Tia  Gottlieb

Tia Gottlieb

1597723740

Airflow State 101: An Overview Apache Airflow State

In Airflow, to describe the status of a DAG or a Task that is waiting to execute the next steps, we have defined State to share that information on the progress of the pipeline. Without the State, the execution of any DAG or task becomes a black box, and you might need to create additional external flag or resources to check status to help determine if a job finished or failed. Fortunately, Airflow provides the mechanism of State and stores each of the last recorded states in its backend DB. Not only this way is easy to watch the status of any job in Airflow UI or DB, but it’s also a persistent layer to help rerun or backfill while confronting failure.

In this article, we are going to discuss the fundamental of what is the Airflow State, what types are those states, how to use the Airflow State to test, and debug. There could be external service, and Airflow might track those states as well, but those states are out of scope for our discussion.

What does the State do in Airflow?

A good example of states in real life is like the traffic light. You’d have three states: RED, YELLOW, and GREEN. The RED light forbids any traffic from proceeding, whereas GREEN light allows traffic to proceed.

The most basic usage of the Airflow state is to designate the current status and assign the Airflow scheduler to decide future actions. Although there are more states in Airflow, similar to the traffic light, there are some common characteristics.

  • No Dual States. In Airflow, the State is a single value. Dual states are not permitted. In this way, a State with both “Failed” and “UP_FOR_RETRY” doesn’t make too much sense here.
  • The State is static, or a snapshot at a given moment. Airflow saved the State in its backend DB, and the updating of the State is not a continuous process. Due to the Airflow scheduler heartbeat interval, you could confront rare cases where the State in the DB is lag updating, and the scheduler goes down.
  • The State has a defined lifecycle. There is a detailed lifecycle diagram in the Airflow repository. The State has to follow the flow of the lifecycle, and the State usually cannot go backward except for retry cases.

#airflow #machine-learning #programming #tech #data-science #deep learning

What is GEEK

Buddha Community

Airflow State 101: An Overview Apache Airflow State
Gerhard  Brink

Gerhard Brink

1624099260

Apache Airflow - A Workflow Manager

As the industry is becoming more data driven, we need to look for a couple of solutions that would be able to process a large amount of data that is required. A workflow management system provides an infrastructure for the set-up, performance and monitoring of a defined sequence of tasks, arranged as a workflow application. Workflow management has become such a common need that most companies have multiple ways of creating and scheduling jobs internally. Apache Airflow is a framework for processing data in a data pipeline. Although Airflow is not a data streaming solution, it deals with the data that is quite stable or slowly changing. It acts as an orchestrator by providing a solution to keep the processes coordinated in a distributed system. Airflow is an initiative of Airbnb. It is written in Python.

Airflow makes it easy for a user to author workflows using python scripts. A Directed Acyclic Graph (DAG) of tasks defines a workflow in Apache Airflow. It contains a set of tasks which executes along with their dependencies.

For example, to build a sales dashboard for your store, you need to perform the following tasks:

  1. Fetch the sales records information
  2. Clean the data / Sort the data according to the profit margins
  3. Push the data to the dashboard

The dependencies of the task mentioned above is:

These tasks are performed in a specific order. For example, Task 2 (cleaning the data) won’t start if we haven’t already completed Task1 (Fetching the data).

Scheduling of tasks

Apache Airflow allows us to define a schedule interval for each DAG, which determines exactly when your pipeline is run by Airflow. ​This way, you can tell Airflow to execute your DAG

@hourly Every Hour 0 * * * *

@daily Every Day 0 0 * * *

@weekly Every Week 0 0 * * 0

@none None

@once Once

and so on, or even use more complicated schedule intervals based on Cron-like expressions.

#apache airflow #big data and fast data #devops #airflow #airflow-setup #apache #data-pipelines

Tia  Gottlieb

Tia Gottlieb

1597723740

Airflow State 101: An Overview Apache Airflow State

In Airflow, to describe the status of a DAG or a Task that is waiting to execute the next steps, we have defined State to share that information on the progress of the pipeline. Without the State, the execution of any DAG or task becomes a black box, and you might need to create additional external flag or resources to check status to help determine if a job finished or failed. Fortunately, Airflow provides the mechanism of State and stores each of the last recorded states in its backend DB. Not only this way is easy to watch the status of any job in Airflow UI or DB, but it’s also a persistent layer to help rerun or backfill while confronting failure.

In this article, we are going to discuss the fundamental of what is the Airflow State, what types are those states, how to use the Airflow State to test, and debug. There could be external service, and Airflow might track those states as well, but those states are out of scope for our discussion.

What does the State do in Airflow?

A good example of states in real life is like the traffic light. You’d have three states: RED, YELLOW, and GREEN. The RED light forbids any traffic from proceeding, whereas GREEN light allows traffic to proceed.

The most basic usage of the Airflow state is to designate the current status and assign the Airflow scheduler to decide future actions. Although there are more states in Airflow, similar to the traffic light, there are some common characteristics.

  • No Dual States. In Airflow, the State is a single value. Dual states are not permitted. In this way, a State with both “Failed” and “UP_FOR_RETRY” doesn’t make too much sense here.
  • The State is static, or a snapshot at a given moment. Airflow saved the State in its backend DB, and the updating of the State is not a continuous process. Due to the Airflow scheduler heartbeat interval, you could confront rare cases where the State in the DB is lag updating, and the scheduler goes down.
  • The State has a defined lifecycle. There is a detailed lifecycle diagram in the Airflow repository. The State has to follow the flow of the lifecycle, and the State usually cannot go backward except for retry cases.

#airflow #machine-learning #programming #tech #data-science #deep learning

Micheal  Block

Micheal Block

1607673670

Introduction to Airflow in Python

What is Work Flow

A set of steps to accomplish a given Data Engineering task. These can include any given task, such as downloading a file, copying data, filtering information, writing to a database, and so forth.

A workflow is of varying levels of complexity. Some workflows may only have 2 or 3 steps, while others consist of hundreds of components.

What is Airflow?

Airflow is a platform to program workflows (general), including the creation, scheduling, and monitoring of workflows. Airflow implements workflows as DAGs, or Directed Acyclic Graphs.

Airflow can be accessed and controlled via code, via the command-line, or via a built-in web interface.

https://airflow.apache.org/docs/stable/

Data Engineering workflows can be managed by Spotify’s Luigi, Microsoft’s SSIS, or even just Bash scripting.

#big-data #airflow #apache-spark #apache-airflow #python

I am Developer

1597487472

Country State City Dropdown list in PHP MySQL PHP

Here, i will show you how to populate country state city in dropdown list in php mysql using ajax.

Country State City Dropdown List in PHP using Ajax

You can use the below given steps to retrieve and display country, state and city in dropdown list in PHP MySQL database using jQuery ajax onchange:

  • Step 1: Create Country State City Table
  • Step 2: Insert Data Into Country State City Table
  • Step 3: Create DB Connection PHP File
  • Step 4: Create Html Form For Display Country, State and City Dropdown
  • Step 5: Get States by Selected Country from MySQL Database in Dropdown List using PHP script
  • Step 6: Get Cities by Selected State from MySQL Database in DropDown List using PHP script

https://www.tutsmake.com/country-state-city-database-in-mysql-php-ajax/

#country state city drop down list in php mysql #country state city database in mysql php #country state city drop down list using ajax in php #country state city drop down list using ajax in php demo #country state city drop down list using ajax php example #country state city drop down list in php mysql ajax

Dedric  Reinger

Dedric Reinger

1596984540

Apache Airflow And The Platform

History

Airflow was born out of Airbnb’s problem of dealing with large amounts of data that was being used in a variety of jobs. To speed up the end-to-end process, Airflow was created to quickly author, iterate on, and monitor batch data pipelines. Airflow later joined Apache.

The Platform

Apache Airflow is a platform for programmatically authoring, scheduling, and monitoring workflows. It is completely open-source with wide community support.

Airflow as an ETL Tool

It is written in Python so we are able to interact with any third party Python API to build the workflow. It is based on an ETL flow-extract, transform, load but at the same time believing that ETL steps are best expressed as code. As a result, Airflow provides much more customisable features compared to other ETL tools, which are mostly user-interface heavy.

Apache Airflow is suited to tasks ranging from pinging specific API endpoints to data transformation to monitoring.

Directed Acyclic Graph

Image for post

#python #workflow #graph #airflow #apache-airflow