Hadoop, Evolution of Hadoop, Features of HadoopDr Neelesh Jain
Hadoop, Evolution of Hadoop, Features of Hadoop is explained in the presentation as per the syllabus of RGPV, BU and MCU for the students of BCA, MCA and B. Tech.
With the advent of Hadoop, there comes the need for professionals skilled in Hadoop Administration making it imperative to be skilled as a Hadoop Admin for better career, salary and job opportunities.
The following blogs will help you understand the significance of Hadoop Administration training:
http://www.edureka.co/blog/why-should-you-go-for-hadoop-administration-course/
http://www.edureka.co/blog/how-to-become-a-hadoop-administrator/
http://www.edureka.co/blog/hadoop-admin-responsibilities/
Hadoop, Evolution of Hadoop, Features of HadoopDr Neelesh Jain
Hadoop, Evolution of Hadoop, Features of Hadoop is explained in the presentation as per the syllabus of RGPV, BU and MCU for the students of BCA, MCA and B. Tech.
With the advent of Hadoop, there comes the need for professionals skilled in Hadoop Administration making it imperative to be skilled as a Hadoop Admin for better career, salary and job opportunities.
The following blogs will help you understand the significance of Hadoop Administration training:
http://www.edureka.co/blog/why-should-you-go-for-hadoop-administration-course/
http://www.edureka.co/blog/how-to-become-a-hadoop-administrator/
http://www.edureka.co/blog/hadoop-admin-responsibilities/
Hadoop Interview Questions and Answers by rohit kapakapa rohit
Hadoop Interview Questions and Answers - More than 130 real time questions and answers covering hadoop hdfs,mapreduce and administrative concepts by rohit kapa
With the advent of Hadoop, there comes the need for professionals skilled in Hadoop Administration making it imperative to be skilled as a Hadoop Admin for better career, salary and job opportunities.
The Hadoop Cluster Administration course at Edureka starts with the fundamental concepts of Apache Hadoop and Hadoop Cluster. It covers topics to deploy, manage, monitor, and secure a Hadoop Cluster. You will learn to configure backup options, diagnose and recover node failures in a Hadoop Cluster. The course will also cover HBase Administration. There will be many challenging, practical and focused hands-on exercises for the learners. Software professionals new to Hadoop can quickly learn the cluster administration through technical sessions and hands-on labs. By the end of this six week Hadoop Cluster Administration training, you will be prepared to understand and solve real world problems that you may come across while working on Hadoop Cluster.
Hadoop Administrator Online training course by (Knowledgebee Trainings) with mastering Hadoop Cluster: Planning & Deployment, Monitoring, Performance tuning, Security using Kerberos, HDFS High Availability using Quorum Journal Manager (QJM) and Oozie, Hcatalog/Hive Administration.
Contact : knowledgebee@beenovo.com
With the advent of Hadoop, there comes the need for professionals skilled in Hadoop Administration making it imperative to be skilled as a Hadoop Admin for better career, salary and job opportunities.
Here is our most popular Hadoop Interview Questions and Answers from our Hadoop Developer Interview Guide. Hadoop Developer Interview Guide has over 100 REAL Hadoop Developer Interview Questions with detailed answers and illustrations asked in REAL interviews. The Hadoop Interview Questions listed in the guide are not "might be" asked interview question, they were asked in interviews at least once.
More about Hadoop
www.beinghadoop.com
https://www.facebook.com/hadoopinfo
This PPT Gives information about
Complete Hadoop Architecture and
information about
how user request is processed in Hadoop?
About Namenode
Datanode
jobtracker
tasktracker
Hadoop installation Post Configurations
These slides cover the very basics of Hadoop architecture, in particular HDFS. This was my presentation in the first Delhi Hadoop User Group (DHUG) meetup held at Gurgaon on 10th September 2011. Loved the positive feedback. I'll also upload a more elaborate version covering Hadoop mapreduce architecture as well soon. Most of the stuff covered in these slides can be found in Tom White's book as well (See the last slide)
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. The Topics covered in the presentation are:
1. Understand Cluster Planning
2.Understand Hadoop Fully Distributed Cluster Setup with two nodes.
3.Add further nodes to the running cluster
4.Upgrade existing Hadoop cluster from Hadoop 1 to Hadoop 2
5.Understand Active namenode failure and how passive takes over
Accompanying slides for the class “Introduction to Hadoop” at the PRACE Autumn school 2020 - HPC and FAIR Big Data organized by the faculty of Mechanical Engineering of the University of Ljubljana (Slovenia).
Hadoop Interview Questions and Answers by rohit kapakapa rohit
Hadoop Interview Questions and Answers - More than 130 real time questions and answers covering hadoop hdfs,mapreduce and administrative concepts by rohit kapa
With the advent of Hadoop, there comes the need for professionals skilled in Hadoop Administration making it imperative to be skilled as a Hadoop Admin for better career, salary and job opportunities.
The Hadoop Cluster Administration course at Edureka starts with the fundamental concepts of Apache Hadoop and Hadoop Cluster. It covers topics to deploy, manage, monitor, and secure a Hadoop Cluster. You will learn to configure backup options, diagnose and recover node failures in a Hadoop Cluster. The course will also cover HBase Administration. There will be many challenging, practical and focused hands-on exercises for the learners. Software professionals new to Hadoop can quickly learn the cluster administration through technical sessions and hands-on labs. By the end of this six week Hadoop Cluster Administration training, you will be prepared to understand and solve real world problems that you may come across while working on Hadoop Cluster.
Hadoop Administrator Online training course by (Knowledgebee Trainings) with mastering Hadoop Cluster: Planning & Deployment, Monitoring, Performance tuning, Security using Kerberos, HDFS High Availability using Quorum Journal Manager (QJM) and Oozie, Hcatalog/Hive Administration.
Contact : knowledgebee@beenovo.com
With the advent of Hadoop, there comes the need for professionals skilled in Hadoop Administration making it imperative to be skilled as a Hadoop Admin for better career, salary and job opportunities.
Here is our most popular Hadoop Interview Questions and Answers from our Hadoop Developer Interview Guide. Hadoop Developer Interview Guide has over 100 REAL Hadoop Developer Interview Questions with detailed answers and illustrations asked in REAL interviews. The Hadoop Interview Questions listed in the guide are not "might be" asked interview question, they were asked in interviews at least once.
More about Hadoop
www.beinghadoop.com
https://www.facebook.com/hadoopinfo
This PPT Gives information about
Complete Hadoop Architecture and
information about
how user request is processed in Hadoop?
About Namenode
Datanode
jobtracker
tasktracker
Hadoop installation Post Configurations
These slides cover the very basics of Hadoop architecture, in particular HDFS. This was my presentation in the first Delhi Hadoop User Group (DHUG) meetup held at Gurgaon on 10th September 2011. Loved the positive feedback. I'll also upload a more elaborate version covering Hadoop mapreduce architecture as well soon. Most of the stuff covered in these slides can be found in Tom White's book as well (See the last slide)
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. The Topics covered in the presentation are:
1. Understand Cluster Planning
2.Understand Hadoop Fully Distributed Cluster Setup with two nodes.
3.Add further nodes to the running cluster
4.Upgrade existing Hadoop cluster from Hadoop 1 to Hadoop 2
5.Understand Active namenode failure and how passive takes over
Accompanying slides for the class “Introduction to Hadoop” at the PRACE Autumn school 2020 - HPC and FAIR Big Data organized by the faculty of Mechanical Engineering of the University of Ljubljana (Slovenia).
How the new operation of Hadoop Distributed FIle System (HDFS) -- Append works. The internals of the processing. The new states that are more than the write operation.
Fundamentals of Big Data, Hadoop project design and case study or Use case
General planning consideration and most necessaries in Hadoop ecosystem and Hadoop projects
This will provide the basis for choosing the right Hadoop implementation, Hadoop technologies integration, adoption and creating an infrastructure.
Building applications using Apache Hadoop with a use-case of WI-FI log analysis has real life example.
Enroll Free Live demo of Hadoop online training and big data analytics courses online and become certified data analyst/ Hadoop developer. Get online Hadoop training & certification.
Impetus provides expert consulting services around Hadoop implementations, including R&D, assessment, deployment (on private and public clouds), optimizations for enhanced static shared data implementations.
This presentation speaks about Advanced Hadoop Tuning and Optimisation.
Schedulers optimization to handle multiple jobs in hadoop clusterShivraj Raj
This effort is projected to give a high level summary of what is Big data and how to solve the issues generated through four V’s and stored in HDFS using various configuration parameters by setting up Hadoop, Pig and Hive to retrieve useful data from bulky data sets.
With the advent of Hadoop, there comes the need for professionals skilled in Hadoop Administration making it imperative to be skilled as a Hadoop Admin for better career, salary and job opportunities.
Know how to setup a Hadoop Cluster With HDFS High Availability here : www.edureka.co/blog/how-to-set-up-hadoop-cluster-with-hdfs-high-availability/
Enroll Free Live demo of Hadoop online training and big data analytics courses online and become certified data analyst/ Hadoop developer. Get online Hadoop training & certification.
#LibreOffice is a #free and powerful #officesuite, and a successor to #OpenOffice.org (commonly known as #OpenOffice).
Its clean interface and feature-rich tools help you unleash your #creativity and enhance your #productivity. #LibreOffice includes several applications that make it the most versatile #Free and #OpenSource office suite on the market: #Writer (#wordprocessing), Calc (#spreadsheets), Impress (presentations), #Draw (vector graphics and #flowcharts), Base (#databases), and #Math (#formula editing).
#LibreOffice is #community-driven and #developed #software, and is a project of the #nonprofit #organization, The #Document #Foundation. #LibreOffice is free and #opensource software, originally based on #OpenOffice.org (commonly known as OpenOffice), and is the most actively developed OpenOffice.org successor project.
#LibreOffice is developed by users who, just like you, believe in the principles of #FreeSoftware and in sharing their work with the world in non-restrictive ways.
This office suite can easily replace costly paid option available. If you need a good office suite which is easily and freely available you can for sure give a try and.
It has following features/components for making your work easy and cost free and vendor independent:
Writer – word processor
Calc – spreadsheet
Impress – presentations
Draw – diagrams
Base – database
Math – formula editor
Charts
Better #collaboration
#Sharingdocuments and edits with other users have been enhanced and well tracked, to make modifications more clear.
Work faster in Calc
Working with #Spreadsheet has the new #Bash-like autocompletion feature helps you to input data in a snap.
#Barcodes and borders
We can now insert #barcodes into your #documents with just a few clicks
For Full information about the release you can visit if your are interested.
https://wiki.documentfoundation.org/ReleaseNotes/7.3
If you need any help you can reach out here
https://twitter.com/libreoffice
https://blog.documentfoundation.org/
https://www.facebook.com/libreoffice.org
https://twitter.com/AskLibreOffice
What Next :
#LibreOffice 7.4 – is next major release in August, you can try installing and test it and help the developers to find if any bug or issue or need any improvement.
Let's install and explore.
We will now install it in #Ubuntu and explore this a bit
#SystemArchitecture Series: #Kerberos Architecture Component and communication flow #architecture
#Kerberos is a ticketing-based #authentication #system, based on the use of #symmetric keys. #Kerberos uses tickets to provide #authentication to resources instead of #passwords. This eliminates the threat of #password stealing via #networksniffing. One of the biggest benefits of #Kerberos is its ability to provide single sign-on (#SSO). Once you log into your #Kerberos environment, you will be automatically logged into other applications in the environment.
To help provide a secure environment, #Kerberos makes use of Mutual #Authentication. In Mutual #Authentication, both the #server and the #client must be authenticated. The client knows that the server can be trusted, and the server knows that the client can be trusted. This #authentication helps prevent man-in-the-middle attacks and #spoofing. #Kerberos is also time sensitive. The tickets in a #Kerberosenvironment must be renewed periodically or they will expire.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
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!
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
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/
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
2. Table of Contents
....................................................................... 0
I.
II.
UPGRADE ............................................................................................................ 0
III.
Table of Contents ...................................................................................................1
IV.
Upgrading Cluster with new Cluster- (Method 1) ................................................ 2
Objective:
Pre-requisites:
Process Flow:
Methods and Process Flow:
Pros and Cons:
Cons
Pros
V.
Upgrading Existing cluster inline- (Method 2) .................................................... 4
Objective:
Pre-requisites:
Common assumptions
Methods and Process Flow:
Pros and Cons:
Cons
Pros
3. Upgrading Cluster with new Cluster- Method 1
Objective:
Upgrade a cluster by configuring a new cluster with same capacity and newer Hadoop version and then migrating the
files from old cluster to new one.
Pre-requisites:
1.
2.
3.
Full-fledged running cluster.
A newly configured cluster with newer version with same amount of resources or better.
Methods to migrate file from older cluster to new one.
Process Flow:
Using CopyToLocal
And
CopyFromLocal
Existing Cluster
V 1.0
New Cluster
Migrate data using
Hadoop cp command
from one cluster to other
V2.0
Using Hadoop distcp to
copy data from one
cluster to other
Methods and Process Flow:
1. CopyToLocal /CopyFromLocal:
The process flows, the files are copied to local drive using Hadoop command CopyToLocal and the files are then
pushed to the new cluster using CopyFromLocal, and the older cluster can be decommissioned.
2. Using Hadoop CP command :
This is a kind of cluster to cluster copy, using Hadoop ‘cp’ command the files are transferred from one HDFS to
other HDFS. As the version are different we need a mechanism called copy from HFTP where the command is
executed from the target cluster by defining source as old cluster with HFTP protocol and target as HDFS protocol.
3. Using Hadoop DISTCP command:
This is a kind of cluster to cluster copy, using Hadoop ‘distcp’ command the files are transferred from one HDFS
to other HDFS. As the version are different we need a mechanism called copy from HFTP where the command is
executed from the target cluster by defining source as old cluster with HFTP protocol and target as HDFS protocol.
In addition map-reduce to be run the cluster (Job Tracker and the task tracker must be running on the both the
cluster). This is a faster approaches to migrate data from one cluster to other one.
UPGRADING HADOOP - OCTOBER 2013
2
4. Pros and Cons:
Cons:
Slow process.
Additional intermediate is required in case of copy to local and copy from local
Overhead of copying files in case of cp and distcp.
Pros:
Safe
Always old cluster is there as a backup
Online/No downtime is required
UPGRADING HADOOP - OCTOBER 2013
3
5. Upgrading Existing cluster inline- Method 2
Hadoop V1
Hadoop V2
HDFS Upgraded Metadata HDFS
Objective:
Upgrading existing cluster from V1 to V2 inline by installing/configuring new cluster and updating metadata.
Pre-requisites:
1.
2.
Backed up Metadata.
Metadata at safe location, so that it can be restored in case upgrade process is not successful.
Common assumptions
Newer versions should provide automatic support and conversion of the older versions data structures.
Downgrades are not supported. In some cases, when e.g. data structure layouts are not affected by particular
version the downgrade may be possible. In general, Hadoop does not provide tools to convert data from newer
versions to older ones.
Different Hadoop components should be upgraded simultaneously.
Inter-version compatibility is not supported. In some cases when e.g. communication protocols remain
unchanged different versions of different components may be compatible. For example, Jobtracker v.0.4.0 can
communicate with Namenode v.0.3.2. In general, Hadoop does not guarantee compatibility of components of
different versions.
Points to keep in mind while upgrading!
IF FOLLOWING HAPPENS DURING UPGRADE THERE MAY BE FULL DATA LOSS
Hardware failure
Software errors, and
Human mistakes
UPGRADING HADOOP - OCTOBER 2013
4
6. Methods and Process Flow:
Stop map-reduce cluster(s) and all client applications running on the DFS cluster.
Stop DFS using the shutdown command.
Install new version of Hadoop software.
Start DFS cluster with -upgrade option.
Start map-reduce cluster.
Verify the components run properly and finalize the upgrade when convinced. This is done using the finalizeUpgrade option to the hadoop dfsadmin command.
Pros and Cons:
Cons:
Chance of data loss if not handled properly.
Requires downtime.
Business impact if 100% up time is required.
Rollback overhead in case of failure.
Pros:
No extra storage is required.
Upgrade Happens in line with metadata update.
Less time taken for data migration.
UPGRADING HADOOP - OCTOBER 2013
5
7. Step by step up gradation process
Link:
http://wiki.apache.org/hadoop/Hadoop_Upgrade
Upgrade is an important part of the lifecycle of any software system, especially a distributed multi-component system like
Hadoop. This is a step-by-step procedure a Hadoop cluster administrator should follow in order to safely transition the
cluster to a newer software version. This is a general procedure, for particular version specific instructions please
additionally refer to the release notes and version change descriptions.
The purpose of the procedure is to minimize damage to the data stored in Hadoop during upgrades, which could be a result
of the following three types of errors:
1.
Hardware failure is considered normal for the operation of the system, and should be handled by the software.
2.
3.
Software errors, and
Human mistakes
can lead to partial or complete data loss.
In our experience the worst damage to the system is incurred when as a result of a software or human mistake the name
node decides that some blocks/files are redundant and issues a command for data nodes to remove the blocks. Although a
lot has been done to prevent this behavior the scenario is still possible.
Common assumptions:
Newer versions should provide automatic support and conversion of the older versions data structures.
Downgrades are not supported. In some cases, when e.g. data structure layouts are not affected by particular
version the downgrade may be possible. In general, Hadoop does not provide tools to convert data from newer
versions to older ones.
Different Hadoop components should be upgraded simultaneously.
Inter-version compatibility is not supported. In some cases when e.g. communication protocols remain unchanged
different versions of different components may be compatible. For example, JobTracker v.0.4.0 can communicate
with NameNode v.0.3.2. In general, Hadoop does not guarantee compatibility of components of different versions.
Instructions:
1.
Stop
map-reduce
cluster(s)
bin/stop-mapred.sh
and all client applications running on the DFS cluster.
2.
Run fsck command:
bin/hadoop fsck / -files -blocks -locations > dfs-v-old-fsck-1.log
Fix DFS to the point there are no errors. The resulting file will contain complete block map of the file system.
Note. Redirecting the fsck output is recommend for large clusters in order to avoid time consuming output to
stdout.
3.
Run lsr command:
bin/hadoop dfs -lsr / > dfs-v-old-lsr-1.log
The resulting file will contain complete namespace of the file system.
4.
Run report command
to
create
a
list
of
data
nodes
participating
in
the
cluster.
bin/hadoop dfsadmin -report > dfs-v-old-report-1.log
5.
6.
Optionally, copy all or unrecoverable only data stored in DFS to a local file system or a backup instance of DFS.
Optionally, stop and restart DFS cluster, in order to create an up-to-date namespace checkpoint of the old version.
bin/stop-dfs.sh
bin/start-dfs.sh
UPGRADING HADOOP - OCTOBER 2013
6
8. 7.
Optionally, repeat 3, 4, 5, and compare the results with the previous run to ensure the state of the file system
remained unchanged.
8.
Copy
the
following
checkpoint
files
into
a
backup
directory:
dfs.name.dir/edits
dfs.name.dir/image/fsimage
9.
Stop
DFS
cluster.
bin/stop-dfs.sh
Verify that DFS has really stopped, and there are no DataNode processes running on any nodes.
10. Install new version of Hadoop software. See GettingStartedWithHadoop and HowToConfigure for details.
11. Optionally, update the conf/slaves file before starting, to reflect the current set of active nodes.
12. Optionally, change the configuration of the name node’s and the job tracker’s port numbers, to ignore unreachable
nodes that are running the old version, preventing them from connecting and disrupting system operation.
fs.default.name
mapred.job.tracker
13. Optionally,
start
name
node
only.
bin/hadoop-daemon.sh start namenode -upgrade
This should convert the checkpoint to the new version format.
run lsr command:
14. Optionally,
bin/hadoop dfs -lsr / > dfs-v-new-lsr-0.log
and compare with dfs-v-old-lsr-1.log
15. Start
DFS
cluster.
bin/start-dfs.sh
16. Run
report
command:
bin/hadoop dfsadmin -report > dfs-v-new-report-1.log
and compare with dfs-v-old-report-1.log to ensure all data nodes previously belonging to the cluster
are up and running.
17. Run lsr command:
bin/hadoop dfs -lsr / > dfs-v-new-lsr-1.log
and compare with dfs-v-old-lsr-1.log. These files should be identical unless the format
of lsr reporting or the data structures have changed in the new version.
18. Run fsck command:
bin/hadoop fsck / -files -blocks -locations > dfs-v-new-fsck-1.log
and compare with dfs-v-old-fsck-1.log. These files should be identical, unless the fsck reporting
format has changed in the new version.
19. Start
map-reduce
cluster
bin/start-mapred.sh
In case of failure the administrator should have the checkpoint files in order to be able to repeat the procedure from the
appropriate point or to restart the old version of Hadoop. The *.log files should help in investigating what went wrong
during the upgrade.
Enhancements:
This is a list of enhancements intended to simplify the upgrade procedure and to make the upgrade safer in general.
1.
2.
A shutdown function is required for Hadoop that would cleanly shut down the cluster, merging edits into the
image, avoiding the restart-DFS phase.
The safe mode implementation will further help to prevent name node from voluntary decisions on block deletion
and replication.
3.
A faster fsck is required. Currently fsck processes 1-2 TB per minute.
4.
Hadoop should provide a backup solution as a stand alone application.
5.
6.
Introduce an explicit -upgrade option for DFS (See below) and a related
finalize upgrade command.
Shutdown command:
During the shutdown the name node performs the following actions.
UPGRADING HADOOP - OCTOBER 2013
7
9. It locks the namespace for further modifications and waits for active leases to expire, and pending block
replications and deletions to complete.
Runs fsck, and optionally saves the result in a file provided.
Checkpoints and replicates the namespace image.
Sends shutdown command to all data nodes and verifies they actually turned themselves off by waiting for as long
as 5 heartbeat intervals during which no heartbeats should be reported.
Stops all running threads and terminates itself.
Upgrade option for DFS:
The main idea of upgrade is that each version that modifies data structures on disk has its own distinct working directory.
For instance, we'd have a "v0.6" and a “v0.7” directory for the name node and for all data nodes. These version directories
will be automatically created when a particular file system version is brought up for the first time. If DFS is started with the upgrade option the new file system version will do the following:
The name node will start in the read-only mode and will read in the old version checkpoint converting it to the new
format.
Create a new working directory corresponding to the new version and save the new image into it. The old
checkpoint will remain untouched in the working directory corresponding to the old version.
The name node will pass the upgrade request to the data nodes.
Each data node will create a working directory corresponding to the new version. If there is metadata in side files it
will be re-generated in the new working directory.
Then the data node will hard link blocks from the old working directory to the new one. The existing blocks will
remain untouched in their old directories.
The data node will confirm the upgrade and send its new block report to the name node.
Once the name node received the upgrade confirmations from all data nodes it will run the fsck and then switch
to the normal mode when it’s ready to serve clients’ requests.
This ensures that a snapshot of the old data is preserved until the new version is validated and tested to function properly.
Following the upgrade the file system can be run for a week or so to gain confidence. It can be rolled back to the
old snapshot if it breaks, or the upgrade can be “finalized” by admin using the “finalize upgrade” command, which would
remove old version working directories.
Care must be taken to deal with data nodes that are missing during the upgrade stage. In order to deal with such nodes the
name node should store the list of data nodes that have completed the upgrade, and reject data nodes that did not confirm
the upgrade.
When DFS will allow modification of blocks, this will require copying blocks into the current version working directory before
modifying them.
Linking allows the data from several versions of Hadoop to coexist and even evolve on the same hardware without
duplicating common parts.
Finalize Upgrade:
When the Hadoop administrator is convinced that the new version works properly he/she/it can issue a “finalize upgrade”
request.
The finalize request is first passed to the data nodes so that they could remove their previous version working
directories with all block files. This does not necessarily lead to physical removal of the blocks as long as they still
are referenced from the new version.
When the name node receives confirmation from all data nodes that current upgrade is finalized it will remove its
own old version directory and the checkpoint in it thus completing the upgrade and making it permanent.
The finalize upgrade procedure can run in the background without disrupting the cluster performance. Being in finalize mode
the name node will periodically verify confirmations from the data nodes and finalize itself when the load is light.
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10. Simplified Upgrade Procedure:
The new utilities will substantially simplify the upgrade procedure:
1.
2.
3.
4.
5.
6.
Stop map-reduce cluster(s) and all client applications running on the DFS cluster.
Stop DFS using the shutdown command.
Install new version of Hadoop software.
Start DFS cluster with -upgrade option.
Start map-reduce cluster.
Verify the components run properly and finalize the upgrade when convinced. This is done using the finalizeUpgrade option to the hadoop dfsadmin command.
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