Slide deck for the fourth data engineering lunch, presented by guest speaker Will Angel. It covered the topic of using Airflow for data engineering. Airflow is a scheduling tool for managing data pipelines.
In the session, we discussed the End-to-end working of Apache Airflow that mainly focused on "Why What and How" factors. It includes the DAG creation/implementation, Architecture, pros & cons. It also includes how the DAG is created for scheduling the Job and what all steps are required to create the DAG using python script & finally with the working demo.
Slide deck for the fourth data engineering lunch, presented by guest speaker Will Angel. It covered the topic of using Airflow for data engineering. Airflow is a scheduling tool for managing data pipelines.
In the session, we discussed the End-to-end working of Apache Airflow that mainly focused on "Why What and How" factors. It includes the DAG creation/implementation, Architecture, pros & cons. It also includes how the DAG is created for scheduling the Job and what all steps are required to create the DAG using python script & finally with the working demo.
In the session, we discussed the End-to-end working of Apache Airflow that mainly focused on "Why What and How" factors. It includes the DAG creation/implementation, Architecture, pros & cons. It also includes how the DAG is created for scheduling the Job and what all steps are required to create the DAG using python script & finally with the working demo.
Introduction to Apache Airflow, it's main concepts and features and an example of a DAG. Afterwards some lessons and best practices learned by from the 3 years I have been using Airflow to power workflows in production.
A 20 minute talk about how WePay runs airflow. Discusses usage and operations. Also covers running Airflow in Google cloud.
Video of the talk is available here:
https://wepayinc.box.com/s/hf1chwmthuet29ux2a83f5quc8o5q18k
Presentation given at Coolblue B.V. demonstrating Apache Airflow (incubating), what we learned from the underlying design principles and how an implementation of these principles reduce the amount of ETL effort. Why choose Airflow? Because it makes your engineering life easier, more people can contribute to how data flows through the organization, so that you can spend more time applying your brain to more difficult problems like Machine Learning, Deep Learning and higher level analysis.
In this video you are going to learn what is an operator in Apache Airflow. There are multiple kinds of operator such as Action Operator, Sensor Operator and Transfer Operator and it's important to know why and when to use one over another.
If you want to access to the entire course and support my work go to
https://www.udemy.com/the-complete-hands-on-course-to-master-apache-airflow/?couponCode=YOUTUBE-AIRFLOW
Thank you very much and have a good learning day :)
Orchestrating workflows Apache Airflow on GCP & AWSDerrick Qin
Working in a cloud or on-premises environment, we all somehow move data from A to B on-demand or on schedule. It is essential to have a tool that can automate recurring workflows. This can be anything from an ETL(Extract, Transform, and Load) job for a regular analytics report all the way to automatically re-training a machine learning model.
In this talk, we will introduce Apache Airflow and how it can help orchestrate your workflows. We will cover key concepts, features, and use cases of Apache Airflow, as well as how you can enjoy Apache Airflow on GCP and AWS by demo-ing a few practical workflows.
Building a Data Pipeline using Apache Airflow (on AWS / GCP)Yohei Onishi
This is the slide I presented at PyCon SG 2019. I talked about overview of Airflow and how we can use Airflow and the other data engineering services on AWS and GCP to build data pipelines.
We will introduce Airflow, an Apache Project for scheduling and workflow orchestration. We will discuss use cases, applicability and how best to use Airflow, mainly in the context of building data engineering pipelines. We have been running Airflow in production for about 2 years, we will also go over some learnings, best practices and some tools we have built around it.
Speakers: Robert Sanders, Shekhar Vemuri
Flyte is a structured programming and distributed processing platform created at Lyft that enables highly concurrent, scalable and maintainable workflows for machine learning and data processing. Welcome to the documentation hub for Flyte.
In the session, we discussed the End-to-end working of Apache Airflow that mainly focused on "Why What and How" factors. It includes the DAG creation/implementation, Architecture, pros & cons. It also includes how the DAG is created for scheduling the Job and what all steps are required to create the DAG using python script & finally with the working demo.
Introduction to Apache Airflow, it's main concepts and features and an example of a DAG. Afterwards some lessons and best practices learned by from the 3 years I have been using Airflow to power workflows in production.
A 20 minute talk about how WePay runs airflow. Discusses usage and operations. Also covers running Airflow in Google cloud.
Video of the talk is available here:
https://wepayinc.box.com/s/hf1chwmthuet29ux2a83f5quc8o5q18k
Presentation given at Coolblue B.V. demonstrating Apache Airflow (incubating), what we learned from the underlying design principles and how an implementation of these principles reduce the amount of ETL effort. Why choose Airflow? Because it makes your engineering life easier, more people can contribute to how data flows through the organization, so that you can spend more time applying your brain to more difficult problems like Machine Learning, Deep Learning and higher level analysis.
In this video you are going to learn what is an operator in Apache Airflow. There are multiple kinds of operator such as Action Operator, Sensor Operator and Transfer Operator and it's important to know why and when to use one over another.
If you want to access to the entire course and support my work go to
https://www.udemy.com/the-complete-hands-on-course-to-master-apache-airflow/?couponCode=YOUTUBE-AIRFLOW
Thank you very much and have a good learning day :)
Orchestrating workflows Apache Airflow on GCP & AWSDerrick Qin
Working in a cloud or on-premises environment, we all somehow move data from A to B on-demand or on schedule. It is essential to have a tool that can automate recurring workflows. This can be anything from an ETL(Extract, Transform, and Load) job for a regular analytics report all the way to automatically re-training a machine learning model.
In this talk, we will introduce Apache Airflow and how it can help orchestrate your workflows. We will cover key concepts, features, and use cases of Apache Airflow, as well as how you can enjoy Apache Airflow on GCP and AWS by demo-ing a few practical workflows.
Building a Data Pipeline using Apache Airflow (on AWS / GCP)Yohei Onishi
This is the slide I presented at PyCon SG 2019. I talked about overview of Airflow and how we can use Airflow and the other data engineering services on AWS and GCP to build data pipelines.
We will introduce Airflow, an Apache Project for scheduling and workflow orchestration. We will discuss use cases, applicability and how best to use Airflow, mainly in the context of building data engineering pipelines. We have been running Airflow in production for about 2 years, we will also go over some learnings, best practices and some tools we have built around it.
Speakers: Robert Sanders, Shekhar Vemuri
Flyte is a structured programming and distributed processing platform created at Lyft that enables highly concurrent, scalable and maintainable workflows for machine learning and data processing. Welcome to the documentation hub for Flyte.
Managing transactions on Ethereum with Apache AirflowMichael Ghen
Apache Airflow is a Python-based workflow management system that can be used to actively monitor and execute transactions on blockchain networks like Ethereum. This presentation is an introduction to Apache Airflow followed by a demonstration of a production deployment. Apache Airflow is an excellent tool for anyone already familiar with Python. Its ability to process jobs and handle errors makes it a good choice tool for managing activity on blockchain networks. The goal of this talk is to demonstrate how Apache Airflow can be used for environmental scanning and batch processing transactions. The demonstration will cover using Airflow and Python for monitoring and executing ERC20 token transactions on the Ethereum blockchain.
Intro to Talend Open Studio for Data IntegrationPhilip Yurchuk
An overview of Talend Open Studio for Data Integration, along with some tips learned from building production jobs and a list of resources. Feel free to contact me for more information.
It is an Comprehensive ETL Tool, Which provides, end to end ERP Solutions,Some of the Most popular ETL Tools are DSPX leader of ETL Tools, Started from 2006,Informatics,ODI,SAS (ETL STUDIO),BODI,ABNITRO.
For More Follow Below Link:
http://bit.ly/1zMzPjW
Metaflow: The ML Infrastructure at NetflixBill Liu
Metaflow was started at Netflix to answer a pressing business need: How to enable an organization of data scientists, who are not software engineers by training, build and deploy end-to-end machine learning workflows and applications independently. We wanted to provide the best possible user experience for data scientists, allowing them to focus on parts they like (modeling using their favorite off-the-shelf libraries) while providing robust built-in solutions for the foundational infrastructure: data, compute, orchestration, and versioning.
Today, the open-source Metaflow powers hundreds of business-critical ML projects at Netflix and other companies from bioinformatics to real estate.
In this talk, you will learn about:
- What to expect from a modern ML infrastructure stack.
- Using Metaflow to boost the productivity of your data science organization, based on lessons learned from Netflix.
- Deployment strategies for a full stack of ML infrastructure that plays nicely with your existing systems and policies.
https://www.aicamp.ai/event/eventdetails/W2021080510
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Online aptitude test management system project report.pdfKamal Acharya
The purpose of on-line aptitude test system is to take online test in an efficient manner and no time wasting for checking the paper. The main objective of on-line aptitude test system is to efficiently evaluate the candidate thoroughly through a fully automated system that not only saves lot of time but also gives fast results. For students they give papers according to their convenience and time and there is no need of using extra thing like paper, pen etc. This can be used in educational institutions as well as in corporate world. Can be used anywhere any time as it is a web based application (user Location doesn’t matter). No restriction that examiner has to be present when the candidate takes the test.
Every time when lecturers/professors need to conduct examinations they have to sit down think about the questions and then create a whole new set of questions for each and every exam. In some cases the professor may want to give an open book online exam that is the student can take the exam any time anywhere, but the student might have to answer the questions in a limited time period. The professor may want to change the sequence of questions for every student. The problem that a student has is whenever a date for the exam is declared the student has to take it and there is no way he can take it at some other time. This project will create an interface for the examiner to create and store questions in a repository. It will also create an interface for the student to take examinations at his convenience and the questions and/or exams may be timed. Thereby creating an application which can be used by examiners and examinee’s simultaneously.
Examination System is very useful for Teachers/Professors. As in the teaching profession, you are responsible for writing question papers. In the conventional method, you write the question paper on paper, keep question papers separate from answers and all this information you have to keep in a locker to avoid unauthorized access. Using the Examination System you can create a question paper and everything will be written to a single exam file in encrypted format. You can set the General and Administrator password to avoid unauthorized access to your question paper. Every time you start the examination, the program shuffles all the questions and selects them randomly from the database, which reduces the chances of memorizing the questions.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
2. What is Airflow?
It is a tool to BUILD, SCHEDULE and MONITOR
data pipelines
Set of data processing elements connected in series.
The output of one element is the input of the next one.
4. Building blocks
of Airflow
Operator
(Worker)
Knows how to perform a task
and has the tools to do it.
Example:
Python Operator
Postgres Operator
Bash Operator
Email Operator
DAG
(Protocol /
Instructions)
Describes the
order of tasks and
what to do if task is failing.
Example:
Run Task A, when it is finished, run
Task B. If one of the tasks failed, stop
the whole process and send me a
notification.
Task
(Specific job)
Job that is done by an
Operator.
Example:
- Load data from some API using
Python Operator
- Write data to the database using
MySQL Operator
Hooks
Interfaces to the external
platforms and databases.
Implements common interface
(all hooks look very similar) and
use Connections
Example:
S3 Hook
Slack Hook
HDFS Hook
Connection
Credentials to the external
systems that can be securely
stored in the Airflow.
Example:
Postgres Connection = Connection
string to the Postgres database
AWS Connection = AWS access
keys
Variables
Like environment
variables.
Can store arbitrary
information and be used in
the Tasks
Examples:
Stack Overflow base URL
Gmail Client ID and Secret
XComs
Let’s Tasks exchange
small messages.
5.
6. I
Create
Questions
table
II
Store data
from Stack
Overflow
III
Write filtered
questions to
S3
IV
Render HTML
template
V
Send me an
email
Postgres
Connection
Postgres
Connection
Postgres
Connection
S3
Connection
Python Operator
Python Operator
Python Operator
Postgres Hook
S3
Connection
S3
Hook
Postgres Hook S3
HookPostgres
Operator
XCom
XCom
Variables
Variables
Email
Operator
7.
8. What have we learned?
- What is Apache Airflow
- What is a data pipeline
- Main Airflow concepts (DAG, Task, Operator, Connection, etc.)
- First pipeline