Rails on HBase

•

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Zachary Pinter and Tony Hillerson from EffectiveUI presented at RailsConf 2011. This presentation covers the basics of HBase, what type of apps it works well with, and how to use HBase with Rails.

Technology

Rails on HBase

Zachary Pinter and Tony Hillerson
RailsConf 2011

What are the
tradeoffs that HBase
makes?

Why HBase is
probably the wrong
choice for your app

Why HBase might be
the right choice for
your app

This is not a guide to
setting up a
production HBase
cluster
*See http://cloudera.com

Tables

column

key core:link

row
llb0ga http://google.com

http://en.oreilly.com/rails2011/public/
llb260
schedule/detail/17886

Column Families

core column family stats column family

key core:link stats:hits

llb0ga http://google.com 100504

http://en.oreilly.com/rails2011/
llb260 2
public/schedule/detail/17886

Column Families
Must be deﬁned at creation or added to schema
later
Should group data accessed and sized similarly

Columns
Can be dynamically added given that the family
exists
Stored as a byte array - do what you need with it

Regions

master
llb0ga lld92q
... ...
llbee9 lq1rro

Regionserver Regionserver

Main Operations
Get
Put
Incr
Delete
Scan

hbase shell

ruby-1.9.2-p180 :002 > status

1 servers, 0 dead, 1.0000 average load

ruby-1.9.2-p180 :003 > (1..10).each{ status }

1 servers, 0 dead, 3.0000 average load

1 servers, 0 dead, 3.0000 average load

1 servers, 0 dead, 3.0000 average load

1 servers, 0 dead, 3.0000 average load

1 servers, 0 dead, 3.0000 average load

1 servers, 0 dead, 3.0000 average load

1 servers, 0 dead, 3.0000 average load

1 servers, 0 dead, 3.0000 average load

1 servers, 0 dead, 3.0000 average load

1 servers, 0 dead, 3.0000 average load

=> 1..10

ruby-1.9.2-p180 :004 >

What are the tradeoffs that
HBase makes?
NoSQL = Tradeoffs

Highly Distributed
Pros Cons

• Built-in sharding • Makes joins difﬁcult/impossible
• No single server holds all the data • Limited real-time queries/sorting
• Different servers operate on different
slices of the data

Sorted Row Keys
Bytearray keys
Any kind of data you want
Sorted in byte order
All row access through the key

Sorted Row Keys
Pros Cons

• Real-time random lookups by key • Conﬂates unique identiﬁer with default
• Real-time range queries sort
• Keys are an integral part of schema
design, requiring extra consideration

Map / Reduce
Pros Cons

• Scales linearly: more servers = faster • Scans every row per query *
response times • Not real-time (batch operation)
• Operates on huge datasets (billions of
rows)
• Works well with dynamic/non-uniform
schemas

HBase vs. X
http://nosql-database.org
http://www.sevenweeks.org/
Seven Databases in Seven Weeks
Eric Redmond
Don’t Miss His Talk!!

HBase Limitations
Limited real-time queries (key lookup, range lookup)
Limited sorting (one default sort per table)
Limited transactions
Manual indexing
Joins/Normalization
Storage of large binary data *

HBase Requirements
• At least 5 Servers (Zookeeper, Region Server, Name Nodes, Data Nodes, etc)
• Memory Intensive (2-4gb bar minimum per server, depending on server role)
• CPU Intensive
• Rough EC2 Cost:
5 c1.xlarge reserved for 1 year
= over $850/month
(not counting bandwidth!)

Large data sets
Ability to aggregate and analyze billions of rows
Starts to shine when relational databases break
down
Is your db already sharded?
Are you using SQL queries that take hours to run?

Hadoop Integration
HDFS for storing ﬁles
Native Map/Reduce
Supports data locality
Doesn’t require data to be transferred

Flexible schema
Supports non-heterogeneous data through column
families with mixed key/value pairs
Ability to refactor the data store via map/reduce
(beats a multi-day ALTER TABLE command)

hbase-stargate
https://github.com/greglu/hbase-stargate
Uses Stargate, HBase REST server

Rhino
https://github.com/sqs/rhino/
Thrift API
Seems to be abandoned?

Massive Record
https://github.com/CompanyBook/massive_record
It works!
Uses Thrift API

Source
Demo source code
github.com/effectiveui/jruby-hbase-demo
github.com/effectiveui/rails-hbase-massive-record

Getting Set Up
(Mac) brew install hbase
Cloudera VM
http://bit.ly/dSfPa9

Thank You!
Zachary: @zpinter
Tony: @thillerson
EffectiveUI.com

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As privacy and data protection regulations evolve rapidly, organizations operating in multiple jurisdictions face mounting challenges to ensure compliance and safeguard customer data. With state-specific privacy laws coming up in multiple states this year, it is essential to understand what their unique data protection regulations will require clearly. How will data privacy evolve in the US in 2024? How to stay compliant? Our panellists will guide you through the intricacies of these states' specific data privacy laws, clarifying complex legal frameworks and compliance requirements. This webinar will review: - The essential aspects of each state's privacy landscape and the latest updates - Common compliance challenges faced by organizations operating in multiple states and best practices to achieve regulatory adherence - Valuable insights into potential changes to existing regulations and prepare your organization for the evolving landscape

TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments

TrustArc

In this session, we will delve into strategic approaches for optimizing knowledge management within Microsoft 365, amidst the evolving landscape of Copilot. From leveraging automatic metadata classification and permission governance with SharePoint Premium, to unlocking Viva Engage for the cultivation of knowledge and communities, you will gain actionable insights to bolster your organization's knowledge-sharing initiatives. In this session, we will also explore how to facilitate solutions to enable your employees to find answers and expertise within Microsoft 365. You will leave equipped with practical techniques and a deeper understanding of how there is more to effective knowledge management than just enabling Copilot, but building actual solutions to prepare the knowledge that Copilot and your employees can use.

Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...

Drew Madelung

Following the popularity of "Cloud Revolution: Exploring the New Wave of Serverless Spatial Data," we're thrilled to announce this much-anticipated encore webinar. In this sequel, we'll dive deeper into the Cloud-Native realm by uncovering practical applications and FME support for these new formats, including COGs, COPC, FlatGeoBuf, GeoParquet, STAC, and ZARR. Building on the foundation laid by industry leaders Michelle Roby of Radiant Earth and Chris Holmes of Planet in the first webinar, this second part offers an in-depth look at the real-world application and behind-the-scenes dynamics of these cutting-edge formats. We will spotlight specific use-cases and workflows, showcasing their efficiency and relevance in practical scenarios. Discover the vast possibilities each format holds, highlighted through detailed discussions and demonstrations. Our expert speakers will dissect the key aspects and provide critical takeaways for effective use, ensuring attendees leave with a thorough understanding of how to apply these formats in their own projects. Elevate your understanding of how FME supports these cutting-edge technologies, enhancing your ability to manage, share, and analyze spatial data. Whether you're building on knowledge from our initial session or are new to the serverless spatial data landscape, this webinar is your gateway to mastering cloud-native formats in your workflows.

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME

Safe Software

Discord is a free app offering voice, video, and text chat functionalities, primarily catering to the gaming community. It serves as a hub for users to create and join servers tailored to their interests. Discord’s ecosystem comprises servers, each functioning as a distinct online community with its own channels dedicated to specific topics or activities. Users can engage in text-based discussions, voice calls, or video chats within these channels. Understanding Discord Servers Discord servers are virtual spaces where users congregate to interact, share content, and build communities. Servers may revolve around gaming, hobbies, interests, or fandoms, providing a platform for like-minded individuals to connect. Communication Features Discord offers a range of communication tools, including text channels for messaging, voice channels for real-time audio conversations, and video channels for face-to-face interactions. These features facilitate seamless communication and collaboration. What Does NSFW Mean? The acronym NSFW stands for “Not Safe For Work,” indicating content that may be inappropriate for professional or public settings. NSFW Content NSFW content encompasses material that is sexually explicit, violent, or otherwise graphic in nature. It often includes nudity, profanity, or depictions of sensitive topics.

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

UK Journal

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Increase engagement and revenue with Muvi Live Paywall! In this presentation, we will explore the five key benefits of using Muvi Live Paywall to monetize your live streams. You'll learn how Muvi Live Paywall can help you: Monetize your live content easily: Set up pay-per-view access to your live streams and start generating revenue from your content. Increase audience engagement: Provide exclusive, premium content behind the paywall to keep your viewers engaged. Gain valuable viewer insights: Track viewer data and analytics to better understand your audience and tailor your content accordingly. Reduce content piracy: Muvi Live Paywall's security features help protect your content from unauthorized distribution. Streamline your workflow: The all-in-one platform simplifies the process of managing and monetizing your live streams. With Muvi Live Paywall, you can take control of your live stream monetization and create a sustainable business model for your content. Learn more about Muvi Live Paywall and start generating revenue from your live streams today!

Top 5 Benefits OF Using Muvi Live Paywall For Live Streams

Roshan Dwivedi

Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving

Edi Saputra

Imagine a world where information flows as swiftly as thought itself, making decision-making as fluid as the data driving it. Every moment is critical, and the right tools can significantly boost your organization’s performance. The power of real-time data automation through FME can turn this vision into reality. Aimed at professionals eager to leverage real-time data for enhanced decision-making and efficiency, this webinar will cover the essentials of real-time data and its significance. We’ll explore: FME’s role in real-time event processing, from data intake and analysis to transformation and reporting An overview of leveraging streams vs. automations FME’s impact across various industries highlighted by real-life case studies Live demonstrations on setting up FME workflows for real-time data Practical advice on getting started, best practices, and tips for effective implementation Join us to enhance your skills in real-time data automation with FME, and take your operational capabilities to the next level.

From Event to Action: Accelerate Your Decision Making with Real-Time Automation

Safe Software

Effective data discovery is crucial for maintaining compliance and mitigating risks in today's rapidly evolving privacy landscape. However, traditional manual approaches often struggle to keep pace with the growing volume and complexity of data. Join us for an insightful webinar where industry leaders from TrustArc and Privya will share their expertise on leveraging AI-powered solutions to revolutionize data discovery. You'll learn how to: - Effortlessly maintain a comprehensive, up-to-date data inventory - Harness code scanning insights to gain complete visibility into data flows leveraging the advantages of code scanning over DB scanning - Simplify compliance by leveraging Privya's integration with TrustArc - Implement proven strategies to mitigate third-party risks Our panel of experts will discuss real-world case studies and share practical strategies for overcoming common data discovery challenges. They'll also explore the latest trends and innovations in AI-driven data management, and how these technologies can help organizations stay ahead of the curve in an ever-changing privacy landscape.

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc

The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.

Artificial Intelligence: Facts and Myths

Joaquim Jorge

Strategies for Landing an Oracle DBA Job as a Fresher

Remote DBA Services

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