dentalzuloo.blogg.se - Data apache airflow series insight

Two things should happen immediately, signalling that it worked: ' 172.32.7.73 /rest/v1/group/name/ Matillion /project/name/ Demo /vĮrsion/name/ default /job/name/ TheMETLJob /run?environmentName= Demo ' It’s helpful if you have cURL, because then you can copy and paste parts of the command, like this: Once you have all of those pieces of information, it’s a good idea to run a quick test to make sure the REST API call is working. If you have Internal Users, they need a tick in the API column like this: The key thing is that the user must be authorized to use the API. This is governed by your choice of User Configuration, which you can do in several ways. You will need to authenticate into the Matillion REST API. To do that, you would simply need to create a new Orchestration Job that runs your Transformation Job or Shared Job.) (Note that you can not directly launch a Transformation Job or a Shared Job using the Matillion ETL REST API. The Job name is simply the name of the Orchestration Job that you want to launch. In this case, the Environment name is Demo, coincidentally the same as the Project name.Īlternatively you can find all your Environment names in the panel at the bottom left of the web user interface. The first is by opening the Job you want to run, and context clicking the background canvas: You can find the Environment name in a couple of different ways. The Version name also appears in the left sidebar. In this case the Group name is Matillion, the Project name is Demo and the Version name is default. In the screenshot below, I’ve pixelated the address of my Matillion ETL instance, but yours will be the IP address or hostname that appears in your browser address bar.Īfter logging in to Matillion ETL, you can find the Group, Project, and Version names from your web browser like this: Login credentials of a user who has API access to Matillion.The address of your Matillion ETL instance.To launch a Matillion Job using the API, you need several pieces of information: The API provides the extensibility that Apache Airflow can use to launch jobs.

Matillion ETL has a large REST API, which is documented here. In these cases, you can actually launch a Matillion Job from Apache Airflow, using only Airflow’s core operators.

You have a cloud data platform, such as Snowflake or Databricks, and wish to take advantage of its scalability for data processing, along with Matillion ETL’s speed and simplicity in terms of job design and maintenance.

Perhaps you are using a SparkSubmit task somewhere

You are processing significant amounts of data – that is, more than XComs is designed to handle.

You have some Apache Airflow logic already, especially if it uses an event driven pattern such as a FileSensor, a SqlSensor or an ExternalTaskSensor.

There may be use cases when you’ll want to use the two together.

However, unlike Airflow, Matillion ETL is also specifically designed to perform data transformation and integration.

When to use Matillion ETL and Apache Airflowīoth Matillion ETL and Apache Airflow have job-scheduling and orchestration capabilities. It’s great for programmatically managing pipelines using Python. Take Apache Airflow.Īpache Airflow is an open source workflow management platform. That means it can integrate with some great open source tools which offer complementary features. One of the best things about Matillion ETL is its flexibility and extensibility. It’s a complete, cloud-native ELT solution. Matillion ETL is a cloud platform that helps you to extract, migrate and integrate your data into your chosen cloud data platform (for example, Snowflake or Databricks), in order to gain business insights.