with minimal administration and enables you to scale your app while keeping costs down. You also learn about the service’s design principles, its history, and about how some of our customers are using DynamoDB in their applications.
SQL to NoSQL Best Practices with Amazon DynamoDB - AWS July 2016 Webinar Se...Amazon Web Services
Applications have traditionally stored data in a relational database management system (RDBMS) and have used a Structured Query Language (SQL) to retrieve and update that data. The growth of “internet scale” apps, such as e-commerce, social media, mobile apps, and the rise of big data have increased data throughput demands beyond the range of traditional relational databases. Non-relational (NoSQL) databases enables your application to scale more cost effectively, even for extraordinarily high demand. Amazon DynamoDB is a fully managed NoSQL database service that lets you focus on your app so you don’t have to worry about hardware acquisition or database management and lets you scale down your costs for off-peak periods. In this webinar, we’ll describe common database tasks, then compare and contrast SQL with equivalent DynamoDB operations.
Learning Objectives:
• Why consider the switch from SQL to NoSQL?
• Benefits of Amazon’s NoSQL database service
• Common SQL database operations and their DynamoDB equivalents
SmugMug: From MySQL to Amazon DynamoDB (DAT204) | AWS re:Invent 2013Amazon Web Services
SmugMug.com is a popular hosting and commerce platform for photo enthusiasts with hundreds of thousands of subscribers and millions of viewers. Learn now SmugMug uses Amazon DynamoDB to provide customers detailed information about millions of daily image and video views. Smugmug shares code and information about their stats stack, which includes an HTTP interface to Amazon DynamoDB and also interfaces with their internal PHP stack and other tools such as Memcached. Get a detailed picture of lessons learned and the methods SmugMug uses to create a system that is easy to use, reliable, and high performing.
Amazon DynamoDB is a fully managed, highly scalable distributed database service. In this technical talk, we will deep dive on how to: Use DynamoDB to build high-scale applications like social gaming, chat, and voting. - Model these applications using DynamoDB, including how to use building blocks such as conditional writes, consistent reads, and batch operations to build the higher-level functionality such as multi-item atomic writes and join queries. - Incorporate best practices such as index projections, item sharding, and parallel scan for maximum scalability
Amazon DynamoDB is a fully managed NoSQL database service for applications that need consistent, single-digit millisecond latency at any scale. This talk explores DynamoDB capabilities and benefits in detail and discusses how to get the most out of your DynamoDB database. We go over schema design best practices with DynamoDB across multiple use cases, including gaming, AdTech, IoT, and others. We also explore designing efficient indexes, scanning, and querying, and go into detail on a number of recently released features, including JSON document support, Streams, and more.
by Edin Zulich, NoSQL Solutions Architect, AWS
Explore Amazon DynamoDB capabilities and benefits in detail and learn how to get the most out of your DynamoDB database. We go over best practices for schema design with DynamoDB across multiple use cases, including gaming, IoT, and others. We explore designing efficient indexes, scanning, and querying, and go into detail on a number of recently released features, including DynamoDB Accelerator (DAX), DynamoDB Time-to-Live, and more. We also provide lessons learned from operating DynamoDB at scale, including provisioning DynamoDB for IoT. Level: 200
Explore DynamoDB capabilities and benefits in detail and learn how to get the most out of your DynamoDB database. We go over schema design best practices with DynamoDB across multiple use cases, including gaming, AdTech, IoT, and others.
DynamoDB is a NoSQL database service built for fast, scalable, consistent performance. This presentation introduces DynamoDB and discusses how to get started, provision throughput, design for the DynamoDB data model, query and scan tables and scale reads and writes without downtime.
AWS re:Invent 2016: Deep Dive on Amazon DynamoDB (DAT304)Amazon Web Services
Explore Amazon DynamoDB capabilities and benefits in detail and learn how to get the most out of your DynamoDB database. We go over best practices for schema design with DynamoDB across multiple use cases, including gaming, AdTech, IoT, and others. We explore designing efficient indexes, scanning, and querying, and go into detail on a number of recently released features, including JSON document support, DynamoDB Streams, and more. We also provide lessons learned from operating DynamoDB at scale, including provisioning DynamoDB for IoT.
Learn how Amazon Redshift, our fully managed, petabyte-scale data warehouse, can help you quickly and cost-effectively analyze all your data using your existing business intelligence tools. Get an introduction to how Amazon Redshift uses massively parallel processing and scale-out architecture to ensure compute resources grow with your dataset size, and columnar, direct-attached storage to dramatically reduce I/O time. Learn how top online retailer RetailMeNot moved their largest Vertica cluster on Amazon EC2 to Amazon Redshift. See how they gain insights from clickstream, location, merchant, marketing, and operational data across desktop and mobile properties.
Learning Objectives:
- Learn the capabilities of Amazon DynamoDB in detail
- Learn best practices for schema design with DynamoDB
- Learn use cases for Non-relational (NoSQL) Databases
by Edin Zulich, NoSQL Solutions Architect, AWS
Following the DynamoDB Deep Dive session, this workshop is a design session (no computer needed) in which we will work through several real world DynamoDB use cases. For each one, we will go over the requirements, propose and analyze possible solutions and their pros and cons, with an eye for performance efficiency, scalability, and cost optimization. Level: 300
Amazon DynamoDB is a fully managed, highly scalable distributed database service. In this technical talk, we show you how to use Amazon DynamoDB to build high-scale applications like social gaming, chat, and voting. We show you how to use building blocks such as secondary indexes, conditional writes, consistent reads, and batch operations to build the higher-level functionality such as multi-item atomic writes and join queries. We also discuss best practices such as index projections, item sharding, and parallel scan for maximum scalability.
Speakers:
Philip Fitzsimons, AWS Solutions Architect
Richard Freeman, PhD, Senior Data Scientist/Architect, JustGiving
This session will begin with an introduction to non-relational (NoSQL) databases and compare them with relational (SQL) databases. Learn the fundamentals of Amazon DynamoDB, a fully managed NoSQL database service, and see the DynamoDB console first-hand. See a walk-through demo of building a serverless web application using this high-performance key-value and JSON document store.
Learn best practices for taking advantage of Amazon Redshift's columnar technology and parallel processing capabilities to improve your data warehouse performance.
Amazon DynamoDB is a fully managed NoSQL database service for applications that need consistent, single-digit millisecond latency at any scale. This talk explores DynamoDB capabilities and benefits in detail and discusses how to get the most out of your DynamoDB database. We go over schema design best practices with DynamoDB across multiple use cases, including gaming, AdTech, IoT, and others. We also explore designing efficient indexes, scanning, and querying, and go into detail on a number of recently released features, including JSON document support, Streams, and more.
Analyzing big data quickly and efficiently requires a data warehouse optimized to handle and scale for large datasets. Amazon Redshift is a fast, petabyte-scale data warehouse that makes it simple and cost-effective to analyze all of your data for a fraction of the cost of traditional data warehouses. In this webinar, we take an in-depth look at data warehousing with Amazon Redshift for big data analytics. We cover best practices to take advantage of Amazon Redshift's columnar technology and parallel processing capabilities to deliver high throughput and query performance.
Learning Objectives:
• Get an inside look at Amazon Redshift's columnar technology and parallel processing capabilities
• Learn how to design schemas and load data efficiently
• Learn best practices for workload management, distribution and sort keys, and optimizing queries
DAT102 Introduction to Amazon DynamoDB - AWS re: Invent 2012Amazon Web Services
Learn why Amazon DynamoDB is the fastest-growing service in AWS history. DynamoDB is a NoSQL database service that lets you scale from one to hundreds of thousands of I/Os per second (and beyond) with the push of a button. It's designed to give you scalability and high performance with minimal administration and enables you to scale your app while keeping costs down. You also learn about the service’s design principles, its history, and about how some of our customers are using DynamoDB in their applications.
Data-Ed Webinar: A Framework for Implementing NoSQL, HadoopDATAVERSITY
Big Data and NoSQL continue to make headlines everywhere. However, most of what has been written about these topics is focused on the hardware, services, and scale out. But what about a Big Data and NoSQL Strategy, one that supports your business strategy? Virtually every major organization thinking about these data platforms is faced with the challenge of figuring out the appropriate approach and the requirements. This presentation will provide guidance on how to think about and establish realistic Big Data management plans and expectations. We will introduce a framework for evaluating the various choices when it comes to implementing and succeeding with Big Data/NoSQL and show how to demonstrate a sample use case.
Takeaways:
A Framework for evaluating Big Data techniques
Deciding on a Big Data platform – How do you know which one is a good fit for you?
The means by which big data techniques can complement existing data management practices
The prototyping nature of practicing big data techniques
The distinct ways in which utilizing Big Data can generate business value
This session will begin with an introduction to non-relational (NoSQL) databases and compare them with relational (SQL) databases. We will also explain the fundamentals of Amazon DynamoDB, a fully managed NoSQL database service. Learn the fundamentals of DynamoDB and see the new DynamoDB console first-hand as we discuss common use cases and benefits of this high-performance key-value and JSON document store.
AWS December 2015 Webinar Series - Design Patterns using Amazon DynamoDBAmazon Web Services
If you’re familiar with relational databases, designing your app to use a NoSQL database like DynamoDB may be new to you. In this webinar, we’ll walk you through common data design patterns for a variety of applications to help you learn how to design a schema, then store and retrieve the data with DynamoDB. We will discuss the benefits of using DynamoDB to develop mobile, web, IoT, and gaming apps.
Learning Objectives:
Learn schema design best practices with DynamoDB across multiple use cases, including gaming, AdTech, IoT, and others
Who Should Attend:
Architects, Developers, and SysOps interested in learning how to design NoSQL schemas to support mobile, web, IoT, AdTech, and gaming apps.
Familiarity with DynamoDB is helpful
Interested in learning about event-driven programming? In this session we will introduce you to some of the basics of using Amazon DynamoDB, its newly launched Streams feature and AWS Lambda. We will provide an overview of both AWS products and walk you through the process of building a real-world application using AWS Triggers, which combines DynamoDB Streams and AWS Lambda.
This session will begin with an introduction to non-relational (NoSQL) databases and compare them with relational (SQL) databases. We will also explain the fundamentals of Amazon DynamoDB, a fully managed NoSQL database service. Learn the fundamentals of DynamoDB and see the new DynamoDB console first-hand as we discuss common use cases and benefits of this high-performance key-value and JSON document store.
In this lecture we analyze key-values databases. At first we introduce key-value characteristics, advantages and disadvantages.
Then we analyze the major Key-Value data stores and finally we discuss about Dynamo DB.
In particular we consider how Dynamo DB: How is implemented
1. Motivation Background
2. Partitioning: Consistent Hashing
3. High Availability for writes: Vector Clocks
4. Handling temporary failures: Sloppy Quorum
5. Recovering from failures: Merkle Trees
6. Membership and failure detection: Gossip Protocol
AWS re:Invent 2016: How DataXu scaled its Attribution System to handle billio...Amazon Web Services
“Attribution" is the marketing term of art for allocating full or partial credit to individual advertisements that eventually lead to a purchase, sign up, download, or other desired consumer interaction. We'll share how we use DynamoDB at the core of our attribution system to store terabytes of advertising history data. The system is cost effective and dynamically scales from 0 to 300K requests per second on demand with predictable performance and low operational overhead.
AWS re:Invent 2016: How Toyota Racing Development Makes Racing Decisions in R...Amazon Web Services
Toyota Racing Development (TRD) developed a robust and highly performant real-time data analysis tool for professional racing. In this talk, learn how we structured a reliable, maintainable, decoupled architecture built around Amazon DynamoDB as both a streaming mechanism and a long-term persistent data store. In racing, milliseconds matter and even moments of downtime can cost a race. You'll see how we used DynamoDB together with Amazon Kinesis and Kinesis Firehose to build a real-time streaming data analysis tool for competitive racing.
AWS re:Invent 2016: 5 Security Automation Improvements You Can Make by Using ...Amazon Web Services
This session demonstrates 5 different security and compliance validation actions that you can perform using Amazon CloudWatch Events and AWS Config rules. This session focuses on the actual code for the various controls, actions, and remediation features, and how to use various AWS services and features to build them. The demos in this session include CIS Amazon Web Services Foundations validation; host-based AWS Config rules validation using AWS Lambda, SSH, and VPC-E; automatic creation and assigning of MFA tokens when new users are created; and automatic instance isolation based on SSH logons or VPC Flow Logs deny logs. This session focuses on code and live demos.
Amazon DynamoDB Design Patterns for Ultra-High Performance Apps (DAT304) | AW...Amazon Web Services
Learn how to deliver extremely low latency, fast performance and throughput for web-scale applications built on Amazon DynamoDB. We show you how to model data, maintain maximum throughput, drive analytics, and use secondary indexes with Amazon DynamoDB. You also hear how customers have built large-scale applications and the real-world lessons they've learned along the way.
AWS re:Invent 2016: Building IoT Applications with AWS and Amazon Alexa (HLC304)Amazon Web Services
Alexa, what is the Internet of Things? Now that technology is small enough to be embedded in everyday devices, Healthcare has an opportunity to exploit the extraordinary potential of connecting ordinary devices. In this presentation, we explain how to rapidly build an IoT system and how to drive the Cloud with your voice on an Amazon Echo. In addition to describing how to use Alexa, we explore using AWS IoT, Lambda, Amazon SNS, and DynamoDB.
If you’re familiar with relational databases, designing your app to use a fully-managed NoSQL database service like Amazon DynamoDB may be new to you. In this webinar, we’ll walk you through common NoSQL design patterns for a variety of applications to help you learn how to design a schema, store, and retrieve data with DynamoDB. We will discuss best practices with DynamoDB to develop IoT, AdTech, and gaming apps.
Amazon DynamoDB is a fully managed NoSQL database service for applications that need consistent, single-digit millisecond latency at any scale. This talk explores DynamoDB capabilities and benefits in detail and discusses how to get the most out of your DynamoDB database. We go over schema design best practices with DynamoDB across multiple use cases, including gaming, AdTech, IoT, and others. We also explore designing efficient indexes, scanning, and querying, and go into detail on a number of recently released features, including JSON document support, Streams, and more.
Keynote at Dockercon Europe Amsterdam Dec 4th, 2014.
Speeding up development with Docker.
Summary of some interesting web scale microservice architectures.
Please send me updates and corrections to the architecture summaries @adrianco
Thanks Adrian
Amazon DynamoDB is a key-value and document database that delivers single-digit millisecond performance at any scale. It's a fully managed, multiregion, multimaster, durable database with built-in security, backup and restore, and in-memory caching for internet-scale applications.
The Rise of Scanamo: Async Access for DynamoDB in ScalaKnoldus Inc.
My Knolx was on the "The Rise of Scanamo: Async Access for DynamoDB in Scala" which is a library to use DynamoDB with Scala in a simpler manner with less error-prone code.
The Rise Of Scanamo: Async Access For DynamoDB In ScalaKnoldus Inc.
With the radical changes in information management technology, there has come a great variety and volume of new kinds of data and new ways to deploy the enterprise application. Organizations like yours need to move from limited, fixed IT assets to far more flexible and scalable technologies so that you can scale much faster and provide greater customer intimacy with operational efficiency.
DynamoDB—Amazon's NOSQL database—is a great choice for organizations. It delivers a level of flexible scalability that meets the extreme demands of application scenarios.
+ Get familiar with DynamoDB
+ How Scanamo is useful for Scala developers for using the DynamoDB
+ Learn about DynamoDB Queries using Scanamo
In this presentation I am illustrating how and why InnodDB perform Merge and Split pages. I will also show what are the possible things to do to reduce the impact.
Introduction to InfluxDB, an Open Source Distributed Time Series Database by ...Hakka Labs
In this presentation, Paul introduces InfluxDB, a distributed time series database that he open sourced based on the backend infrastructure at Errplane. He talks about why you'd want a database specifically for time series and he covers the API and some of the key features of InfluxDB, including:
• Stores metrics (like Graphite) and events (like page views, exceptions, deploys)
• No external dependencies (self contained binary)
• Fast. Handles many thousands of writes per second on a single node
• HTTP API for reading and writing data
• SQL-like query language
• Distributed to scale out to many machines
• Built in aggregate and statistics functions
• Built in downsampling
Think Like Spark: Some Spark Concepts and a Use CaseRachel Warren
A deeper explanation of Spark's evaluation principals including lazy evaluation, the Spark execution environment, anatomy of a Spark Job (Tasks, Stages, Query execution plan) and presents one use case to demonstrate these concepts.
Amazon DynamoDB is a fast and flexible NoSQL database service for applications that need consistent, single-digit millisecond latency at any scale. It is a fully managed cloud database and supports both document and key-value store models. Its flexible data model and reliable performance make it a great fit for mobile, web, gaming, ad tech, IoT, and many other applications.
Learning Objectives:
Understand the differences between relational and non-relational databases
Learn about common use cases for DynamoDB across gaming, ad tech, IoT, and more
See how DynamoDB helps customers handle spikes in traffic and save development time for new feature launches
Who Should Attend:
Developers, IT Decision Makers, and Executives interested in learning more about Amazon Web Services’ serverless NoSQL service to scale mobile, web, IoT, ad tech, and gaming apps
Couchbase Data Platform | Big Data DemystifiedOmid Vahdaty
Couchbase is a popular open source NoSQL platform used by giants like Apple, LinkedIn, Walmart, Visa and many others and runs on-premise or in a public/hybrid/multi cloud.
Couchbase has a sub-millisecond K/V cache integrated with a document based DB, a unique and many more services and features.
In this session we will talk about the unique architecture of Couchbase, its unique N1QL language - a SQL-Like language that is ANSI compliant, the services and features Couchbase offers and demonstrate some of them live.
We will also discuss what makes Couchbase different than other popular NoSQL platforms like MongoDB, Cassandra, Redis, DynamoDB etc.
At the end we will talk about the next version of Couchbase (6.5) that will be released later this year and about Couchbase 7.0 that will be released next year.
Machine Learning Essentials Demystified part2 | Big Data DemystifiedOmid Vahdaty
achine Learning Essentials Abstract:
Machine Learning (ML) is one of the hottest topics in the IT world today. But what is it really all about?
In this session we will talk about what ML actually is and in which cases it is useful.
We will talk about a few common algorithms for creating ML models and demonstrate their use with Python. We will also take a peek at Deep Learning (DL) and Artificial Neural Networks and explain how they work (without too much math) and demonstrate DL model with Python.
The target audience are developers, data engineers and DBAs that do not have prior experience with ML and want to know how it actually works.
Machine Learning Essentials Demystified part1 | Big Data DemystifiedOmid Vahdaty
Machine Learning Essentials Abstract:
Machine Learning (ML) is one of the hottest topics in the IT world today. But what is it really all about?
In this session we will talk about what ML actually is and in which cases it is useful.
We will talk about a few common algorithms for creating ML models and demonstrate their use with Python. We will also take a peek at Deep Learning (DL) and Artificial Neural Networks and explain how they work (without too much math) and demonstrate DL model with Python.
The target audience are developers, data engineers and DBAs that do not have prior experience with ML and want to know how it actually works.
The technology of fake news between a new front and a new frontier | Big Dat...Omid Vahdaty
קוראים לי ניצן אור קדראי ואני עומדת בצומת המעניינת שבין טכנולוגיה, מדיה ואקטיביזם.
בארבע וחצי השנים האחרונות אני עובדת בידיעות אחרונות, בהתחלה כמנהלת המוצר של אפליקציית ynet וכיום כמנהלת החדשנות.
הייתי שותפה בהקמת עמותת סטארט-אח, עמותה המספקת שירותי פיתוח ומוצר עבור עמותות אחרות, ולאחרונה מתעסקת בהקמת קהילה שמטרתה לחקור את ההיבטים הטכנולוגיים של תופעת הפייק ניוז ובניית כלים אפליקטיביים לצורך ניהול חכם של המלחמה בתופעה.
ההרצאה תדבר על תופעת הפייק ניוז. נתמקד בטכנולוגיה שמאפשרת את הפצת הפייק ניוז ונראה דוגמאות לשימוש בטכנולוגיה זו.
נבחן את היקף התופעה ברשתות החברתיות ונלמד איך ענקיות הטכנולוגיה מנסות להילחם בה.
Big Data in 200 km/h | AWS Big Data Demystified #1.3 Omid Vahdaty
What we're about
A while ago I entered the challenging world of Big Data. As an engineer, at first, I was not so impressed with this field. As time went by, I realised more and more, The technological challenges in this area are too great to master by one person. Just look at the picture in this articles, it only covers a small fraction of the technologies in the Big Data industry…
Consequently, I created a meetup detailing all the challenges of Big Data, especially in the world of cloud. I am using AWS infrastructure to answer the basic questions of anyone starting their way in the big data world.
how to transform data (TXT, CSV, TSV, JSON) into Parquet, ORCwhich technology should we use to model the data ? EMR? Athena? Redshift? Spectrum? Glue? Spark? SparkSQL?how to handle streaming?how to manage costs?Performance tips?Security tip?Cloud best practices tips?
Some of our online materials:
Website:
https://big-data-demystified.ninja/
Youtube channels:
https://www.youtube.com/channel/UCzeGqhZIWU-hIDczWa8GtgQ?view_as=subscriber
https://www.youtube.com/channel/UCMSdNB0fGmX5dXI7S7Y_LFA?view_as=subscriber
Meetup:
https://www.meetup.com/AWS-Big-Data-Demystified/
https://www.meetup.com/Big-Data-Demystified
Facebook Group :
https://www.facebook.com/groups/amazon.aws.big.data.demystified/
Facebook page (https://www.facebook.com/Amazon-AWS-Big-Data-Demystified-1832900280345700/)
Audience:
Data Engineers
Data Science
DevOps Engineers
Big Data Architects
Solution Architects
CTO
VP R&D
Making your analytics talk business | Big Data DemystifiedOmid Vahdaty
MAKING YOUR ANALYTICS TALK BUSINESS
Aligning your analysis to the business is fundamental for all types of analytics (digital or product analytics, business intelligence, etc) and is vertical- and tool agnostic. In this talk we will build on the discussion that was started in the previous meetup, and will discuss how analysts can learn to derive their stakeholders' expectations, how to shift from metrics to "real" KPIs, and how to approach an analysis in order to create real impact.
This session is primarily geared towards those starting out into analytics, practitioners who feel that they are still struggling to prove their value in the organization or simply folks who want to power up their reporting and recommendation skills. If you are already a master at aligning your analysis to the business, you're most welcome as well: join us to share your experiences so that we can all learn from each other and improve!
Bios:
Eliza Savov - Eliza is the team lead of the Customer Experience and Analytics team at Clicktale, the worldwide leader in behavioral analytics. She has extensive experience working with data analytics, having previously worked at Clicktale as a senior customer experience analyst, and as a product analyst at Seeking Alpha.
BI STRATEGY FROM A BIRD'S EYE VIEW (How to become a trusted advisor) | Omri H...Omid Vahdaty
In the talk we will discuss how to break down the company’s overall goals all the way to your BI team’s daily activities in 3 simple stages:
1. Understanding the path to success - Creating a revenue model
2. Gathering support and strategizing - Structuring a team
3. Executing - Tracking KPIs
Bios:
Omri Halak -Omri is the director of business operations at Logz.io, an intelligent and scalable machine data analytics platform built on ELK & Grafana that empowers engineers to monitor, troubleshoot, and secure mission-critical applications more effectively. In this position, Omri combines actionable business insights from the BI side with fast and effective delivery on the Operations side. Omri has ample experience connecting data with business, with previous positions at SimilarWeb as a business analyst, at Woobi as finance director, and as Head of State Guarantees at Israel Ministry of Finance.
AI and Big Data in Health Sector Opportunities and challenges | Big Data Demy...Omid Vahdaty
Lecturer has Deep experience defining Cloud computing, security models for IaaS, PaaS, and SaaS architectures specifically as the architecture relates to IAM. Deep Experience Defining Privacy protection Policy, a big fan of GDPR interpretation.
DeelExperience in Information security, Defining Healthcare security best practices including AI and Big Data, IT Security and ICS security and privacy controls in the industrial environments.
Deep knowledge of security frameworks such as Cloud Security Alliance (CSA), International Organization for Standardization (ISO), National Institute of Standards and Technology (NIST), IBM ITCS104 etc.
What Will You learn:
Every day, the website collects a huge amount of data. The data allows to analyze the behavior of Internet users, their interests, their purchasing behavior and the conversion rates. In order to increase business, big data offers the tools to analyze and process data in order to reveal competitive advantages from the data.
What Healthcare has to do with Big Data
How AI can assist in patient care?
Why some are afraid? Are there any dangers?
Aerospike meetup july 2019 | Big Data DemystifiedOmid Vahdaty
Building a low latency (sub millisecond), high throughput database that can handle big data AND linearly scale is not easy - but we did it anyway...
In this session we will get to know Aerospike, an enterprise distributed primary key database solution.
- We will do an introduction to Aerospike - basic terms, how it works and why is it widely used in mission critical systems deployments.
- We will understand the 'magic' behind Aerospike ability to handle small, medium and even Petabyte scale data, and still guarantee predictable performance of sub-millisecond latency
- We will learn how Aerospike devops is different than other solutions in the market, and see how easy it is to run it on cloud environments as well as on premise.
We will also run a demo - showing a live example of the performance and self-healing technologies the database have to offer.
ALIGNING YOUR BI OPERATIONS WITH YOUR CUSTOMERS' UNSPOKEN NEEDS, by Eyal Stei...Omid Vahdaty
ALIGNING YOUR BI OPERATIONS WITH YOUR CUSTOMERS' UNSPOKEN NEEDS
-Learn how to connect BI and product management to solve business problems
-Discover how to lead clients to ask the right questions to get the data and insight they really want
-Get pointers on saving your time and your company's resources by understanding what your customers need, not what they ask for
AWS Big Data Demystified #1.2 | Big Data architecture lessons learned Omid Vahdaty
A while ago I entered the challenging world of Big Data. As an engineer, at first, I was not so impressed with this field. As time went by, I realised more and more, The technological challenges in this area are too great to master by one person. Just look at the picture in this articles, it only covers a small fraction of the technologies in the Big Data industry…
Consequently, I created a meetup detailing all the challenges of Big Data, especially in the world of cloud. I am using AWS & GCP and Data Center infrastructure to answer the basic questions of anyone starting their way in the big data world.
how to transform data (TXT, CSV, TSV, JSON) into Parquet, ORC,AVRO which technology should we use to model the data ? EMR? Athena? Redshift? Spectrum? Glue? Spark? SparkSQL? GCS? Big Query? Data flow? Data Lab? tensor flow? how to handle streaming? how to manage costs? Performance tips? Security tip? Cloud best practices tips?
In this meetup we shall present lecturers working on several cloud vendors, various big data platforms such hadoop, Data warehourses , startups working on big data products. basically - if it is related to big data - this is THE meetup.
Some of our online materials (mixed content from several cloud vendor):
Website:
https://big-data-demystified.ninja (under construction)
Meetups:
https://www.meetup.com/Big-Data-Demystified
https://www.meetup.com/AWS-Big-Data-Demystified/
You tube channels:
https://www.youtube.com/channel/UCMSdNB0fGmX5dXI7S7Y_LFA?view_as=subscriber
https://www.youtube.com/channel/UCzeGqhZIWU-hIDczWa8GtgQ?view_as=subscriber
Audience:
Data Engineers
Data Science
DevOps Engineers
Big Data Architects
Solution Architects
CTO
VP R&D
AWS Big Data Demystified #3 | Zeppelin + spark sql, jdbc + thrift, ganglia, r...Omid Vahdaty
AWS Big Data Demystified is all about knowledge sharing b/c knowledge should be given for free. in this lecture we will dicusss the advantages of working with Zeppelin + spark sql, jdbc + thrift, ganglia, r+ spark r + livy, and a litte bit about ganglia on EMR.\
subscribe to you youtube channel to see the video of this lecture:
https://www.youtube.com/channel/UCzeGqhZIWU-hIDczWa8GtgQ?view_as=subscriber
Amazon aws big data demystified | Introduction to streaming and messaging flu...Omid Vahdaty
amazon aws big data demystified meetup:
https://www.meetup.com/AWS-Big-Data-Demystified/
Introduction to streaming and messaging flume kafka sqs kinesis
AWS Big Data Demystified #1: Big data architecture lessons learned Omid Vahdaty
AWS Big Data Demystified #1: Big data architecture lessons learned . a quick overview of a big data techonoligies, which were selected and disregard in our company
The video: https://youtu.be/l5KmaZNQxaU
dont forget to subcribe to the youtube channel
The website: https://amazon-aws-big-data-demystified.ninja/
The meetup : https://www.meetup.com/AWS-Big-Data-Demystified/
The facebook group : https://www.facebook.com/Amazon-AWS-Big-Data-Demystified-1832900280345700/
CW RADAR, FMCW RADAR, FMCW ALTIMETER, AND THEIR PARAMETERSveerababupersonal22
It consists of cw radar and fmcw radar ,range measurement,if amplifier and fmcw altimeterThe CW radar operates using continuous wave transmission, while the FMCW radar employs frequency-modulated continuous wave technology. Range measurement is a crucial aspect of radar systems, providing information about the distance to a target. The IF amplifier plays a key role in signal processing, amplifying intermediate frequency signals for further analysis. The FMCW altimeter utilizes frequency-modulated continuous wave technology to accurately measure altitude above a reference point.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
#vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore#blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #blackmagicforlove #blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #Amilbabainuk #amilbabainspain #amilbabaindubai #Amilbabainnorway #amilbabainkrachi #amilbabainlahore #amilbabaingujranwalan #amilbabainislamabad
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
2. Concepts
● Schema less - other than the primary key attributes, you do not need to define any attributes or data types at table creation time.
● Table == collection/Table from OLTP
● Item == “Row in a table”.
● Attributes == “col of a row ” in a table. May change from item to item.
● Primary key ==a primary key uniquely identifies each item in the table, so that no two items can have the same key. 2 types
○ Partitions key - simple hash function that maps item into specific partition
○ Partition + sort key - A composite primary key
■ Hash function maps item into partition. Also called hash attribute
■ The item will be sorted via sort key. Also called range attribute.
● Secondary Index. Non key index. Another way to read data. Faster? :)
○ Global secondary index – an index with a partition key and sort key that can be different from those on the table.
○ Local secondary index – an index that has the same partition key as the table, but a different sort key.
3. DynamoDB stream
Optional feature : Each event is represented by a stream record. If you enable a stream on a table, DynamoDB Streams will
write a stream record whenever one of the following events occurs:
If a new item is added to the table, the stream captures an image of the entire item, including all of its attributes.
If an item is updated, the stream captures the "before" and "after" image of any attributes that were modified in the item.
If an item is deleted from the table, the stream captures an image of the entire item before it was deleted.
Lifetime of 24 hours
Actions
a. ListStreams
b. DescribeStream
c. GetShardIterator
d. GetRecords
4. DynamoDB API
● Control Plane: create and manage tables:
○ CreateTable
○ DescribeTable
○ ListTables
○ UpdateTable
○ DeleteTable
● Data Plane : actions on data:
○ create, read, update, and delete
5. DynamoDB API
● Data Plane : actions on data:
○ Create
■ putItem - only 1 item, must specify primary key
■ batchWriteItem - write upto 25 item in transaction
○ Read
■ getItem - get only 1 item
■ batchGetItems - get upto 100 items.
■ Query
■ Scan
○ Update - updateItem, 1 item, spesify primary ket, atomic counters to save writes? ;)
○ Delete, deleteItem upto 1 item, BatchDeleteItems. (upto 25)
6. DynamoDB data types
Scalar Types – A scalar type can represent exactly one value. The scalar types are number, string, binary, Boolean,
and null.
Document Types – A document type can represent a complex structure with nested attributes—such as you would
find in a JSON document. The document types are list and map.
Set Types – A set type can represent multiple scalar values. The set types are string set, number set, and binary set.
7. Documents?
● complex data structures up to 32 levels deep.
● size limit (400 KB).
● List:
○ A list type attribute can store an ordered collection of values
○ E.g FavoriteThings: ["Cookies", "Coffee", 3.14159]
● Map - A map type attribute can store an unordered collection of name-value pairs, ideal for json.
○ {
Day: "Monday",
UnreadEmails: 42,
ItemsOnMyDesk: [
"Coffee Cup",
"Telephone",
{
Pens: { Quantity : 3},
Pencils: { Quantity : 2},
Erasers: { Quantity : 1}
}
]
}
8. Sets?
● item size limit (400 KB).
● DynamoDB does not support empty sets.
● Example (String Set, Number Set, and Binary Set)
● ["Black", "Green" ,"Red"]
[42.2, -19, 7.5, 3.14]
["U3Vubnk=", "UmFpbnk=", "U25vd3k="]
10. Partitions?
● DynamoDB stores data in partitions.
● A partition is an allocation of storage for a table
● backed by solid-state drives (SSDs)
● Multi AZ - automatically replicated across multiple Availability Zones within an AWS region.
● Partition management is handled automatically by DynamoDB
● Partion key in a table - hash map function to map an item to a partion
13. Getting started
● Download(!) dynamo to your laptop for training:
http://docs.aws.amazon.com/amazondynamodb/latest/gettingstartedguide/Ge
ttingStarted.Download.html
● Start server
○ java -Djava.library.path=./DynamoDBLocal_lib -jar DynamoDBLocal.jar -sharedDb -inMemory
○ Port 8000
14. Java and DynamoDB
Setup access key , secret key
Setup JAVA and dynamo DB:
http://docs.aws.amazon.com/sdk-for-java/v1/developer-guide/setup-install.html
Easy to get started with Ecplise, didnt find anything supported for Intellij
https://www.eclipse.org/downloads
Setup AWS tool kit
http://docs.aws.amazon.com/toolkit-for-eclipse/v1/user-guide/setup-install.html
Setup Java SDK:
http://docs.aws.amazon.com/sdk-for-java/v1/developer-guide/setup-install.html
15. Java and DynamoDB
Using the SDK:
add the full path to the lib and third-party directories to the dependencies in your build file, and add them to your java
CLASSPATH to run your code.
Working with local (onsite) installation of dynamodb:
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/DynamoDBLocal.html
○ java -Djava.library.path=./DynamoDBLocal_lib -jar DynamoDBLocal.jar -sharedDb
Command line options for local DynamoDB (in memory, path to save files etc):
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/DynamoDBLocal.html
Specify local end point example:
https://github.com/aws/aws-sdk-java/issues/330
16. Sample Code
final String USAGE = "n" +"Usage:n" + " CreateTable <table>nn" + "Where:n" + " table - the table to create.nn" + "Example:n" + "CreateTable Hello
if (args.length < 1) {
System.out.println(USAGE);
System.exit(1);
} /* Read the name from command args */
String table_name = args[0];
System.out.format(
"Creating table "%s" with a simple primary key: "Name".n", table_name);
17. Sample Code
CreateTableRequest request = new CreateTableRequest()
.withAttributeDefinitions(new AttributeDefinition("Name", ScalarAttributeType.S))
.withKeySchema(new KeySchemaElement("Name", KeyType.HASH))
.withProvisionedThroughput(new ProvisionedThroughput(new Long(1), new Long(1)))
.withTableName(table_name);
final AmazonDynamoDBClient dynamoDB = new AmazonDynamoDBClient();
dynamoDB.setEndpoint("http://127.0.0.1:8000");
dynamoDB.setSignerRegionOverride("eu-west-1");