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Tag Archive for pysparkdatabricksazure-databricks

Share cluster params between jobs

I have a workflow WF1 in which I trigger another workflow WF2 in the task T2. Here is the thing. I know I can use os.environ.copy() output as a parameter in the task T2 and os.environ.update() inside WF2. But imagine any task of WF2 fails. When I repai & run the WF2, it will not have WF1 environ parameters. So my question, is there any other way to copy env parameters from WF1 to WF2 that supports repair runs & tasks without losing all the variables?

Share cluster params between jobs

I have a workflow WF1 in which I trigger another workflow WF2 in the task T2. Here is the thing. I know I can use os.environ.copy() output as a parameter in the task T2 and os.environ.update() inside WF2. But imagine any task of WF2 fails. When I repai & run the WF2, it will not have WF1 environ parameters. So my question, is there any other way to copy env parameters from WF1 to WF2 that supports repair runs & tasks without losing all the variables?

Share cluster params between jobs

I have a workflow WF1 in which I trigger another workflow WF2 in the task T2. Here is the thing. I know I can use os.environ.copy() output as a parameter in the task T2 and os.environ.update() inside WF2. But imagine any task of WF2 fails. When I repai & run the WF2, it will not have WF1 environ parameters. So my question, is there any other way to copy env parameters from WF1 to WF2 that supports repair runs & tasks without losing all the variables?

Share cluster params between jobs

I have a workflow WF1 in which I trigger another workflow WF2 in the task T2. Here is the thing. I know I can use os.environ.copy() output as a parameter in the task T2 and os.environ.update() inside WF2. But imagine any task of WF2 fails. When I repai & run the WF2, it will not have WF1 environ parameters. So my question, is there any other way to copy env parameters from WF1 to WF2 that supports repair runs & tasks without losing all the variables?

Share cluster params between jobs

I have a workflow WF1 in which I trigger another workflow WF2 in the task T2. Here is the thing. I know I can use os.environ.copy() output as a parameter in the task T2 and os.environ.update() inside WF2. But imagine any task of WF2 fails. When I repai & run the WF2, it will not have WF1 environ parameters. So my question, is there any other way to copy env parameters from WF1 to WF2 that supports repair runs & tasks without losing all the variables?

Share cluster params between jobs

I have a workflow WF1 in which I trigger another workflow WF2 in the task T2. Here is the thing. I know I can use os.environ.copy() output as a parameter in the task T2 and os.environ.update() inside WF2. But imagine any task of WF2 fails. When I repai & run the WF2, it will not have WF1 environ parameters. So my question, is there any other way to copy env parameters from WF1 to WF2 that supports repair runs & tasks without losing all the variables?

Share cluster params between jobs

I have a workflow WF1 in which I trigger another workflow WF2 in the task T2. Here is the thing. I know I can use os.environ.copy() output as a parameter in the task T2 and os.environ.update() inside WF2. But imagine any task of WF2 fails. When I repai & run the WF2, it will not have WF1 environ parameters. So my question, is there any other way to copy env parameters from WF1 to WF2 that supports repair runs & tasks without losing all the variables?

De-duplicate data from Autoloader in Databricks

I want to read in files using the Databricks Autoloader. I want to drop_duplicates and take the newer value, since it is possible that values can appear in newer files and even be updated.