This document provides instructions and an application form for the State Level National Talent Search Examination 2018-2019 for students in Class 10. Key details include:
- The exam date is November 4, 2018.
- The agency conducting the NTSE exam is the Rajya Shiksha Kendra in Bhopal, Madhya Pradesh.
- The application form requests information such as the candidate's name, school details, family details, disability status, and parental income.
- The form must be signed by the candidate and principal/head of the institution. It includes instructions on correctly filling out and submitting the form before the deadline.
This document appears to be a multi-page PDF file titled "PC_12.1-4_Notes.pdf" that contains notes or information across 6 numbered pages. However, without being able to view the actual contents of the PDF pages, the summary is limited to just the file name and number of pages it contains.
This document appears to be notes from multiple pages of a file called "PC_1.4-5_Notes.pdf". However, without being able to view the actual file contents, I am unable to determine the essential information or high-level topic of the notes. The summary provided does not contain enough contextual details to extract meaningful insights about the document.
This document appears to be a 12 page PDF file titled "PC_2.6_Notes P2_Rational.pdf" that likely contains details and rationale related to a programming concept or technical specification, but without being able to view the file contents, no meaningful high-level summary can be provided.
This 6-page document discusses half angles and their relationship to trigonometric functions. It defines half angles and shows how the trig functions of a half angle can be defined in terms of the trig functions of the original angle. Examples are provided to demonstrate how to use half angle identities to simplify expressions involving trig functions.
This document appears to be a 10 page PDF titled "PC_4.1_Notes.pdf" that likely contains notes or information related to a personal computing topic labeled "PC_4.1". The PDF spans 10 sequentially numbered pages, but without accessing and reviewing the full document contents, no more specific summarization can be provided.
This document provides instructions and an application form for the State Level National Talent Search Examination 2018-2019 for students in Class 10. Key details include:
- The exam date is November 4, 2018.
- The agency conducting the NTSE exam is the Rajya Shiksha Kendra in Bhopal, Madhya Pradesh.
- The application form requests information such as the candidate's name, school details, family details, disability status, and parental income.
- The form must be signed by the candidate and principal/head of the institution. It includes instructions on correctly filling out and submitting the form before the deadline.
This document appears to be a multi-page PDF file titled "PC_12.1-4_Notes.pdf" that contains notes or information across 6 numbered pages. However, without being able to view the actual contents of the PDF pages, the summary is limited to just the file name and number of pages it contains.
This document appears to be notes from multiple pages of a file called "PC_1.4-5_Notes.pdf". However, without being able to view the actual file contents, I am unable to determine the essential information or high-level topic of the notes. The summary provided does not contain enough contextual details to extract meaningful insights about the document.
This document appears to be a 12 page PDF file titled "PC_2.6_Notes P2_Rational.pdf" that likely contains details and rationale related to a programming concept or technical specification, but without being able to view the file contents, no meaningful high-level summary can be provided.
This 6-page document discusses half angles and their relationship to trigonometric functions. It defines half angles and shows how the trig functions of a half angle can be defined in terms of the trig functions of the original angle. Examples are provided to demonstrate how to use half angle identities to simplify expressions involving trig functions.
This document appears to be a 10 page PDF titled "PC_4.1_Notes.pdf" that likely contains notes or information related to a personal computing topic labeled "PC_4.1". The PDF spans 10 sequentially numbered pages, but without accessing and reviewing the full document contents, no more specific summarization can be provided.
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
End-to-end pipeline agility - Berlin Buzzwords 2024Lars Albertsson
We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
The Ipsos - AI - Monitor 2024 Report.pdfSocial Samosa
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
2024 State of Marketing Report – by HubspotMarius Sescu
https://www.hubspot.com/state-of-marketing
· Scaling relationships and proving ROI
· Social media is the place for search, sales, and service
· Authentic influencer partnerships fuel brand growth
· The strongest connections happen via call, click, chat, and camera.
· Time saved with AI leads to more creative work
· Seeking: A single source of truth
· TLDR; Get on social, try AI, and align your systems.
· More human marketing, powered by robots
ChatGPT is a revolutionary addition to the world since its introduction in 2022. A big shift in the sector of information gathering and processing happened because of this chatbot. What is the story of ChatGPT? How is the bot responding to prompts and generating contents? Swipe through these slides prepared by Expeed Software, a web development company regarding the development and technical intricacies of ChatGPT!
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
End-to-end pipeline agility - Berlin Buzzwords 2024Lars Albertsson
We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
The Ipsos - AI - Monitor 2024 Report.pdfSocial Samosa
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
2024 State of Marketing Report – by HubspotMarius Sescu
https://www.hubspot.com/state-of-marketing
· Scaling relationships and proving ROI
· Social media is the place for search, sales, and service
· Authentic influencer partnerships fuel brand growth
· The strongest connections happen via call, click, chat, and camera.
· Time saved with AI leads to more creative work
· Seeking: A single source of truth
· TLDR; Get on social, try AI, and align your systems.
· More human marketing, powered by robots
ChatGPT is a revolutionary addition to the world since its introduction in 2022. A big shift in the sector of information gathering and processing happened because of this chatbot. What is the story of ChatGPT? How is the bot responding to prompts and generating contents? Swipe through these slides prepared by Expeed Software, a web development company regarding the development and technical intricacies of ChatGPT!
Product Design Trends in 2024 | Teenage EngineeringsPixeldarts
The realm of product design is a constantly changing environment where technology and style intersect. Every year introduces fresh challenges and exciting trends that mold the future of this captivating art form. In this piece, we delve into the significant trends set to influence the look and functionality of product design in the year 2024.
How Race, Age and Gender Shape Attitudes Towards Mental HealthThinkNow
Mental health has been in the news quite a bit lately. Dozens of U.S. states are currently suing Meta for contributing to the youth mental health crisis by inserting addictive features into their products, while the U.S. Surgeon General is touring the nation to bring awareness to the growing epidemic of loneliness and isolation. The country has endured periods of low national morale, such as in the 1970s when high inflation and the energy crisis worsened public sentiment following the Vietnam War. The current mood, however, feels different. Gallup recently reported that national mental health is at an all-time low, with few bright spots to lift spirits.
To better understand how Americans are feeling and their attitudes towards mental health in general, ThinkNow conducted a nationally representative quantitative survey of 1,500 respondents and found some interesting differences among ethnic, age and gender groups.
Technology
For example, 52% agree that technology and social media have a negative impact on mental health, but when broken out by race, 61% of Whites felt technology had a negative effect, and only 48% of Hispanics thought it did.
While technology has helped us keep in touch with friends and family in faraway places, it appears to have degraded our ability to connect in person. Staying connected online is a double-edged sword since the same news feed that brings us pictures of the grandkids and fluffy kittens also feeds us news about the wars in Israel and Ukraine, the dysfunction in Washington, the latest mass shooting and the climate crisis.
Hispanics may have a built-in defense against the isolation technology breeds, owing to their large, multigenerational households, strong social support systems, and tendency to use social media to stay connected with relatives abroad.
Age and Gender
When asked how individuals rate their mental health, men rate it higher than women by 11 percentage points, and Baby Boomers rank it highest at 83%, saying it’s good or excellent vs. 57% of Gen Z saying the same.
Gen Z spends the most amount of time on social media, so the notion that social media negatively affects mental health appears to be correlated. Unfortunately, Gen Z is also the generation that’s least comfortable discussing mental health concerns with healthcare professionals. Only 40% of them state they’re comfortable discussing their issues with a professional compared to 60% of Millennials and 65% of Boomers.
Race Affects Attitudes
As seen in previous research conducted by ThinkNow, Asian Americans lag other groups when it comes to awareness of mental health issues. Twenty-four percent of Asian Americans believe that having a mental health issue is a sign of weakness compared to the 16% average for all groups. Asians are also considerably less likely to be aware of mental health services in their communities (42% vs. 55%) and most likely to seek out information on social media (51% vs. 35%).
AI Trends in Creative Operations 2024 by Artwork Flow.pdfmarketingartwork
Creative operations teams expect increased AI use in 2024. Currently, over half of tasks are not AI-enabled, but this is expected to decrease in the coming year. ChatGPT is the most popular AI tool currently. Business leaders are more actively exploring AI benefits than individual contributors. Most respondents do not believe AI will impact workforce size in 2024. However, some inhibitions still exist around AI accuracy and lack of understanding. Creatives primarily want to use AI to save time on mundane tasks and boost productivity.
Organizational culture includes values, norms, systems, symbols, language, assumptions, beliefs, and habits that influence employee behaviors and how people interpret those behaviors. It is important because culture can help or hinder a company's success. Some key aspects of Netflix's culture that help it achieve results include hiring smartly so every position has stars, focusing on attitude over just aptitude, and having a strict policy against peacocks, whiners, and jerks.
PEPSICO Presentation to CAGNY Conference Feb 2024Neil Kimberley
PepsiCo provided a safe harbor statement noting that any forward-looking statements are based on currently available information and are subject to risks and uncertainties. It also provided information on non-GAAP measures and directing readers to its website for disclosure and reconciliation. The document then discussed PepsiCo's business overview, including that it is a global beverage and convenient food company with iconic brands, $91 billion in net revenue in 2023, and nearly $14 billion in core operating profit. It operates through a divisional structure with a focus on local consumers.
Content Methodology: A Best Practices Report (Webinar)contently
This document provides an overview of content methodology best practices. It defines content methodology as establishing objectives, KPIs, and a culture of continuous learning and iteration. An effective methodology focuses on connecting with audiences, creating optimal content, and optimizing processes. It also discusses why a methodology is needed due to the competitive landscape, proliferation of channels, and opportunities for improvement. Components of an effective methodology include defining objectives and KPIs, audience analysis, identifying opportunities, and evaluating resources. The document concludes with recommendations around creating a content plan, testing and optimizing content over 90 days.
How to Prepare For a Successful Job Search for 2024Albert Qian
The document provides guidance on preparing a job search for 2024. It discusses the state of the job market, focusing on growth in AI and healthcare but also continued layoffs. It recommends figuring out what you want to do by researching interests and skills, then conducting informational interviews. The job search should involve building a personal brand on LinkedIn, actively applying to jobs, tailoring resumes and interviews, maintaining job hunting as a habit, and continuing self-improvement. Once hired, the document advises setting new goals and keeping skills and networking active in case of future opportunities.
A report by thenetworkone and Kurio.
The contributing experts and agencies are (in an alphabetical order): Sylwia Rytel, Social Media Supervisor, 180heartbeats + JUNG v MATT (PL), Sharlene Jenner, Vice President - Director of Engagement Strategy, Abelson Taylor (USA), Alex Casanovas, Digital Director, Atrevia (ES), Dora Beilin, Senior Social Strategist, Barrett Hoffher (USA), Min Seo, Campaign Director, Brand New Agency (KR), Deshé M. Gully, Associate Strategist, Day One Agency (USA), Francesca Trevisan, Strategist, Different (IT), Trevor Crossman, CX and Digital Transformation Director; Olivia Hussey, Strategic Planner; Simi Srinarula, Social Media Manager, The Hallway (AUS), James Hebbert, Managing Director, Hylink (CN / UK), Mundy Álvarez, Planning Director; Pedro Rojas, Social Media Manager; Pancho González, CCO, Inbrax (CH), Oana Oprea, Head of Digital Planning, Jam Session Agency (RO), Amy Bottrill, Social Account Director, Launch (UK), Gaby Arriaga, Founder, Leonardo1452 (MX), Shantesh S Row, Creative Director, Liwa (UAE), Rajesh Mehta, Chief Strategy Officer; Dhruv Gaur, Digital Planning Lead; Leonie Mergulhao, Account Supervisor - Social Media & PR, Medulla (IN), Aurelija Plioplytė, Head of Digital & Social, Not Perfect (LI), Daiana Khaidargaliyeva, Account Manager, Osaka Labs (UK / USA), Stefanie Söhnchen, Vice President Digital, PIABO Communications (DE), Elisabeth Winiartati, Managing Consultant, Head of Global Integrated Communications; Lydia Aprina, Account Manager, Integrated Marketing and Communications; Nita Prabowo, Account Manager, Integrated Marketing and Communications; Okhi, Web Developer, PNTR Group (ID), Kei Obusan, Insights Director; Daffi Ranandi, Insights Manager, Radarr (SG), Gautam Reghunath, Co-founder & CEO, Talented (IN), Donagh Humphreys, Head of Social and Digital Innovation, THINKHOUSE (IRE), Sarah Yim, Strategy Director, Zulu Alpha Kilo (CA).
Trends In Paid Search: Navigating The Digital Landscape In 2024Search Engine Journal
The search marketing landscape is evolving rapidly with new technologies, and professionals, like you, rely on innovative paid search strategies to meet changing demands.
It’s important that you’re ready to implement new strategies in 2024.
Check this out and learn the top trends in paid search advertising that are expected to gain traction, so you can drive higher ROI more efficiently in 2024.
You’ll learn:
- The latest trends in AI and automation, and what this means for an evolving paid search ecosystem.
- New developments in privacy and data regulation.
- Emerging ad formats that are expected to make an impact next year.
Watch Sreekant Lanka from iQuanti and Irina Klein from OneMain Financial as they dive into the future of paid search and explore the trends, strategies, and technologies that will shape the search marketing landscape.
If you’re looking to assess your paid search strategy and design an industry-aligned plan for 2024, then this webinar is for you.
5 Public speaking tips from TED - Visualized summarySpeakerHub
From their humble beginnings in 1984, TED has grown into the world’s most powerful amplifier for speakers and thought-leaders to share their ideas. They have over 2,400 filmed talks (not including the 30,000+ TEDx videos) freely available online, and have hosted over 17,500 events around the world.
With over one billion views in a year, it’s no wonder that so many speakers are looking to TED for ideas on how to share their message more effectively.
The article “5 Public-Speaking Tips TED Gives Its Speakers”, by Carmine Gallo for Forbes, gives speakers five practical ways to connect with their audience, and effectively share their ideas on stage.
Whether you are gearing up to get on a TED stage yourself, or just want to master the skills that so many of their speakers possess, these tips and quotes from Chris Anderson, the TED Talks Curator, will encourage you to make the most impactful impression on your audience.
See the full article and more summaries like this on SpeakerHub here: https://speakerhub.com/blog/5-presentation-tips-ted-gives-its-speakers
See the original article on Forbes here:
http://www.forbes.com/forbes/welcome/?toURL=http://www.forbes.com/sites/carminegallo/2016/05/06/5-public-speaking-tips-ted-gives-its-speakers/&refURL=&referrer=#5c07a8221d9b
ChatGPT and the Future of Work - Clark Boyd Clark Boyd
Everyone is in agreement that ChatGPT (and other generative AI tools) will shape the future of work. Yet there is little consensus on exactly how, when, and to what extent this technology will change our world.
Businesses that extract maximum value from ChatGPT will use it as a collaborative tool for everything from brainstorming to technical maintenance.
For individuals, now is the time to pinpoint the skills the future professional will need to thrive in the AI age.
Check out this presentation to understand what ChatGPT is, how it will shape the future of work, and how you can prepare to take advantage.
The document provides career advice for getting into the tech field, including:
- Doing projects and internships in college to build a portfolio.
- Learning about different roles and technologies through industry research.
- Contributing to open source projects to build experience and network.
- Developing a personal brand through a website and social media presence.
- Networking through events, communities, and finding a mentor.
- Practicing interviews through mock interviews and whiteboarding coding questions.
Google's Just Not That Into You: Understanding Core Updates & Search IntentLily Ray
1. Core updates from Google periodically change how its algorithms assess and rank websites and pages. This can impact rankings through shifts in user intent, site quality issues being caught up to, world events influencing queries, and overhauls to search like the E-A-T framework.
2. There are many possible user intents beyond just transactional, navigational and informational. Identifying intent shifts is important during core updates. Sites may need to optimize for new intents through different content types and sections.
3. Responding effectively to core updates requires analyzing "before and after" data to understand changes, identifying new intents or page types, and ensuring content matches appropriate intents across video, images, knowledge graphs and more.
A brief introduction to DataScience with explaining of the concepts, algorithms, machine learning, supervised and unsupervised learning, clustering, statistics, data preprocessing, real-world applications etc.
It's part of a Data Science Corner Campaign where I will be discussing the fundamentals of DataScience, AIML, Statistics etc.
Time Management & Productivity - Best PracticesVit Horky
Here's my presentation on by proven best practices how to manage your work time effectively and how to improve your productivity. It includes practical tips and how to use tools such as Slack, Google Apps, Hubspot, Google Calendar, Gmail and others.
The six step guide to practical project managementMindGenius
The six step guide to practical project management
If you think managing projects is too difficult, think again.
We’ve stripped back project management processes to the
basics – to make it quicker and easier, without sacrificing
the vital ingredients for success.
“If you’re looking for some real-world guidance, then The Six Step Guide to Practical Project Management will help.”
Dr Andrew Makar, Tactical Project Management
2. Problem Statement
1 Business Need – To access at least 7 years of data
2 Banking Compliance – Require to perform Database Backup and Disaster Recovery (DR) plan
3 Short maintenance window for database clean up, optimization, backup etc.
4 MPP database does not support incremental & cumulative backup
2
5 EDW database size >50 TB in compressed format
6 Critical system – Short RTO & MTD
7 Shorten backup time, restore time, RTO & MTD
https://www.linkedin.com/in/tankianhui
4. Method 1 - Standard Backup & DR Strategy
Task :
DR Environment
Table Partition
ev
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
..
..
..
..
..
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
PROD Environment
4
https://www.linkedin.com/in/tankianhui
5. Method 1 - Standard Backup & DR Strategy
Task :
DR Environment
Table Partition
ev
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
..
..
..
..
..
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
PROD Environment
5
https://www.linkedin.com/in/tankianhui
Weekly
6. Method 1 - Standard Backup & DR Strategy
WeeklyTask :
DR Environment
Table Partition
ev
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
..
..
..
..
..
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Full database/table backup
1
PROD Environment
6
https://www.linkedin.com/in/tankianhui
7. Method 1 - Standard Backup & DR Strategy
WeeklyTask :
DR Environment
Table Partition
ev
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
..
..
..
..
..
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Full database/table backup
1
PROD Environment
7
https://www.linkedin.com/in/tankianhui
DR
8. Method 1 - Standard Backup & DR Strategy
Weekly DRTask :
DR Environment
Table Partition
ev
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
..
..
..
..
..
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Table Partition
ev
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
..
..
..
..
..
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Full database/table backup
1
Full database/table restore
2
Catch-up run 7 days
3
PROD Environment
8
https://www.linkedin.com/in/tankianhui
9. Method 1 - Standard Backup & DR Strategy
Weekly DRTask :
DR Environment
Table Partition
ev
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
..
..
..
..
..
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Table Partition
ev
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
..
..
..
..
..
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Full database/table backup
1
Full database/table restore
2
Catch-up run 7 days
3
PROD Environment
Business continue
4
9
https://www.linkedin.com/in/tankianhui
10. Method 2 - Backup & DR Strategy for Super Big Table
- Store data in several tables (Daily, Monthly, Yearly)
11. Method 2 - Backup & DR Strategy for Super Big Table
- Store data in several tables (Daily, Monthly, Yearly)
Table Partition
ev
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c0
ev_p201601
ev_p201602
ev_p201603
ev_p201604
ev_p201605
ev_p201606
ev_p201607
ev_p201608
ev_p201609
ev_p201610
ev_p201611
ev_p201612
Table Partition
ev_c1
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
Table Partition
ev_c2
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Table Partition
ev_c5
ev_p201401
ev_p201402
ev_p201403
ev_p201404
ev_p201405
ev_p201406
ev_p201407
ev_p201408
ev_p201409
ev_p201410
ev_p201411
ev_p201412
Table Partition
ev_c6
ev_p201501
ev_p201502
ev_p201503
ev_p201504
ev_p201505
ev_p201506
ev_p201507
ev_p201508
ev_p201509
ev_p201510
ev_p201511
ev_p201512
DR Environment
Table
ev_c0
Table
ev_c1
Table
ev_c2
Table
ev_c3
Table
ev_c4
Table
ev_c5
Table
ev_c6
Task :
Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table
Daily Table Monthly Table
11
https://www.linkedin.com/in/tankianhui
Yearly Table
Backup on 2/4/2017
Restored in DR on 3/4/2017
Backup Tape keep for 7 years
Backup on 2/4/2018
Restored in DR on 3/4/2018
Backup Tape keep for 7 years
Backup on 2/4/2019
Restored in DR on 3/4/2019
Backup Tape keep for 7 years
Backup on 2/4/2014
Restored in DR on 3/4/2014
Backup Tape keep for 7 years
Backup on 2/4/2015
Restored in DR on 3/4/2015
Backup Tape keep for 7 years
Backup on 2/4/2016
Restored in DR on 3/4/2016
Backup Tape keep for 7 years
Restored on
3/4/2017
Restored on
3/4/2018
Restored on
4/4/2013
Restored on
3/4/2015
Restored on
3/4/2016
Restored on
3/4/2013
Restored on
3/4/2014
Restored on
3/4/2019
Backup on 2/4/2013
Restored in DR on 3/4/2013
Backup Tape keep for 7 years
12. Method 2 - Backup & DR Strategy for Super Big Table
- Store data in several tables (Daily, Monthly, Yearly)
Table Partition
ev
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c0
ev_p201601
ev_p201602
ev_p201603
ev_p201604
ev_p201605
ev_p201606
ev_p201607
ev_p201608
ev_p201609
ev_p201610
ev_p201611
ev_p201612
Table Partition
ev_c1
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
Table Partition
ev_c2
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Table Partition
ev_c5
ev_p201401
ev_p201402
ev_p201403
ev_p201404
ev_p201405
ev_p201406
ev_p201407
ev_p201408
ev_p201409
ev_p201410
ev_p201411
ev_p201412
Table Partition
ev_c6
ev_p201501
ev_p201502
ev_p201503
ev_p201504
ev_p201505
ev_p201506
ev_p201507
ev_p201508
ev_p201509
ev_p201510
ev_p201511
ev_p201512
DR Environment
Table
ev_c0
Table
ev_c1
Table
ev_c2
Table
ev_c3
Table
ev_c4
Table
ev_c5
Table
ev_c6
DailyTask :
Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table
Daily Table Monthly Table
Daily
Example
12
https://www.linkedin.com/in/tankianhui
Yearly Table
Backup on 2/4/2017
Restored in DR on 3/4/2017
Backup Tape keep for 7 years
Backup on 2/4/2018
Restored in DR on 3/4/2018
Backup Tape keep for 7 years
Backup on 2/4/2019
Restored in DR on 3/4/2019
Backup Tape keep for 7 years
Backup on 2/4/2014
Restored in DR on 3/4/2014
Backup Tape keep for 7 years
Backup on 2/4/2015
Restored in DR on 3/4/2015
Backup Tape keep for 7 years
Backup on 2/4/2016
Restored in DR on 3/4/2016
Backup Tape keep for 7 years
Restored on
3/4/2017
Restored on
3/4/2018
Restored on
4/4/2013
Restored on
3/4/2015
Restored on
3/4/2016
Restored on
3/4/2013
Restored on
3/4/2014
Restored on
3/4/2019
Backup on 2/4/2013
Restored in DR on 3/4/2013
Backup Tape keep for 7 years
13. Method 2 - Backup & DR Strategy for Super Big Table
- Store data in several tables (Daily, Monthly, Yearly)
Table Partition
ev
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c0
ev_p201601
ev_p201602
ev_p201603
ev_p201604
ev_p201605
ev_p201606
ev_p201607
ev_p201608
ev_p201609
ev_p201610
ev_p201611
ev_p201612
Table Partition
ev_c1
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
Table Partition
ev_c2
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Table Partition
ev_c5
ev_p201401
ev_p201402
ev_p201403
ev_p201404
ev_p201405
ev_p201406
ev_p201407
ev_p201408
ev_p201409
ev_p201410
ev_p201411
ev_p201412
Table Partition
ev_c6
ev_p201501
ev_p201502
ev_p201503
ev_p201504
ev_p201505
ev_p201506
ev_p201507
ev_p201508
ev_p201509
ev_p201510
ev_p201511
ev_p201512
DR Environment
Table
ev_c0
Table
ev_c1
Table
ev_c2
Table
ev_c3
Table
ev_c4
Table
ev_c5
Table
ev_c6
Backup Daily Table
1
DailyTask :
Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table
Daily Table Monthly Table
Daily
Example
13
https://www.linkedin.com/in/tankianhui
Yearly Table
Backup on 2/4/2017
Restored in DR on 3/4/2017
Backup Tape keep for 7 years
Backup on 2/4/2018
Restored in DR on 3/4/2018
Backup Tape keep for 7 years
Backup on 2/4/2019
Restored in DR on 3/4/2019
Backup Tape keep for 7 years
Backup on 2/4/2014
Restored in DR on 3/4/2014
Backup Tape keep for 7 years
Backup on 2/4/2015
Restored in DR on 3/4/2015
Backup Tape keep for 7 years
Backup on 2/4/2016
Restored in DR on 3/4/2016
Backup Tape keep for 7 years
Restored on
3/4/2017
Restored on
3/4/2018
Restored on
4/4/2013
Restored on
3/4/2015
Restored on
3/4/2016
Restored on
3/4/2013
Restored on
3/4/2014
Restored on
3/4/2019
Backup on 2/4/2013
Restored in DR on 3/4/2013
Backup Tape keep for 7 years
14. Method 2 - Backup & DR Strategy for Super Big Table
- Store data in several tables (Daily, Monthly, Yearly)
Table Partition
ev
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c0
ev_p201601
ev_p201602
ev_p201603
ev_p201604
ev_p201605
ev_p201606
ev_p201607
ev_p201608
ev_p201609
ev_p201610
ev_p201611
ev_p201612
Table Partition
ev_c1
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
Table Partition
ev_c2
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Table Partition
ev_c5
ev_p201401
ev_p201402
ev_p201403
ev_p201404
ev_p201405
ev_p201406
ev_p201407
ev_p201408
ev_p201409
ev_p201410
ev_p201411
ev_p201412
Table Partition
ev_c6
ev_p201501
ev_p201502
ev_p201503
ev_p201504
ev_p201505
ev_p201506
ev_p201507
ev_p201508
ev_p201509
ev_p201510
ev_p201511
ev_p201512
DR Environment
Table
ev_c0
Table
ev_c1
Table
ev_c2
Table
ev_c3
Table
ev_c4
Table
ev_c5
Table
ev_c6
Backup Daily Table
1
DailyTask :
Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table
Daily Table Monthly Table
Daily
Example
14
https://www.linkedin.com/in/tankianhui
Yearly Table
Backup on 2/4/2017
Restored in DR on 3/4/2017
Backup Tape keep for 7 years
Backup on 2/4/2018
Restored in DR on 3/4/2018
Backup Tape keep for 7 years
Backup on 2/4/2019
Restored in DR on 3/4/2019
Backup Tape keep for 7 years
Backup on 2/4/2014
Restored in DR on 3/4/2014
Backup Tape keep for 7 years
Backup on 2/4/2015
Restored in DR on 3/4/2015
Backup Tape keep for 7 years
Backup on 2/4/2016
Restored in DR on 3/4/2016
Backup Tape keep for 7 years
Restored on
3/4/2017
Restored on
3/4/2018
Restored on
4/4/2013
Restored on
3/4/2015
Restored on
3/4/2016
Restored on
3/4/2013
Restored on
3/4/2014
Restored on
3/4/2019
Backup on 2/4/2013
Restored in DR on 3/4/2013
Backup Tape keep for 7 years
Monthly
2nd Aug
2019
15. Method 2 - Backup & DR Strategy for Super Big Table
- Store data in several tables (Daily, Monthly, Yearly)
Table Partition
ev
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c0
ev_p201601
ev_p201602
ev_p201603
ev_p201604
ev_p201605
ev_p201606
ev_p201607
ev_p201608
ev_p201609
ev_p201610
ev_p201611
ev_p201612
Table Partition
ev_c1
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
Table Partition
ev_c2
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Table Partition
ev_c5
ev_p201401
ev_p201402
ev_p201403
ev_p201404
ev_p201405
ev_p201406
ev_p201407
ev_p201408
ev_p201409
ev_p201410
ev_p201411
ev_p201412
Table Partition
ev_c6
ev_p201501
ev_p201502
ev_p201503
ev_p201504
ev_p201505
ev_p201506
ev_p201507
ev_p201508
ev_p201509
ev_p201510
ev_p201511
ev_p201512
DR Environment
Table
ev_c0
Table
ev_c1
Table
ev_c2
Table
ev_c3
Table
ev_c4
Table
ev_c5
Table
ev_c6
Exchange
Partition
>3 months
Backup Daily Table
1
Daily Monthly
Backup Monthly Table
3
Task :
Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table
Daily Table Monthly Table
Daily2nd Aug
2019
Example
15
https://www.linkedin.com/in/tankianhui
Yearly Table
Backup on 2/4/2017
Restored in DR on 3/4/2017
Backup Tape keep for 7 years
Backup on 2/4/2018
Restored in DR on 3/4/2018
Backup Tape keep for 7 years
Backup on 2/4/2019
Restored in DR on 3/4/2019
Backup Tape keep for 7 years
Backup on 2/4/2014
Restored in DR on 3/4/2014
Backup Tape keep for 7 years
Backup on 2/4/2015
Restored in DR on 3/4/2015
Backup Tape keep for 7 years
Backup on 2/4/2016
Restored in DR on 3/4/2016
Backup Tape keep for 7 years
Restored on
3/4/2017
Restored on
3/4/2018
Restored on
4/4/2013
Restored on
3/4/2015
Restored on
3/4/2016
Restored on
3/4/2013
Restored on
3/4/2014
Restored on
3/4/2019
Backup on 2/4/2013
Restored in DR on 3/4/2013
Backup Tape keep for 7 years
Housekeeping
4
2
16. Method 2 - Backup & DR Strategy for Super Big Table
- Store data in several tables (Daily, Monthly, Yearly)
Table Partition
ev
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
Table Partition
ev
ev_p202001
ev_p202002
ev_p202003
ev_p202004
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c0
ev_p201601
ev_p201602
ev_p201603
ev_p201604
ev_p201605
ev_p201606
ev_p201607
ev_p201608
ev_p201609
ev_p201610
ev_p201611
ev_p201612
Table Partition
ev_c1
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
Table Partition
ev_c2
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Table Partition
ev_c5
ev_p201401
ev_p201402
ev_p201403
ev_p201404
ev_p201405
ev_p201406
ev_p201407
ev_p201408
ev_p201409
ev_p201410
ev_p201411
ev_p201412
Table Partition
ev_c6
ev_p201501
ev_p201502
ev_p201503
ev_p201504
ev_p201505
ev_p201506
ev_p201507
ev_p201508
ev_p201509
ev_p201510
ev_p201511
ev_p201512
DR Environment
Table
ev_c0
Table
ev_c1
Table
ev_c2
Table
ev_c3
Table
ev_c4
Table
ev_c5
Table
ev_c6
Exchange
Partition
>3 months
Backup Daily Table
1
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Housekeeping
Daily Monthly Yearly
4
Table Partition
ev_h
Backup Monthly Table
3
Task :
Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table
Daily Table Monthly Table
Daily2nd Aug
2019
2nd April
2020
Example
16
https://www.linkedin.com/in/tankianhui
ev_p201901
ev_p201902
ev_p201903
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
ev_p201909
ev_p201910
ev_p201911
ev_p201912
Yearly Table
Backup on 2/4/2017
Restored in DR on 3/4/2017
Backup Tape keep for 7 years
Backup on 2/4/2018
Restored in DR on 3/4/2018
Backup Tape keep for 7 years
Backup on 2/4/2019
Restored in DR on 3/4/2019
Backup Tape keep for 7 years
Backup on 2/4/2014
Restored in DR on 3/4/2014
Backup Tape keep for 7 years
Backup on 2/4/2015
Restored in DR on 3/4/2015
Backup Tape keep for 7 years
Backup on 2/4/2016
Restored in DR on 3/4/2016
Backup Tape keep for 7 years
Restored on
3/4/2017
Restored on
3/4/2018
Restored on
4/4/2013
Restored on
3/4/2015
Restored on
3/4/2016
Restored on
3/4/2013
Restored on
3/4/2014
Restored on
3/4/2019
Backup on 2/4/2013
Restored in DR on 3/4/2013
Backup Tape keep for 7 years
2
17. Method 2 - Backup & DR Strategy for Super Big Table
- Store data in several tables (Daily, Monthly, Yearly)
Year MOD 7
2010 1
2011 2
2012 3
2013 4
2014 5
2015 6
2016 0
2017 1
2018 2
2019 3
2020 4
2021 5
Table Partition
ev
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
Table Partition
ev
ev_p202001
ev_p202002
ev_p202003
ev_p202004
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c0
ev_p201601
ev_p201602
ev_p201603
ev_p201604
ev_p201605
ev_p201606
ev_p201607
ev_p201608
ev_p201609
ev_p201610
ev_p201611
ev_p201612
Table Partition
ev_c1
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
Table Partition
ev_c2
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Table Partition
ev_c5
ev_p201401
ev_p201402
ev_p201403
ev_p201404
ev_p201405
ev_p201406
ev_p201407
ev_p201408
ev_p201409
ev_p201410
ev_p201411
ev_p201412
Table Partition
ev_c6
ev_p201501
ev_p201502
ev_p201503
ev_p201504
ev_p201505
ev_p201506
ev_p201507
ev_p201508
ev_p201509
ev_p201510
ev_p201511
ev_p201512
DR Environment
Table
ev_c0
Table
ev_c1
Table
ev_c2
Table
ev_c3
Table
ev_c4
Table
ev_c5
Table
ev_c6
Exchange
Partition
>3 months
Backup Daily Table
1
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Housekeeping
Daily Monthly Yearly
4
Exchange
Partitions
Table Partition
ev_h
Backup Monthly Table
3
Task :
Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table
Daily Table Monthly Table
Daily2nd Aug
2019
2nd April
2020
Example
17
https://www.linkedin.com/in/tankianhui
ev_p201901
ev_p201902
ev_p201903
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
ev_p201909
ev_p201910
ev_p201911
ev_p201912
Backup Yearly Table
Backup Tape keep for 7 years
6
Yearly Table
Backup on 2/4/2017
Restored in DR on 3/4/2017
Backup Tape keep for 7 years
Backup on 2/4/2018
Restored in DR on 3/4/2018
Backup Tape keep for 7 years
Backup on 2/4/2019
Restored in DR on 3/4/2019
Backup Tape keep for 7 years
Backup on 2/4/2014
Restored in DR on 3/4/2014
Backup Tape keep for 7 years
Backup on 2/4/2015
Restored in DR on 3/4/2015
Backup Tape keep for 7 years
Backup on 2/4/2016
Restored in DR on 3/4/2016
Backup Tape keep for 7 years
Restored on
3/4/2017
Restored on
3/4/2018
Restored on
4/4/2013
Restored on
3/4/2015
Restored on
3/4/2016
Restored on
3/4/2013
Restored on
3/4/2014
Restored on
3/4/2019
Backup on 2/4/2020
Restored in DR on 3/4/2013
Backup Tape keep for 7 years
2 5
18. Method 2 - Backup & DR Strategy for Super Big Table
- Store data in several tables (Daily, Monthly, Yearly)
Year MOD 7
2010 1
2011 2
2012 3
2013 4
2014 5
2015 6
2016 0
2017 1
2018 2
2019 3
2020 4
2021 5
Table Partition
ev
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
Table Partition
ev
ev_p202001
ev_p202002
ev_p202003
ev_p202004
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c0
ev_p201601
ev_p201602
ev_p201603
ev_p201604
ev_p201605
ev_p201606
ev_p201607
ev_p201608
ev_p201609
ev_p201610
ev_p201611
ev_p201612
Table Partition
ev_c1
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
Table Partition
ev_c2
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Table Partition
ev_c5
ev_p201401
ev_p201402
ev_p201403
ev_p201404
ev_p201405
ev_p201406
ev_p201407
ev_p201408
ev_p201409
ev_p201410
ev_p201411
ev_p201412
Table Partition
ev_c6
ev_p201501
ev_p201502
ev_p201503
ev_p201504
ev_p201505
ev_p201506
ev_p201507
ev_p201508
ev_p201509
ev_p201510
ev_p201511
ev_p201512
DR Environment
Table
ev_c0
Table
ev_c1
Table
ev_c2
Table
ev_c3
Table
ev_c4
Table
ev_c5
Table
ev_c6
Exchange
Partition
>3 months
Backup Daily Table
1
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Housekeeping
Daily Monthly Yearly
4
Exchange
Partitions
Table Partition
ev_h
Backup Monthly Table
3
Task :
Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table
Daily Table Monthly Table
Daily2nd Aug
2019
2nd April
2020
Example
18
https://www.linkedin.com/in/tankianhui
ev_p201901
ev_p201902
ev_p201903
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
ev_p201909
ev_p201910
ev_p201911
ev_p201912
Backup Yearly Table
Backup Tape keep for 7 years
6
Yearly Table
Backup on 2/4/2017
Restored in DR on 3/4/2017
Backup Tape keep for 7 years
Backup on 2/4/2018
Restored in DR on 3/4/2018
Backup Tape keep for 7 years
Backup on 2/4/2019
Restored in DR on 3/4/2019
Backup Tape keep for 7 years
Backup on 2/4/2014
Restored in DR on 3/4/2014
Backup Tape keep for 7 years
Backup on 2/4/2015
Restored in DR on 3/4/2015
Backup Tape keep for 7 years
Backup on 2/4/2016
Restored in DR on 3/4/2016
Backup Tape keep for 7 years
Restored on
3/4/2017
Restored on
3/4/2018
Restored on
4/4/2013
Restored on
3/4/2015
Restored on
3/4/2016
Restored on
3/4/2013
Restored on
3/4/2014
Restored on
3/4/2019
Backup on 2/4/2020
Restored in DR on 3/4/2013
Backup Tape keep for 7 years
2 5
Disaster
Preparedness Plan
3rd April
2020
19. Method 2 - Backup & DR Strategy for Super Big Table
- Store data in several tables (Daily, Monthly, Yearly)
Year MOD 7
2010 1
2011 2
2012 3
2013 4
2014 5
2015 6
2016 0
2017 1
2018 2
2019 3
2020 4
2021 5
Table Partition
ev
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
Table Partition
ev
ev_p202001
ev_p202002
ev_p202003
ev_p202004
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c0
ev_p201601
ev_p201602
ev_p201603
ev_p201604
ev_p201605
ev_p201606
ev_p201607
ev_p201608
ev_p201609
ev_p201610
ev_p201611
ev_p201612
Table Partition
ev_c1
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
Table Partition
ev_c2
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Table Partition
ev_c5
ev_p201401
ev_p201402
ev_p201403
ev_p201404
ev_p201405
ev_p201406
ev_p201407
ev_p201408
ev_p201409
ev_p201410
ev_p201411
ev_p201412
Table Partition
ev_c6
ev_p201501
ev_p201502
ev_p201503
ev_p201504
ev_p201505
ev_p201506
ev_p201507
ev_p201508
ev_p201509
ev_p201510
ev_p201511
ev_p201512
DR Environment
Table
ev_c0
Table
ev_c1
Table
ev_c2
Table
ev_c3
Table
ev_c4
Table
ev_c5
Table
ev_c6
Exchange
Partition
>3 months
Backup Daily Table
1
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Housekeeping
Daily Monthly Yearly
4
Table Partition
ev_h
Backup Monthly Table
3
Disaster
Preparedness Plan
Task :
Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table
Daily Table Monthly Table
Daily2nd Aug
2019
2nd April
2020
3rd April
2020
Example
19
https://www.linkedin.com/in/tankianhui
ev_p201901
ev_p201902
ev_p201903
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
ev_p201909
ev_p201910
ev_p201911
ev_p201912
Backup Yearly Table
Backup Tape keep for 7 years
6
Yearly Table
Backup on 2/4/2017
Restored in DR on 3/4/2017
Backup Tape keep for 7 years
Backup on 2/4/2018
Restored in DR on 3/4/2018
Backup Tape keep for 7 years
Backup on 2/4/2019
Restored in DR on 3/4/2019
Backup Tape keep for 7 years
Backup on 2/4/2014
Restored in DR on 3/4/2014
Backup Tape keep for 7 years
Backup on 2/4/2015
Restored in DR on 3/4/2015
Backup Tape keep for 7 years
Backup on 2/4/2016
Restored in DR on 3/4/2016
Backup Tape keep for 7 years
Restored on
3/4/2017
Restored on
3/4/2018
Restored on
4/4/2013
Restored on
3/4/2015
Restored on
3/4/2016
Restored on
3/4/2020
Restored on
3/4/2014
Restored on
3/4/2019
Backup on 2/4/2020
Restored in DR on 3/4/2020
Backup Tape keep for 7 years
2
Exchange
Partitions
Restore in DR
5
7
20. Method 2 - Backup & DR Strategy for Super Big Table
- Store data in several tables (Daily, Monthly, Yearly)
Table Partition
ev
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
Table Partition
ev
ev_p202001
ev_p202002
ev_p202003
ev_p202004
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c0
ev_p201601
ev_p201602
ev_p201603
ev_p201604
ev_p201605
ev_p201606
ev_p201607
ev_p201608
ev_p201609
ev_p201610
ev_p201611
ev_p201612
Table Partition
ev_c1
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
Table Partition
ev_c2
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Table Partition
ev_c5
ev_p201401
ev_p201402
ev_p201403
ev_p201404
ev_p201405
ev_p201406
ev_p201407
ev_p201408
ev_p201409
ev_p201410
ev_p201411
ev_p201412
Table Partition
ev_c6
ev_p201501
ev_p201502
ev_p201503
ev_p201504
ev_p201505
ev_p201506
ev_p201507
ev_p201508
ev_p201509
ev_p201510
ev_p201511
ev_p201512
DR Environment
Table
ev_c0
Table
ev_c1
Table
ev_c2
Table
ev_c3
Table
ev_c4
Table
ev_c5
Table
ev_c6
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Daily Monthly Yearly
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
ev_p201909
ev_p201910
ev_p201911
ev_p201912
Disaster
Preparedness Plan
DRTask :
Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table
Daily Table Monthly Table
Daily2nd Aug
2019
2nd April
2020
3rd April
2020
15th April
2020
Example
20
https://www.linkedin.com/in/tankianhui
Backup on 2/4/2017
Restored in DR on 3/4/2017
Backup Tape keep for 7 years
Backup on 2/4/2018
Restored in DR on 3/4/2018
Backup Tape keep for 7 years
Backup on 2/4/2019
Restored in DR on 3/4/2019
Backup Tape keep for 7 years
Backup on 2/4/2014
Restored in DR on 3/4/2014
Backup Tape keep for 7 years
Backup on 2/4/2015
Restored in DR on 3/4/2015
Backup Tape keep for 7 years
Backup on 2/4/2016
Restored in DR on 3/4/2016
Backup Tape keep for 7 years
Restored on
3/4/2017
Restored on
3/4/2018
Restored on
4/4/2013
Restored on
3/4/2015
Restored on
3/4/2016
Restored on
3/4/2020
Restored on
3/4/2014
Restored on
3/4/2019
Backup on 2/4/2020
Restored in DR on 3/4/2020
Backup Tape keep for 7 years
21. Method 2 - Backup & DR Strategy for Super Big Table
- Store data in several tables (Daily, Monthly, Yearly)
Table Partition
ev
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
Table Partition
ev
ev_p202001
ev_p202002
ev_p202003
ev_p202004
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c0
ev_p201601
ev_p201602
ev_p201603
ev_p201604
ev_p201605
ev_p201606
ev_p201607
ev_p201608
ev_p201609
ev_p201610
ev_p201611
ev_p201612
Table Partition
ev_c1
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
Table Partition
ev_c2
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Table Partition
ev_c5
ev_p201401
ev_p201402
ev_p201403
ev_p201404
ev_p201405
ev_p201406
ev_p201407
ev_p201408
ev_p201409
ev_p201410
ev_p201411
ev_p201412
Table Partition
ev_c6
ev_p201501
ev_p201502
ev_p201503
ev_p201504
ev_p201505
ev_p201506
ev_p201507
ev_p201508
ev_p201509
ev_p201510
ev_p201511
ev_p201512
DR Environment
Table
ev_c0
Table
ev_c1
Table
ev_c2
Table
ev_c3
Table
ev_c4
Table
ev_c5
Table
ev_c6
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Daily Monthly Yearly
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
ev_p201909
ev_p201910
ev_p201911
ev_p201912
Disaster
Preparedness Plan
DR
Table
ev
Only require to restore
Daily Tables to continue
Daily Batch/Catch-up 1 day
Task :
Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table
Daily Table Monthly Table
Daily2nd Aug
2019
2nd April
2020
3rd April
2020
15th April
2020
Example
21
https://www.linkedin.com/in/tankianhui
Backup on 2/4/2017
Restored in DR on 3/4/2017
Backup Tape keep for 7 years
Backup on 2/4/2018
Restored in DR on 3/4/2018
Backup Tape keep for 7 years
Backup on 2/4/2019
Restored in DR on 3/4/2019
Backup Tape keep for 7 years
Backup on 2/4/2014
Restored in DR on 3/4/2014
Backup Tape keep for 7 years
Backup on 2/4/2015
Restored in DR on 3/4/2015
Backup Tape keep for 7 years
Backup on 2/4/2016
Restored in DR on 3/4/2016
Backup Tape keep for 7 years
Restored on
3/4/2017
Restored on
3/4/2018
Restored on
4/4/2013
Restored on
3/4/2015
Restored on
3/4/2016
Restored on
3/4/2020
Restored on
3/4/2014
Restored on
3/4/2019
Backup on 2/4/2020
Restored in DR on 3/4/2020
Backup Tape keep for 7 years
22. Method 2 - Backup & DR Strategy for Super Big Table
- Store data in several tables (Daily, Monthly, Yearly)
Table Partition
ev
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
Table Partition
ev
ev_p202001
ev_p202002
ev_p202003
ev_p202004
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c0
ev_p201601
ev_p201602
ev_p201603
ev_p201604
ev_p201605
ev_p201606
ev_p201607
ev_p201608
ev_p201609
ev_p201610
ev_p201611
ev_p201612
Table Partition
ev_c1
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
Table Partition
ev_c2
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Table Partition
ev_c5
ev_p201401
ev_p201402
ev_p201403
ev_p201404
ev_p201405
ev_p201406
ev_p201407
ev_p201408
ev_p201409
ev_p201410
ev_p201411
ev_p201412
Table Partition
ev_c6
ev_p201501
ev_p201502
ev_p201503
ev_p201504
ev_p201505
ev_p201506
ev_p201507
ev_p201508
ev_p201509
ev_p201510
ev_p201511
ev_p201512
DR Environment
Table
ev_c0
Table
ev_c1
Table
ev_c2
Table
ev_c3
Table
ev_c4
Table
ev_c5
Table
ev_c6
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Daily Monthly Yearly
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
ev_p201909
ev_p201910
ev_p201911
ev_p201912
Disaster
Preparedness Plan
DR
Table
ev
Only require to restore
Daily Tables to continue
Daily Batch/Catch-up 1 day
Task :
Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table
Daily Table Monthly Table
Business Continue
Daily2nd Aug
2019
2nd April
2020
3rd April
2020
15th April
2020
Example
22
https://www.linkedin.com/in/tankianhui
Backup on 2/4/2017
Restored in DR on 3/4/2017
Backup Tape keep for 7 years
Backup on 2/4/2018
Restored in DR on 3/4/2018
Backup Tape keep for 7 years
Backup on 2/4/2019
Restored in DR on 3/4/2019
Backup Tape keep for 7 years
Backup on 2/4/2014
Restored in DR on 3/4/2014
Backup Tape keep for 7 years
Backup on 2/4/2015
Restored in DR on 3/4/2015
Backup Tape keep for 7 years
Backup on 2/4/2016
Restored in DR on 3/4/2016
Backup Tape keep for 7 years
Restored on
3/4/2017
Restored on
3/4/2018
Restored on
4/4/2013
Restored on
3/4/2015
Restored on
3/4/2016
Restored on
3/4/2020
Restored on
3/4/2014
Restored on
3/4/2019
Backup on 2/4/2020
Restored in DR on 3/4/2020
Backup Tape keep for 7 years
23. Method 2 - Backup & DR Strategy for Super Big Table
- Store data in several tables (Daily, Monthly, Yearly)
Table Partition
ev
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
Table Partition
ev
ev_p202001
ev_p202002
ev_p202003
ev_p202004
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c0
ev_p201601
ev_p201602
ev_p201603
ev_p201604
ev_p201605
ev_p201606
ev_p201607
ev_p201608
ev_p201609
ev_p201610
ev_p201611
ev_p201612
Table Partition
ev_c1
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
Table Partition
ev_c2
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Table Partition
ev_c5
ev_p201401
ev_p201402
ev_p201403
ev_p201404
ev_p201405
ev_p201406
ev_p201407
ev_p201408
ev_p201409
ev_p201410
ev_p201411
ev_p201412
Table Partition
ev_c6
ev_p201501
ev_p201502
ev_p201503
ev_p201504
ev_p201505
ev_p201506
ev_p201507
ev_p201508
ev_p201509
ev_p201510
ev_p201511
ev_p201512
DR Environment
Table
ev_c0
Table
ev_c1
Table
ev_c2
Table
ev_c3
Table
ev_c4
Table
ev_c5
Table
ev_c6
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Daily Monthly Yearly
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
ev_p201909
ev_p201910
ev_p201911
ev_p201912
Disaster
Preparedness Plan
DR
Table
ev
Only require to restore
Daily Tables to continue
Daily Batch/Catch-up 1 day
Table
ev_h
Restore Monthly Tables
stage-by-stage (later)
May restore monthly for
Disaster Preparedness
Task :
Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table
Daily Table Monthly Table
Business Continue
Daily2nd Aug
2019
2nd April
2020
3rd April
2020
15th April
2020
Example
23
https://www.linkedin.com/in/tankianhui
Backup on 2/4/2017
Restored in DR on 3/4/2017
Backup Tape keep for 7 years
Backup on 2/4/2018
Restored in DR on 3/4/2018
Backup Tape keep for 7 years
Backup on 2/4/2019
Restored in DR on 3/4/2019
Backup Tape keep for 7 years
Backup on 2/4/2014
Restored in DR on 3/4/2014
Backup Tape keep for 7 years
Backup on 2/4/2015
Restored in DR on 3/4/2015
Backup Tape keep for 7 years
Backup on 2/4/2016
Restored in DR on 3/4/2016
Backup Tape keep for 7 years
Restored on
3/4/2017
Restored on
3/4/2018
Restored on
4/4/2013
Restored on
3/4/2015
Restored on
3/4/2016
Restored on
3/4/2020
Restored on
3/4/2014
Restored on
3/4/2019
Backup on 2/4/2020
Restored in DR on 3/4/2020
Backup Tape keep for 7 years
24. Method 2 - Backup & DR Strategy for Super Big Table
- Store data in several tables (Daily, Monthly, Yearly)
Table Partition
ev
ev_p201905
ev_p201906
ev_p201907
ev_p201908
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
Table Partition
ev
ev_p202001
ev_p202002
ev_p202003
ev_p202004
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c4
ev_p201301
ev_p201302
ev_p201303
ev_p201304
ev_p201305
ev_p201306
ev_p201307
ev_p201308
ev_p201309
ev_p201310
ev_p201311
ev_p201312
Table Partition
ev_c0
ev_p201601
ev_p201602
ev_p201603
ev_p201604
ev_p201605
ev_p201606
ev_p201607
ev_p201608
ev_p201609
ev_p201610
ev_p201611
ev_p201612
Table Partition
ev_c1
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
Table Partition
ev_c2
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Table Partition
ev_c5
ev_p201401
ev_p201402
ev_p201403
ev_p201404
ev_p201405
ev_p201406
ev_p201407
ev_p201408
ev_p201409
ev_p201410
ev_p201411
ev_p201412
Table Partition
ev_c6
ev_p201501
ev_p201502
ev_p201503
ev_p201504
ev_p201505
ev_p201506
ev_p201507
ev_p201508
ev_p201509
ev_p201510
ev_p201511
ev_p201512
Backup on 2/4/2017
Restored in DR on 3/4/2017
Backup Tape keep for 7 years
Backup on 2/4/2018
Restored in DR on 3/4/2018
Backup Tape keep for 7 years
Backup on 2/4/2019
Restored in DR on 3/4/2019
Backup Tape keep for 7 years
Backup on 2/4/2014
Restored in DR on 3/4/2014
Backup Tape keep for 7 years
Backup on 2/4/2015
Restored in DR on 3/4/2015
Backup Tape keep for 7 years
Backup on 2/4/2016
Restored in DR on 3/4/2016
Backup Tape keep for 7 years
DR Environment
Table
ev_c0
Table
ev_c1
Table
ev_c2
Table
ev_c3
Table
ev_c4
Table
ev_c5
Table
ev_c6
Restored on
3/4/2017
Restored on
3/4/2018
Restored on
4/4/2013
Restored on
3/4/2015
Restored on
3/4/2016
Table Partition
ev_c3
ev_p201201
ev_p201202
ev_p201203
ev_p201204
ev_p201205
ev_p201206
ev_p201207
ev_p201208
ev_p201209
ev_p201210
ev_p201211
ev_p201212
Daily Monthly Yearly
Table Partition
ev_h
ev_p201901
ev_p201902
ev_p201903
ev_p201904
ev_p201905
ev_p201906
ev_p201907
ev_p201908
ev_p201909
ev_p201910
ev_p201911
ev_p201912
Disaster
Preparedness Plan
DR
Table
ev
Only require to restore
Daily Tables to continue
Daily Batch/Catch-up 1 day
Table
ev_h
Restore Monthly Tables
stage-by-stage (later)
May restore monthly for
Disaster Preparedness
Task :
Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table Yearly Table
Daily Table Monthly Table
Restored on
3/4/2020
Restored on
3/4/2014
Restored on
3/4/2019
Business Continue
Daily2nd Aug
2019
2nd April
2020
3rd April
2020
15th April
2020
Example
24
https://www.linkedin.com/in/tankianhui
Summary
• Backup Time
• Backup Size
• Backup Storage
• Restore Time
• RTO & MTD
• Maintenance Window
• And etc.
• No backup on same
historical data
yearly/*monthly/*daily
Backup on 2/4/2020
Restored in DR on 3/4/2020
Backup Tape keep for 7 years
25. Method 3 - Backup & DR Strategy for Big Table
- Store data in several tables (Daily, Historical + Offload to Hadoop)
26. Method 3 - Backup & DR Strategy for Big Table
- Store data in several tables (Daily, Historical + Offload to Hadoop)
Table Partition
ev
ev_p201903
ev_p201904
ev_p201905
ev_p201906
Table Partition
ev_h
ev_p201612
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
Task :
DR Environment
Table Partition
ev_t
Table Partition
ev_x
ev_p201206
..
ev_p201301
..
ev_p201401
..
ev_p201501
..
ev_p201601
..
ev_p201611
ev_p201612
Daily Table Historical Table (Min 2 years) Temporary Table External Table (Data in HDFS)
Example
26
https://www.linkedin.com/in/tankianhui
27. Method 3 - Backup & DR Strategy for Big Table
- Store data in several tables (Daily, Historical + Offload to Hadoop)
Daily
Table Partition
ev
ev_p201903
ev_p201904
ev_p201905
ev_p201906
Table Partition
ev_h
ev_p201612
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
DailyTask :
DR Environment
Table Partition
ev_t
Table Partition
ev_x
ev_p201206
..
ev_p201301
..
ev_p201401
..
ev_p201501
..
ev_p201601
..
ev_p201611
ev_p201612
Daily Table Historical Table (Min 2 years) Temporary Table External Table (Data in HDFS)
Example
27
https://www.linkedin.com/in/tankianhui
28. Method 3 - Backup & DR Strategy for Big Table
- Store data in several tables (Daily, Historical + Offload to Hadoop)
Daily
Table Partition
ev
ev_p201903
ev_p201904
ev_p201905
ev_p201906
Table Partition
ev_h
ev_p201612
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
DailyTask :
DR Environment
Table Partition
ev_t
Table Partition
ev_x
ev_p201206
..
ev_p201301
..
ev_p201401
..
ev_p201501
..
ev_p201601
..
ev_p201611
ev_p201612
Daily Table Historical Table (Min 2 years) Temporary Table External Table (Data in HDFS)
Example
Backup Daily Table
1
28
https://www.linkedin.com/in/tankianhui
29. Method 3 - Backup & DR Strategy for Big Table
- Store data in several tables (Daily, Historical + Offload to Hadoop)
Daily
Table Partition
ev
ev_p201903
ev_p201904
ev_p201905
ev_p201906
Table Partition
ev_h
ev_p201612
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
DailyTask :
DR Environment
Table Partition
ev_t
Table Partition
ev_x
ev_p201206
..
ev_p201301
..
ev_p201401
..
ev_p201501
..
ev_p201601
..
ev_p201611
ev_p201612
Daily Table Historical Table (Min 2 years) Temporary Table External Table (Data in HDFS)
Example
Backup Daily Table
1
29
https://www.linkedin.com/in/tankianhui
Monthly
2nd June
2019
30. Method 3 - Backup & DR Strategy for Big Table
- Store data in several tables (Daily, Historical + Offload to Hadoop)
Daily
Table Partition
ev
ev_p201903
ev_p201904
ev_p201905
ev_p201906
Table Partition
ev_h
ev_p201612
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p20170
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
Daily MonthlyTask :
DR Environment
Table Partition
ev_t
Table Partition
ev_x
ev_p201206
..
ev_p201301
..
ev_p201401
..
ev_p201501
..
ev_p201601
..
ev_p201611
ev_p201612
Exchange
Partition
>3 months
2
Daily Table Historical Table (Min 2 years) Temporary Table External Table (Data in HDFS)
Example
2nd June
2019
Backup Daily Table
Backup Historical Table
1
3
30
https://www.linkedin.com/in/tankianhui
ev_p201902
31. Method 3 - Backup & DR Strategy for Big Table
- Store data in several tables (Daily, Historical + Offload to Hadoop)
Daily
Table Partition
ev
ev_p201903
ev_p201904
ev_p201905
ev_p201906
Table Partition
ev_h
ev_p201612
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p20170
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
Daily MonthlyTask :
DR Environment
Table Partition
ev_t
Table Partition
ev_x
ev_p201206
..
ev_p201301
..
ev_p201401
..
ev_p201501
..
ev_p201601
..
ev_p201611
ev_p201612
Exchange
Partition
>3 months
2
Daily Table Historical Table (Min 2 years) Temporary Table External Table (Data in HDFS)
Example
2nd June
2019
Backup Daily Table
Backup Historical Table
1
3
31
https://www.linkedin.com/in/tankianhui
ev_p201902
Disaster
Preparedness Plan
3rd June
2019
32. Method 3 - Backup & DR Strategy for Big Table
- Store data in several tables (Daily, Historical + Offload to Hadoop)
Daily
Table Partition
ev
ev_p201903
ev_p201904
ev_p201905
ev_p201906
Table Partition
ev_h
ev_p201612
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p20170
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
Daily MonthlyTask :
DR Environment
Table Partition
ev_t
Table Partition
ev_x
ev_p201206
..
ev_p201301
..
ev_p201401
..
ev_p201501
..
ev_p201601
..
ev_p201611
ev_p201612
Exchange
Partition
>3 months
2
Daily Table Historical Table (Min 2 years) Temporary Table External Table (Data in HDFS)
Example
2nd June
2019
Backup Daily Table
Backup Historical Table
1
3
32
https://www.linkedin.com/in/tankianhui
ev_p201902
Disaster
Preparedness Plan
Table
ev_h
Restore in DR
4
3rd June
2019
33. Method 3 - Backup & DR Strategy for Big Table
- Store data in several tables (Daily, Historical + Offload to Hadoop)
Daily
Table Partition
ev
ev_p201903
ev_p201904
ev_p201905
ev_p201906
Table Partition
ev_h
ev_p201612
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
Daily Monthly Half-YearlyTask :
DR Environment
Table Partition
ev_t
Table Partition
ev_x
ev_p201206
..
ev_p201301
..
ev_p201401
..
ev_p201501
..
ev_p201601
..
ev_p201611
ev_p201612
Exchange
Partition
>3 months
2
Daily Table Historical Table (Min 2 years) Temporary Table External Table (Data in HDFS)
Disaster
Preparedness Plan
Table
ev_h
Restore in DR
4
Example
2nd June
2019
3rd June
2019
2nd July
2019
Table Partition
ev_h
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
ev_p201903
Table Partition
ev
ev_p201904
ev_p201905
ev_p201906
ev_p201907
Backup Daily Table
Backup Historical Table
1
3
33
https://www.linkedin.com/in/tankianhui
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
34. Method 3 - Backup & DR Strategy for Big Table
- Store data in several tables (Daily, Historical + Offload to Hadoop)
Daily
Table Partition
ev
ev_p201903
ev_p201904
ev_p201905
ev_p201906
Table Partition
ev_h
ev_p201612
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
Daily Monthly Half-YearlyTask :
DR Environment
Table Partition
ev_t
Table Partition
ev_x
ev_p201206
..
ev_p201301
..
ev_p201401
..
ev_p201501
..
ev_p201601
..
ev_p201611
ev_p201612
Exchange
Partition
>3 months
2
Exchange
Partitions
>2 years
5
Daily Table Historical Table (Min 2 years) Temporary Table External Table (Data in HDFS)
Backup Half-Yearly
Table. Backup Tape
keep for 7 years
6
Off load to Hadoop
7
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
Disaster
Preparedness Plan
Table
ev_h
Restore in DR
4
Example
2nd June
2019
3rd June
2019
2nd July
2019
Table Partition
ev_h
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
ev_p201903
Table Partition
ev
ev_p201904
ev_p201905
ev_p201906
ev_p201907
Backup Daily Table
Backup Historical Table
1
3
34
https://www.linkedin.com/in/tankianhui
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
35. Method 3 - Backup & DR Strategy for Big Table
- Store data in several tables (Daily, Historical + Offload to Hadoop)
Daily
Table Partition
ev
ev_p201903
ev_p201904
ev_p201905
ev_p201906
Table Partition
ev_h
ev_p201612
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
Daily Monthly Half-YearlyTask :
DR Environment
Table Partition
ev_t
Table Partition
ev_x
ev_p201206
..
ev_p201301
..
ev_p201401
..
ev_p201501
..
ev_p201601
..
ev_p201611
ev_p201612
Exchange
Partition
>3 months
2
Exchange
Partitions
>2 years
5
Daily Table Historical Table (Min 2 years) Temporary Table External Table (Data in HDFS)
Backup Half-Yearly
Table. Backup Tape
keep for 7 years
6
Off load to Hadoop
7
Disaster
Preparedness Plan
Table
ev_h
Restore in DR
4
Example
2nd June
2019
3rd June
2019
2nd July
2019
Table Partition
ev_h
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
ev_p201903
Table Partition
ev
ev_p201904
ev_p201905
ev_p201906
ev_p201907
Backup Daily Table
Backup Historical Table
1
3
35
https://www.linkedin.com/in/tankianhui
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
Disaster
Preparedness Plan
4th July
2019
36. Method 3 - Backup & DR Strategy for Big Table
- Store data in several tables (Daily, Historical + Offload to Hadoop)
Daily
Table Partition
ev
ev_p201903
ev_p201904
ev_p201905
ev_p201906
Table Partition
ev_h
ev_p201612
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
Daily Monthly Half-Yearly Disaster
Preparedness Plan
Task :
DR Environment
Table Partition
ev_t
Table Partition
ev_x
ev_p201206
..
ev_p201301
..
ev_p201401
..
ev_p201501
..
ev_p201601
..
ev_p201611
ev_p201612
Exchange
Partition
>3 months
2
Exchange
Partitions
>2 years
5
Daily Table Historical Table (Min 2 years) Temporary Table External Table (Data in HDFS)
Backup Half-Yearly
Table. Backup Tape
keep for 7 years
6
Off load to Hadoop
7
Table
ev_x
Table
ev_t
Restore in DR
Disaster
Preparedness Plan
Table
ev_h
Restore in DR
4
Example
2nd June
2019
3rd June
2019
2nd July
2019
4th July
2019
Table Partition
ev_h
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
ev_p201903
Table Partition
ev
ev_p201904
ev_p201905
ev_p201906
ev_p201907
Backup Daily Table
Backup Historical Table
1
3
36
https://www.linkedin.com/in/tankianhui
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
8
37. Method 3 - Backup & DR Strategy for Big Table
- Store data in several tables (Daily, Historical + Offload to Hadoop)
Daily
Table Partition
ev
ev_p201903
ev_p201904
ev_p201905
ev_p201906
Table Partition
ev_h
ev_p201612
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
Daily Monthly Half-Yearly Disaster
Preparedness Plan
DRTask :
DR Environment
Table Partition
ev_t
Table Partition
ev_x
ev_p201206
..
ev_p201301
..
ev_p201401
..
ev_p201501
..
ev_p201601
..
ev_p201611
ev_p201612
Daily Table Historical Table (Min 2 years) Temporary Table External Table (Data in HDFS)
Table
ev_x
Table
ev_t
Disaster
Preparedness Plan
Table
ev_h
Example
2nd June
2019
3rd June
2019
2nd July
2019
4th July
2019
15th July
2019
Table Partition
ev_h
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
ev_p201903
Table Partition
ev
ev_p201904
ev_p201905
ev_p201906
ev_p201907
37
https://www.linkedin.com/in/tankianhui
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
38. Method 3 - Backup & DR Strategy for Big Table
- Store data in several tables (Daily, Historical + Offload to Hadoop)
Daily
Table Partition
ev
ev_p201903
ev_p201904
ev_p201905
ev_p201906
Table Partition
ev_h
ev_p201612
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
Daily Monthly Half-Yearly Disaster
Preparedness Plan
DR
Table
ev
Only require to restore
Daily Tables to continue
Daily Batch/Catch-up 1 day
Task :
DR Environment
Table Partition
ev_t
Table Partition
ev_x
ev_p201206
..
ev_p201301
..
ev_p201401
..
ev_p201501
..
ev_p201601
..
ev_p201611
ev_p201612
Daily Table Historical Table (Min 2 years) Temporary Table External Table (Data in HDFS)
Table
ev_x
Table
ev_t
Disaster
Preparedness Plan
Table
ev_h
Example
2nd June
2019
3rd June
2019
2nd July
2019
4th July
2019
15th July
2019
Table Partition
ev_h
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
ev_p201903
Table Partition
ev
ev_p201904
ev_p201905
ev_p201906
ev_p201907
38
https://www.linkedin.com/in/tankianhui
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
39. Method 3 - Backup & DR Strategy for Big Table
- Store data in several tables (Daily, Historical + Offload to Hadoop)
Daily
Table Partition
ev
ev_p201903
ev_p201904
ev_p201905
ev_p201906
Table Partition
ev_h
ev_p201612
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
Daily Monthly Half-Yearly Disaster
Preparedness Plan
DR
Table
ev
Only require to restore
Daily Tables to continue
Daily Batch/Catch-up 1 day
Task :
Business Continue
DR Environment
Table Partition
ev_t
Table Partition
ev_x
ev_p201206
..
ev_p201301
..
ev_p201401
..
ev_p201501
..
ev_p201601
..
ev_p201611
ev_p201612
Daily Table Historical Table (Min 2 years) Temporary Table External Table (Data in HDFS)
Table
ev_x
Table
ev_t
Disaster
Preparedness Plan
Table
ev_h
Example
2nd June
2019
3rd June
2019
2nd July
2019
4th July
2019
15th July
2019
Table Partition
ev_h
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
ev_p201903
Table Partition
ev
ev_p201904
ev_p201905
ev_p201906
ev_p201907
39
https://www.linkedin.com/in/tankianhui
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
40. Method 3 - Backup & DR Strategy for Big Table
- Store data in several tables (Daily, Historical + Offload to Hadoop)
Daily
Table Partition
ev
ev_p201903
ev_p201904
ev_p201905
ev_p201906
Table Partition
ev_h
ev_p201612
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
Daily Monthly Half-Yearly Disaster
Preparedness Plan
DR
Table
ev
Only require to restore
Daily Tables to continue
Daily Batch/Catch-up 1 day
Task :
Business Continue
DR Environment
Table Partition
ev_t
Table Partition
ev_x
ev_p201206
..
ev_p201301
..
ev_p201401
..
ev_p201501
..
ev_p201601
..
ev_p201611
ev_p201612
Daily Table Historical Table (Min 2 years) Temporary Table External Table (Data in HDFS)
Table
ev_x
Table
ev_t
Disaster
Preparedness Plan
Table
ev_h
Example
2nd June
2019
3rd June
2019
2nd July
2019
4th July
2019
15th July
2019
Table Partition
ev_h
ev_p201707
ev_p201708
ev_p201709
ev_p201710
ev_p201711
ev_p201712
ev_p201801
ev_p201802
ev_p201803
ev_p201804
ev_p201805
ev_p201806
ev_p201807
ev_p201808
ev_p201809
ev_p201810
ev_p201811
ev_p201812
ev_p201901
ev_p201902
ev_p201903
Table Partition
ev
ev_p201904
ev_p201905
ev_p201906
ev_p201907
40
https://www.linkedin.com/in/tankianhui
Summary
• Backup Time
• Backup Size
• Backup Storage
• Restore Time
• RTO & MTD
• Maintenance Window
• And etc.
• No backup on same
historical data
yearly/*monthly/*daily
ev_p201701
ev_p201702
ev_p201703
ev_p201704
ev_p201705
ev_p201706
41. Comparison – Backup Strategy x Data Volume to Backup
Data Volume to Backup
(Number of Months)
1. Backup Time
2. Backup File Size
3. Backup Storage
=
Stacked Column Chart (1-year projection)
Stacked Column Chart (5-months projection)
41
https://www.linkedin.com/in/tankianhui
42. Important Things to Consider
1 Complexity & Workload – Developer, Modeler, DBA, Support, Operation
2 EDW data in Daily Table for Daily Batch Run & Reporting – 3 months data?
3 Data retention in EDW → Hot & Cold Data → Off load to Hadoop HDFS/HIVE (SQL-on-Hadoop)
4 Performance - EDW (MPP DB) vs Hadoop (SQL-on-Hadoop)
42
5 Only applicable for transaction or append-only table
6 Backup Strategy + Incremental/Cumulative Backup – 2 in 1
https://www.linkedin.com/in/tankianhui