In this session you will learn:
Flume Overview
Flume Agent
Sinks
Flume Installation
What is Netcat & Telnet?
For more information, visit: https://www.mindsmapped.com/courses/big-data-hadoop/hadoop-developer-training-a-step-by-step-tutorial/
In this session you will learn:
1. Kafka Overview
2. Need for Kafka
3. Kafka Architecture
4. Kafka Components
5. ZooKeeper Overview
6. Leader Node
For more information, visit: https://www.mindsmapped.com/courses/big-data-hadoop/hadoop-developer-training-a-step-by-step-tutorial/
In this session you will learn:
PIG
PIG - Overview
Installation and Running Pig
Load in Pig
Macros in Pig
For more information, visit: https://www.mindsmapped.com/courses/big-data-hadoop/hadoop-developer-training-a-step-by-step-tutorial/
Get acquainted with a distributed, reliable tool/service for collecting a large amount of streaming data to centralized storage with their architecture.
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
take care!
In this session you will learn:
1. Kafka Overview
2. Need for Kafka
3. Kafka Architecture
4. Kafka Components
5. ZooKeeper Overview
6. Leader Node
For more information, visit: https://www.mindsmapped.com/courses/big-data-hadoop/hadoop-developer-training-a-step-by-step-tutorial/
In this session you will learn:
PIG
PIG - Overview
Installation and Running Pig
Load in Pig
Macros in Pig
For more information, visit: https://www.mindsmapped.com/courses/big-data-hadoop/hadoop-developer-training-a-step-by-step-tutorial/
Get acquainted with a distributed, reliable tool/service for collecting a large amount of streaming data to centralized storage with their architecture.
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
take care!
Apache Flume is a simple yet robust data collection and aggregation framework which allows easy declarative configuration of components to pipeline data from upstream source to backend services such as Hadoop HDFS, HBase and others.
Get to know the configuration with Hadoop installation types and also handling of the HDFS files.
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Talk soon!
In this session you will learn:
Hadoop Data Types
Hadoop MapReduce Paradigm
Map and Reduce Tasks
Map Phase
MapReduce: The Reducer
IOException & JobConf
For more information, visit: https://www.mindsmapped.com/courses/big-data-hadoop/hadoop-developer-training-a-step-by-step-tutorial/
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.
Well illustrated with definitions of Apache Hive with its architecture workflows plus with the types of data available for Apache Hive
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Well-defined introduction about working with Big Data and introduction to the Hadoop Ecosystem.
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Talk soon!
Design data pipeline to gather log events and transform it to queryable data with HIVE ddl.
This covers Java applications with log4j and non-java unix applications using rsyslog.
Apache Flume is a simple yet robust data collection and aggregation framework which allows easy declarative configuration of components to pipeline data from upstream source to backend services such as Hadoop HDFS, HBase and others.
Get to know the configuration with Hadoop installation types and also handling of the HDFS files.
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Talk soon!
In this session you will learn:
Hadoop Data Types
Hadoop MapReduce Paradigm
Map and Reduce Tasks
Map Phase
MapReduce: The Reducer
IOException & JobConf
For more information, visit: https://www.mindsmapped.com/courses/big-data-hadoop/hadoop-developer-training-a-step-by-step-tutorial/
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.
Well illustrated with definitions of Apache Hive with its architecture workflows plus with the types of data available for Apache Hive
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Well-defined introduction about working with Big Data and introduction to the Hadoop Ecosystem.
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Talk soon!
Design data pipeline to gather log events and transform it to queryable data with HIVE ddl.
This covers Java applications with log4j and non-java unix applications using rsyslog.
First slide
1) Apache Flume is a distributed and available service, in which it can collect and move large amount of streaming data from one location to another.
2) Most frequently it will deliver the log data into HDFS.
Second slide
1) Event and Client are the logical components of flume.
2) An Event is a Singular unit of data which can be transported by Flume NG from its Source to destination.
3) Typically an Event will be composed of Zero or more headers and a body. Here the headers will be used for contextual routing. This means by using the Header definition we can rout the data to the next eligible destination.
4) Client is an Event generator. It will generate the events and send it to one or more agents.
Eg: Apache webservers, which generates continuously a huge amount of log data.
Third slide
1) Flume agent is a JVM Daemon service, which holds all Flume-NG components like Sources, Channels, Sinks...etc.
2) Here the Source will send the events to channel and channel will stored it, later the channel will send the events to sink.
Fourth slide
1) Source is an active component, which receives data from different locations and places it on one or more Channels.
2) The declaration of source component in “.conf” file of agent “a1” is listed here. In this s1 means Source component, a1 means agent.
a1.sources=s1
a1.sources.s1.type=netcat (netcat is one of the Source type)
3) There are different Source types are available like Pollable (Means Auto generating like “tail –F” command and sequencing command), event driven and Netcat.
4) Even we can write our won Source type and specify that Custom class name to source type parameter.
Fifth slide
1) A channel is a bridge between Source and Sink.
2) Channel will store the Source events and send it to Sink.
3) There are three different types of Channels like memory channel which is very fast but no guarantee for data loss. And file channel which will store the events in a file system before sending it to sink. And the third one is database channel which will store the events in database.
4) Single Channel can be connected to any number of Sources and Sinks.
Sixth slide
1) A sink receives events from one channel only.
In this session you will learn:
What is Java?
Variable and Data types in Java
For more information, visit: https://www.mindsmapped.com/courses/big-data-hadoop/hadoop-developer-training-a-step-by-step-tutorial/
In this session you will learn:
HIVE Overview
Working of Hive
Hive Tables
Hive - Data Types
Complex Types
Hive Database
HiveQL - Select-Joins
Different Types of Join
Partitions
Buckets
Strict Mode in Hive
Like and Rlike in Hive
Hive UDF
For more information, visit: https://www.mindsmapped.com/courses/big-data-hadoop/hadoop-developer-training-a-step-by-step-tutorial/
In this session you will learn:
PIG
Loads in Pig Continued
Verification
Filters
Macros in Pig
For more information, visit: https://www.mindsmapped.com/courses/big-data-hadoop/hadoop-developer-training-a-step-by-step-tutorial/
Session 03 - Hadoop Installation and Basic CommandsAnandMHadoop
In this session you will learn:
Hadoop Installation and Commands
For more information, visit: https://www.mindsmapped.com/courses/big-data-hadoop/hadoop-developer-training-a-step-by-step-tutorial/
In this session you will learn:
Evolution of Yarn
Containers
Job initialization steps
Resource manager
For more information, visit: https://www.mindsmapped.com/courses/big-data-hadoop/hadoop-developer-training-a-step-by-step-tutorial/
In this session you will learn:
What is Big Data?
What is Hadoop?
Overview of Hadoop Ecosystem
Hadoop Distributed File System or HDFS
Hadoop Cluster Modes
Yarn
MapReduce
Hive
Pig
Zookeeper
Flume
Sqoop
For more information, visit: https://www.mindsmapped.com/courses/big-data-hadoop/hadoop-developer-training-a-step-by-step-tutorial/
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
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.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
3. Page 2Classification: Restricted
Apache Flume is a tool used to collect streaming data such as log files,
events from various sources.
Data which is to be collected will be produced by various sources like
applications servers, social networking sites and various others. This data
will be in the form of log files and events.
Log file − In general, a log file is a file that lists events/actions that occur in
an operating system. For example, web servers list every request made to
the server in the log files.
Processing the log files produces info:: −
Understanding the application performance and various software and
hardware failures.
The user behavior and derive better business insights.
An event is the basic unit of the data transported inside Flume.
When the rate of incoming data exceeds the rate at which data can be
written to the destination, Flume acts as a mediator between data
producers and the centralized stores and provides a steady flow of data
between them
Flume Overview
4. Page 3Classification: Restricted
Flume deploys as one or more agents, each contained within its own instance
of the Java Virtual Machine (JVM).
Agents consist of three components: sources, sinks, and channels. An agent
must have at least one of each in order to run. Sources collect incoming data as
events. Sinks write events out, and channels provide a queue to connect the
source and sink
Flume Agent
5. Page 4Classification: Restricted
Sources
Flume agents may have more than one source, but must have at least one. Sources
require a name and a type; the type then dictates additional configuration
parameters.
On consuming an event, Flume sources write the event to a channel. Importantly,
sources write to their channels as transactions. By dealing in events and
transactions, Flume agents maintain end-to-end flow reliability. Events are not
dropped inside a Flume agent unless the channel is explicitly allowed to discard
them due to a full queue.
Channels
Channels are the mechanism by which Flume agents transfer events from their
sources to their sinks. Events written to the channel by a source are not removed
from the channel until a sink removes that event in a transaction. This allows Flume
sinks to retry writes in the event of a failure in the external repository (such as
HDFS or an outgoing network connection). For example, if the network between a
Flume agent and a Hadoop cluster goes down, the channel will keep all events
queued until the sink can correctly write to the cluster and close its transactions
with the channel.
Flume Agent
6. Page 5Classification: Restricted
Sinks provide Flume agents output capability — if you need to write to a new
type storage, just write a Java class that implements the necessary classes.
Like sources, sinks correspond to a type of output: writes to HDFS or HBase,
remote procedure calls to other agents, or any number of other external
repositories. Sinks remove events from the channel in transactions and write
them to output. Transactions close when the event is successfully written,
ensuring that all events are committed to their final destination.
Sinks
7. Page 6Classification: Restricted
Follow the steps mentioned below to install and configure Flume on a linux
box. Flume agent requires hadoop configurations available on the same
node.
•Download the latest version of Flume from here.
•Change directory to /usr/local/work
Command :$cd usr/local/work
•Untar the < apache-flume-<version>-bin.tar.gz>
command :$sudo tar –xzvf apache-flume-1.5.0-bin.tar.gz
•Move to flume directory
command: sudo mv usr/local/work/apache-flume-1.5.0-bin flume
Flume Installation
8. Page 7Classification: Restricted
•Add Flume to Path in user bash profile
command :$sudo nano ~/.bashrc
export FLUME_HOME="/usr/local/work/flume"
export PATH=$PATH:$FLUME_HOME/bin
Copy the config file in Flume conf folder to change for custom agents
Command: $ cd /usr/local/work/flume/conf
Command :$ sudo cp flume-conf.properties.template flume.conf
•Command :$ sudo cp flume-env.sh.template flume-env.sh
•Open flume-env.sh Command :$ sudo nano flume-env.sh
•6.1 Configure Java
JAVA_HOME=/usr/local/work/java
Modify the flume.conf in conf directory and add required to it. Also
comment the existing properties.
Flume Installation
9. Page 8Classification: Restricted
Go to /usr/local/work/flume/conf
then open the file flume.conf using:::::::
This configuration lets a user generate events and subsequently logs
them to the console.
mishra@mishra-VirtualBox:/usr/local/work/flume/conf$ sudo nano
flume.conf
commentt all the lines and paste::::::::
anand.sources = mis
anand.sinks = his
anand.channels = c
# Describe/configure the source
anand.sources.mis.type = netcat
anand.sources.mis.bind = localhost
anand.sources.mis.port = 44444
Flume Installation
10. Page 9Classification: Restricted
# Describe the sink
anand.sinks.his.type = logger
# Use a channel which buffers events in memory
anand.channels.c.type = memory
anand.channels.c.capacity = 1000
anand.channels.c.transactionCapacity = 100
# Bind the source and sink to the channel
anand.sources.mis.channels = c
anand.sinks.his.channel = c
Flume Installation
11. Page 10Classification: Restricted
This configuration defines a single agent named anand. anand has a source that listens for
data on port 44444, a channel that buffers event data in memory, and a sink that logs event
data to the console.
mishra@mishra-VirtualBox:/usr/local/work/flume$ bin/flume-ng agent --conf conf --conf-file
conf/flume.conf --name anand -Dflume.root.logger=INFO,console or
mishra@mishra-VirtualBox:/usr/local/work/flume/conf$ flume-ng agent --conf conf --conf-file
flume.conf --name anand -Dflume.root.logger=INFO,console
now open another terminal and do the following
From a separate terminal, we can then telnet port 44444 and send Flume an event:
mishra@mishra-VirtualBox:~$ telnet localhost 44444
you will get the following on your screen:::
Trying 127.0.0.1...
Connected to localhost.
Escape character is '^]'.
Now type anything which you want as your streaming data communicating through telnet
port
like:: hello andy....how r u??? Now check on the terminal on which flume is running. You will
find same output
Flume Installation
12. Page 11Classification: Restricted
What is netcat?
netcat:: functions it can do various other things like creating socket servers to
listen for incoming connections on ports, transfer files from the terminal etc.
Netcat is a computer networking service for reading from and writing network
connections using TCP or UDP
More technically speaking, netcat can act as a socket server or client and interact
with other programs at the same time sending and receiving data through the
network.
Ncat is a feature-packed networking utility which reads and writes data across
networks from the command line
What is telnet?
A network protocol that allows a user on one computer to log into another
computer that is part of the same network. Telnet is a user command and an
underlying TCP/IP protocol for accessing remote computers. Telnet is most likely
to be used by program developers and anyone who has a need to use specific
applications or data located at a particular host computer.
What is Netcat & Telnet?
13. Page 12Classification: Restricted
IN case when you want your data in hdfs::::
open flume.conf file and paste::::::
mishra@mishra-VirtualBox:/usr/local/work/flume/conf$ sudo nano flume.conf
comment all lines with # and paste:::::
agent.sources = mis
agent.sinks = his
agent.channels = c
# Describe/configure the source
agent.sources.mis.type = netcat
agent.sources.mis.bind = localhost
agent.sources.mis.port = 44444
# Define a sink that outputs to logger.
agent.sinks.his.type = hdfs
agent.sinks.his.hdfs.path =hdfs://localhost:8020/flumedata/
agent.sinks.his.hdfs.fileType = DataStream
agent.sinks.his.hdfs.writeFormat = Text
agent.channels.c.type = memory
agent.channels.c.capacity = 1000
agent.channels.c.transactionCapacity = 100
# Bind the source and sink to the channel
agent.sources.mis.channels = c
agent.sinks.his.channel = c
Flume
14. Page 13Classification: Restricted
now run the command
mishra@mishra-VirtualBox:/usr/local/work/flume$ bin/flume-ng agent --conf
conf --conf-file conf/flume.conf --name agent -
Dflume.root.logger=INFO,console
or
mishra@mishra-VirtualBox:/usr/local/work/flume/conf$ flume-ng agent --conf
conf --conf-file flume.conf --name agent -Dflume.root.logger=INFO,console
telnet localhost 44444
write anything here
mishra@mishra-VirtualBox:~$ hadoop fs -cat
/flumedata/FlumeData.1467740902549
Flume