Cloud computing, big data, and mobile are three major trends that will change the world. Cloud computing provides scalable and elastic IT resources as services over the internet. Big data involves large amounts of both structured and unstructured data that can generate business insights when analyzed. The hadoop ecosystem, including components like HDFS, mapreduce, pig, and hive, provides an architecture for distributed storage and processing of big data across commodity hardware.
Apache Drill [1] is a distributed system for interactive analysis of large-scale datasets, inspired by Google’s Dremel technology. It is a design goal to scale to 10,000 servers or more and to be able to process Petabytes of data and trillions of records in seconds. Since its inception in mid 2012, Apache Drill has gained widespread interest in the community. In this talk we focus on how Apache Drill enables interactive analysis and query at scale. First we walk through typical use cases and then delve into Drill's architecture, the data flow and query languages as well as data sources supported.
[1] http://incubator.apache.org/drill/
Apache Drill [1] is a distributed system for interactive analysis of large-scale datasets, inspired by Google’s Dremel technology. It is a design goal to scale to 10,000 servers or more and to be able to process Petabytes of data and trillions of records in seconds. Since its inception in mid 2012, Apache Drill has gained widespread interest in the community. In this talk we focus on how Apache Drill enables interactive analysis and query at scale. First we walk through typical use cases and then delve into Drill's architecture, the data flow and query languages as well as data sources supported.
[1] http://incubator.apache.org/drill/
Cloudera Sessions - Clinic 1 - Getting Started With HadoopCloudera, Inc.
If you are interested in Hadoop and its capabilities, but you are not sure where to begin, this is the session for you. Learn the basics of Hadoop, see how to spin up a development cluster in the cloud or on-premise, and start exploring ETL processing with SQL and other familiar tools
Overview of Big data, Hadoop and Microsoft BI - version1Thanh Nguyen
Big Data and advanced analytics are critical topics for executives today. But many still aren't sure how to turn that promise into value. This presentation provides an overview of 16 examples and use cases that lay out the different ways companies have approached the issue and found value: everything from pricing flexibility to customer preference management to credit risk analysis to fraud protection and discount targeting. For the latest on Big Data & Advanced Analytics: http://mckinseyonmarketingandsales.com/topics/big-data
Hadoop is an open source software framework that supports data-intensive distributed applications. Hadoop is licensed under the Apache v2 license. It is therefore generally known as Apache Hadoop. Hadoop has been developed, based on a paper originally written by Google on MapReduce system and applies concepts of functional programming. Hadoop is written in the Java programming language and is the highest-level Apache project being constructed and used by a global community of contributors. Hadoop was developed by Doug Cutting and Michael J. Cafarella. And just don't overlook the charming yellow elephant you see, which is basically named after Doug's son's toy elephant!
The topics covered in presentation are:
1. Big Data Learning Path
2.Big Data Introduction
3. Hadoop and its Eco-system
4.Hadoop Architecture
5.Next Step on how to setup Hadoop
WANdisco is a provider of non-stop software for global enterprises to meet the challenges of Big Data and distributed software development.
KEY HIGHLIGHTS, Session 1: Tuesday, Feb. 26, 5:15 p.m.-6 p.m.
Hadoop and HBase on the Cloud: A Case Study on Performance and Isolation
Cloud infrastructure is a flexible tool to orchestrate multiple Hadoop and HBase clusters, which provides strict isolation of data and compute resources for multiple customers. Most importantly, our benchmarks show that virtualized environment allows for higher average utilization of per-node resources. For more session information, visit http://na.apachecon.com/schedule/presentation/131/.
CO-PRESENTERS, Dr. Konstantin V. Shvachko, Chief Architect, Big Data, WANdisco and Jagane Sundar, CTO/VP Engineering, Big Data, WANdisco
A veteran Hadoop developer and respected author, Konstantin Shvachko is a technical expert specializing in efficient data structures and algorithms for large-scale distributed storage systems. Konstantin joined WANdisco through the AltoStor acquisition and before that he was founder and Chief Scientist at AltoScale, a Hadoop and HBase-as-a-Platform company acquired by VertiCloud. Konstantin played a lead architectural role at eBay, building two generations of the organization's Hadoop platform. At Yahoo!, he worked on the Hadoop Distributed File System (HDFS). Konstantin has dozens of publications and presentations to his credit and is currently a member of the Apache Hadoop PMC. Konstantin has a Ph.D. in Computer Science and M.S. in Mathematics from Moscow State University, Russia.
Jagane Sundar has extensive big data, cloud, virtualization, and networking experience and joined WANdisco through its AltoStor acquisition. Before AltoStor, Jagane was founder and CEO of AltoScale, a Hadoop and HBase-as-a-Platform company acquired by VertiCloud. His experience with Hadoop began as Director of Hadoop Performance and Operability at Yahoo! Jagane has such accomplishments to his credit as the creation of Livebackup, development of a user mode TCP Stack for Precision I/O, development of the NFS and PPP clients and parts of the TCP stack for JavaOS for Sun MicroSystems, and more. Jagane received his B.E. in Electronics and Communications Engineering from Anna University.
About WANdisco
WANdisco ( LSE : WAND ) is a provider of enterprise-ready, non-stop software solutions that enable globally distributed organizations to meet today's data challenges of secure storage, scalability and availability. WANdisco's products are differentiated by the company's patented, active-active data replication technology, serving crucial high availability (HA) requirements, including Hadoop Big Data and Application Lifecycle Management (ALM). Fortune Global 1000 companies including AT&T, Motorola, Intel and Halliburton rely on WANdisco for performance, reliability, security and availability. For additional information, please visit www.wandisco.com.
EclipseCon Keynote: Apache Hadoop - An IntroductionCloudera, Inc.
Todd Lipcon explains why you should be interested in Apache Hadoop, what it is, and how it works. Todd also brings to light the Hadoop ecosystem and real business use cases that evolve around Hadoop and the ecosystem.
( EMC World 2012 ) :Apache Hadoop is now enterprise ready. This session reviews the features/roadmap of Hadoop. We will review some of the key capabilities of GPHD 1.x and our plans for 2012.
Supporting Financial Services with a More Flexible Approach to Big DataWANdisco Plc
In this webinar, WANdisco and Hortonworks look at three examples of using 'Big Data' to get a more comprehensive view of customer behavior and activity in the banking and insurance industries. Then we'll pull out the common threads from these examples, and see how a flexible next-generation Hadoop architecture lets you get a step up on improving your business performance. Join us to learn:
- How to leverage data from across an entire global enterprise
- How to analyze a wide variety of structured and unstructured data to get quick, meaningful answers to critical questions
- What industry leaders have put in place
Cloudera Sessions - Clinic 1 - Getting Started With HadoopCloudera, Inc.
If you are interested in Hadoop and its capabilities, but you are not sure where to begin, this is the session for you. Learn the basics of Hadoop, see how to spin up a development cluster in the cloud or on-premise, and start exploring ETL processing with SQL and other familiar tools
Overview of Big data, Hadoop and Microsoft BI - version1Thanh Nguyen
Big Data and advanced analytics are critical topics for executives today. But many still aren't sure how to turn that promise into value. This presentation provides an overview of 16 examples and use cases that lay out the different ways companies have approached the issue and found value: everything from pricing flexibility to customer preference management to credit risk analysis to fraud protection and discount targeting. For the latest on Big Data & Advanced Analytics: http://mckinseyonmarketingandsales.com/topics/big-data
Hadoop is an open source software framework that supports data-intensive distributed applications. Hadoop is licensed under the Apache v2 license. It is therefore generally known as Apache Hadoop. Hadoop has been developed, based on a paper originally written by Google on MapReduce system and applies concepts of functional programming. Hadoop is written in the Java programming language and is the highest-level Apache project being constructed and used by a global community of contributors. Hadoop was developed by Doug Cutting and Michael J. Cafarella. And just don't overlook the charming yellow elephant you see, which is basically named after Doug's son's toy elephant!
The topics covered in presentation are:
1. Big Data Learning Path
2.Big Data Introduction
3. Hadoop and its Eco-system
4.Hadoop Architecture
5.Next Step on how to setup Hadoop
WANdisco is a provider of non-stop software for global enterprises to meet the challenges of Big Data and distributed software development.
KEY HIGHLIGHTS, Session 1: Tuesday, Feb. 26, 5:15 p.m.-6 p.m.
Hadoop and HBase on the Cloud: A Case Study on Performance and Isolation
Cloud infrastructure is a flexible tool to orchestrate multiple Hadoop and HBase clusters, which provides strict isolation of data and compute resources for multiple customers. Most importantly, our benchmarks show that virtualized environment allows for higher average utilization of per-node resources. For more session information, visit http://na.apachecon.com/schedule/presentation/131/.
CO-PRESENTERS, Dr. Konstantin V. Shvachko, Chief Architect, Big Data, WANdisco and Jagane Sundar, CTO/VP Engineering, Big Data, WANdisco
A veteran Hadoop developer and respected author, Konstantin Shvachko is a technical expert specializing in efficient data structures and algorithms for large-scale distributed storage systems. Konstantin joined WANdisco through the AltoStor acquisition and before that he was founder and Chief Scientist at AltoScale, a Hadoop and HBase-as-a-Platform company acquired by VertiCloud. Konstantin played a lead architectural role at eBay, building two generations of the organization's Hadoop platform. At Yahoo!, he worked on the Hadoop Distributed File System (HDFS). Konstantin has dozens of publications and presentations to his credit and is currently a member of the Apache Hadoop PMC. Konstantin has a Ph.D. in Computer Science and M.S. in Mathematics from Moscow State University, Russia.
Jagane Sundar has extensive big data, cloud, virtualization, and networking experience and joined WANdisco through its AltoStor acquisition. Before AltoStor, Jagane was founder and CEO of AltoScale, a Hadoop and HBase-as-a-Platform company acquired by VertiCloud. His experience with Hadoop began as Director of Hadoop Performance and Operability at Yahoo! Jagane has such accomplishments to his credit as the creation of Livebackup, development of a user mode TCP Stack for Precision I/O, development of the NFS and PPP clients and parts of the TCP stack for JavaOS for Sun MicroSystems, and more. Jagane received his B.E. in Electronics and Communications Engineering from Anna University.
About WANdisco
WANdisco ( LSE : WAND ) is a provider of enterprise-ready, non-stop software solutions that enable globally distributed organizations to meet today's data challenges of secure storage, scalability and availability. WANdisco's products are differentiated by the company's patented, active-active data replication technology, serving crucial high availability (HA) requirements, including Hadoop Big Data and Application Lifecycle Management (ALM). Fortune Global 1000 companies including AT&T, Motorola, Intel and Halliburton rely on WANdisco for performance, reliability, security and availability. For additional information, please visit www.wandisco.com.
EclipseCon Keynote: Apache Hadoop - An IntroductionCloudera, Inc.
Todd Lipcon explains why you should be interested in Apache Hadoop, what it is, and how it works. Todd also brings to light the Hadoop ecosystem and real business use cases that evolve around Hadoop and the ecosystem.
( EMC World 2012 ) :Apache Hadoop is now enterprise ready. This session reviews the features/roadmap of Hadoop. We will review some of the key capabilities of GPHD 1.x and our plans for 2012.
Supporting Financial Services with a More Flexible Approach to Big DataWANdisco Plc
In this webinar, WANdisco and Hortonworks look at three examples of using 'Big Data' to get a more comprehensive view of customer behavior and activity in the banking and insurance industries. Then we'll pull out the common threads from these examples, and see how a flexible next-generation Hadoop architecture lets you get a step up on improving your business performance. Join us to learn:
- How to leverage data from across an entire global enterprise
- How to analyze a wide variety of structured and unstructured data to get quick, meaningful answers to critical questions
- What industry leaders have put in place
Контроль зверей: инструменты для управления и мониторинга распределенных сист...yaevents
Александр Козлов, Cloudera Inc.
Александр Козлов, старший архитектор в Cloudera Inc., работает с большими компаниями, многие из которых находятся в рейтинге Fortune 500, над проектами по созданию систем анализа большого количества данных. Закончил аспирантуру физического факультета Московского государственного университета, после чего также получил степень Ph.D. в Стэнфорде. До Cloudera и после окончания учебы работал над статистическим анализом данных и соответствующими компьютерными технологиями в SGI, Hewlett-Packard, а также стартапе Turn.
Тема доклада
Контроль зверей: инструменты для управления и мониторинга распределенных систем от Cloudera.
Тезисы
Поддержание распределенных систем, состоящих из тысяч компьютеров, является сложной задачей. Компания Cloudera, которая специализируется на создании распределенных технологий, разработала набор средств для централизованного управления распределенных Hadoop/HBase кластеров. Hadoop и HBase являются проектами Apache Software Foundation, и их применение для анализа частично структурированных данных ускоряется во всем мире. В этом докладе будет рассказано о SCM, системе для конфигурации, настройки, и управления Hadoop/HBase и Activity Monitor, системе для мониторинга ряда ОС и Hadoop/HBase метрик, а также об особенностях подхода Cloudera в отличие от существующих решений для мониторинга (Tivoli, xCat, Ganglia, Nagios и т.д.).
Content presented at a talk on Aug. 29th. Purpose is to inform a fairly technical audience on the primary tenets of Big Data and the hadoop stack. Also, did a walk-thru' of hadoop and some of the hadoop stack i.e. Pig, Hive, Hbase.
Hadoop and Internet of Things presentation from Sinergija 2014 conference, held in Belgrade in October 2014. How the rising data resources change the business, and how the Big Data technologies combined with Internet of Things devices can help to improve the business and the everyday life. Hadoop is already the most significant technology for working with Big Data. Microsoft is playing a very important role in this field, with the Stinger initiative. The main goal is to bring the enterprise SQL at Hadoop scale.
Hadoop Demystified + MapReduce (Java and C#), Pig, and Hive DemosLester Martin
A walk-thru of core Hadoop, the ecosystem tools, and Hortonworks Data Platform (HDP) followed by code examples in MapReduce (Java and C#), Pig, and Hive.
Presented at the Atlanta .NET User Group meeting in July 2014.
Coordinating the Many Tools of Big Data - Apache HCatalog, Apache Pig and Apa...Big Data Spain
Session presented at Big Data Spain 2012 Conference
16th Nov 2012
ETSI Telecomunicacion UPM Madrid
www.bigdataspain.org
More info: http://www.bigdataspain.org/es-2012/conference/coordinating-many-tools-of-big-data/alan-gates
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
The Metaverse and AI: how can decision-makers harness the Metaverse for their...Jen Stirrup
The Metaverse is popularized in science fiction, and now it is becoming closer to being a part of our daily lives through the use of social media and shopping companies. How can businesses survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and how does the Metaverse fit into business strategy when futurist ideas are developing into reality at accelerated rates? How do we do this when our data isn't up to scratch? How can we move towards success with our data so we are set up for the Metaverse when it arrives?
How can you help your company evolve, adapt, and succeed using Artificial Intelligence and the Metaverse to stay ahead of the competition? What are the potential issues, complications, and benefits that these technologies could bring to us and our organizations? In this session, Jen Stirrup will explain how to start thinking about these technologies as an organisation.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
4. It’s About the Ecosystem
Structured, Semi-structured
Cloud Computing
SaaS
Enterprise Data Warehouse
PaaS
IaaS
Generate
Big Data
Lead
Business Insights
create
Competition, Innovation,
Productivity
6. What is the problem
• Getting the data to the processors
becomes the bottleneck
• Quick calculation
– Typical disk data transfer rate:
• 75MB/sec
– Time taken to transfer 100GB of data
to the processor:
• approx. 22 minutes!
7. The Era of Big Data – Are You Ready
Data for business commercial analysis
• 2011: multi-terabyte (TB)
• 2020: 35.2 ZB (1 ZB = 1 billion TB)
8. Who Needs It?
Enterprise Database Hadoop
When to use? When to use?
• Ad-hoc Reporting (<1sec) • Affordable Storage/Compute
• Multi-step Transactions • Unstructured or Semi-structured
• Lots of Inserts/Updates/Deletes • Resilient Auto Scalability
10. – inspired by
• Apache Hadoop project
– inspired by Google's MapReduce and Google File System
papers.
• Open sourced, flexible and available architecture for
large scale computation and data processing on a
network of commodity hardware
• Open Source Software + Hardware Commodity
– IT Costs Reduction
15. Word Count Example
Key: offset
Value: line
Key: word Key: word
Value: count Value: sum of count
0:The cat sat on the mat
22:The aardvark sat on the sofa
17. The Ecosystem is the System
• Hadoop has become the kernel of the distributed
operating system for Big Data
• No one uses the kernel alone
• A collection of projects at Apache
20. What is ZooKeeper
• A centralized service for maintaining
– Configuration information
– Providing distributed synchronization
• A set of tools to build distributed applications that can
safely handle partial failures
• ZooKeeper was designed to store coordination data
– Status information
– Configuration
– Location information
22. What’s the problem for data collection
• Data collection is currently a priori and ad hoc
• A priori – decide what you want to collect ahead of time
• Ad hoc – each kind of data source goes through its own
collection path
23. (and how can it help?)
• A distributed data collection service
• It efficiently collecting, aggregating, and moving large
amounts of data
• Fault tolerant, many failover and recovery mechanism
• One-stop solution for data collection of all formats
30. Why Hive and Pig?
• Although MapReduce is very powerful, it can also be
complex to master
• Many organizations have business or data analysts who
are skilled at writing SQL queries, but not at writing Java
code
• Many organizations have programmers who are skilled
at writing code in scripting languages
• Hive and Pig are two projects which evolved separately
to help such people analyze huge amounts of data via
MapReduce
– Hive was initially developed at Facebook, Pig at Yahoo!
31. Hive – Developed by
• What is Hive?
– An SQL-like interface to Hadoop
• Data Warehouse infrastructure that provides data
summarization and ad hoc querying on top of Hadoop
– MapRuduce for execution
– HDFS for storage
• Hive Query Language
– Basic-SQL : Select, From, Join, Group-By
– Equi-Join, Muti-Table Insert, Multi-Group-By
– Batch query
SELECT * FROM purchases WHERE price > 100 GROUP BY storeid
33. Pig – Initiated by
• A high-level scripting language (Pig Latin)
• Process data one step at a time
• Simple to write MapReduce program
• Easy understand
• Easy debug A = load ‘a.txt’ as (id, name, age, ...)
B = load ‘b.txt’ as (id, address, ...)
C = JOIN A BY id, B BY id;STORE C into ‘c.txt’
35. Hive vs. Pig
Hive Pig
Language HiveQL (SQL-like) Pig Latin, a scripting language
Schema Table definitions A schema is optionally defined
that are stored in a at runtime
metastore
Programmait Access JDBC, ODBC PigServer
36. WordCount Example
• Input
Hello World Bye World
Hello Hadoop Goodbye Hadoop
• For the given sample input the map emits
< Hello, 1>
< World, 1>
< Bye, 1>
< World, 1>
< Hello, 1>
< Hadoop, 1>
< Goodbye, 1>
< Hadoop, 1>
• the reduce just sums up the values
< Bye, 1>
< Goodbye, 1>
< Hadoop, 2>
< Hello, 2>
< World, 2>
37. WordCount Example In MapReduce
public class WordCount {
public static class Map extends Mapper<LongWritable, Text, Text, IntWritable> {
private final static IntWritable one = new IntWritable(1);
private Text word = new Text();
public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
String line = value.toString();
StringTokenizer tokenizer = new StringTokenizer(line);
while (tokenizer.hasMoreTokens()) {
word.set(tokenizer.nextToken());
context.write(word, one);
}
}
}
public static class Reduce extends Reducer<Text, IntWritable, Text, IntWritable> {
public void reduce(Text key, Iterable<IntWritable> values, Context context)
throws IOException, InterruptedException {
int sum = 0;
for (IntWritable val : values) {
sum += val.get();
}
context.write(key, new IntWritable(sum));
}
}
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
Job job = new Job(conf, "wordcount");
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
job.setMapperClass(Map.class);
job.setReducerClass(Reduce.class);
job.setInputFormatClass(TextInputFormat.class);
job.setOutputFormatClass(TextOutputFormat.class);
FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
job.waitForCompletion(true);
}
38. WordCount Example By Pig
A = LOAD 'wordcount/input' USING PigStorage as (token:chararray);
B = GROUP A BY token;
C = FOREACH B GENERATE group, COUNT(A) as count;
DUMP C;
39. WordCount Example By Hive
CREATE TABLE wordcount (token STRING);
LOAD DATA LOCAL INPATH ’wordcount/input'
OVERWRITE INTO TABLE wordcount;
SELECT count(*) FROM wordcount GROUP BY token;
43. I – Inspired by
• Coordinated by Zookeeper
• Low Latency
• Random Reads And Writes
• Distributed Key/Value Store
• Simple API
– PUT
– GET
– DELETE
– SCAN
44. Hbase – Data Model
• Cells are “versioned”
• Table rows are sorted by row key
• Region – a row range [start-key:end-key]
47. What is ?
• A Java Web Application
• Oozie is a workflow scheduler for Hadoop
• Crond for Hadoop
• Triggered Job 1 Job 2
– Time
– Data
Job 3
Job 4 Job 5
50. What is
• Machine-learning tool
• Distributed and scalable machine learning algorithms on
the Hadoop platform
• Building intelligent applications easier and faster
52. Hue – developed by
• Hadoop User Experience
• Apache Open source project
• HUE is a web UI for Hadoop
• Platform for building custom applications with a nice UI
library
53. Hue
• HUE comes with a suite of applications
– File Browser: Browse HDFS; change permissions and
ownership; upload, download, view and edit files.
– Job Browser: View jobs, tasks, counters, logs, etc.
– Beeswax: Wizards to help create Hive tables, load data, run and
manage Hive queries, and download results in Excel format.
56. Use case Example
• Predict what the user likes based on
– His/Her historical behavior
– Aggregate behavior of people similar to him
57. Conclusion
Today, we introduced:
• Why Hadoop is needed
• The basic concepts of HDFS and MapReduce
• What sort of problems can be solved with Hadoop
• What other projects are included in the Hadoop
ecosystem
63. New Design Concept for Threat Intelligence
CDN / xSP Human
Intelligence
Honeypot
Web Crawler
Trend Micro
Mail Protection
Trend Micro
Trend Micro Endpoint Protection
Web Protection
150M+ Worldwide Endpoints/Sensors
64. Challenges We Are Faced
The Concept is Great but ….
6TB of data and 15B lines of logs received daily by
It becomes the Big Data Challenge!
65. Issues to Address
Threat
Raw Data Information Intelligence/Solution
Volume: Infinite
Time: No Delay
Target: Keep Changing Threats
66. SPN
Feedback
SPAM
CDN Log SPN High Level Architecture
HTTP POST
L4
Log Log
Receiver Receiver
L4
Log Post Log Post Log Post
Processing Processing Processing
SPN infrastructure
Adhoc-Query (Pig)
MapReduce HBase
Circus
Hadoop Distributed File System (Ambari)
(HDFS)
Feedback Information
Message Bus
Application
Email Reputation Service Web Reputation File Reputation
Service Service
67. Trend Micro Big Data process capacity
雲端防毒每日需要處理的資料量
• 85 億個 Web Reputation 查詢
• 30 億個 Email Reputation查詢
• 70 億個 File Reputation 查詢
• 處理 6 TB 從全世界收集到的 raw logs
• 來自1.5億台終端裝置的連線
68. Trend Micro: Web Reputation Services
Technology Process Operation
Trend Micro User Traffic | Honeypot
Products / Technology
8 billions/day
Akamai 40% filtered
CDN Cache
4.8 billions/day
Rating Server for Known
15 Minutes
High Throughput Web Service Threats 82% filtered
Unknown & Prefilter
Hadoop Cluster
860 millions/day
Page Download
Web Crawling
99.98% filtered
Threat
Analysis
Machine Learning
Data Mining
25,000 malicious URL /day
Block malicious URL within 15 minutes once it goes online!
72. Hbase use Case@Facebook - Messages
HBase Use Cases @ Facebook
Facebook Insights Operational Data Store
Self-service More Analytics/Hashout apps
Messages Hashout Site Integrity
2010 2011 2012 2013
Social Graph Search Indexing
Realtime Hive Updates
Cross-system Tracing
… and more
73. Flagship App:Facebook Messages
Monthly data volume prior to launch
• Monthly data volume prior to launch
15B x 1,024 bytes = 14TB
120B x 100 bytes = 11TB
74. Facebook Messages Now
book Messages NOW
•
StatsQuick Stats
Messages Chats
– 11B+ messages/day
• 90B+ data accesses
+ messages/day
• Peak:1.5M ops/sec
0B+ data~55% Read, 45% Write
•
accesses
eak: 1.5M ops/sec
55%Rd, 45% Wr data
– 20PB+ of total
Emails SMS
• Grows 400TB/month
B+ of total data
rows 400TB/month
75. Facebook Messages:Requirements
• Very High Write Volume
– Previously, chat was not persisted to disk
• Ever-growing data sets(Old data rarely gets
accessed)
• Elasticity & automatic failover
• Strong consistency within a single data center
• Large scans/map-reduce support for migrations &
schema conversions
• Bulk import data
76. Physical Multi-tenancy
• Real-time Ads Insights
– Real-time analytics for social plugins on top of Hbase
– Publishers get real-time distribution/engagement metrics:
• # of impressions, likes
• analytics by domain/URL/demographics and time periods
– Uses HBase capabilities:
• Efficient counters (single-RPC increments)
• TTL for purging old data
– Needs massive write throughput & low latencies
• Billions of URLs
• Millions of counter increments/second
• Operational Data Store
77. Facebook Open Source Stack
• Memcached --> App Server Cache
• ZooKeeper --> Small Data Coordination Service
• HBase --> Database Storage Engine
• HDFS --> Distributed FileSystem
• Hadoop --> Asynchronous Map-Reduce Jobs