learning/prompts/documentation-lookup/16_advanced_pipeline_lifecycle.md - beam - Git at Google

 Prompt:
 What is a pipeline development lifecycle in Apache Beam?

 Response:
 The Apache Beam pipeline development lifecycle is an iterative process that usually involves the following steps:
 - Design your pipeline.
 - Develop your pipeline code.
 - Test your pipeline.
 - Deploy your pipeline.

 During each iteration, you might need to go back and forth between the different steps to refine your pipeline code and to fix bugs.

 To design a pipeline, you need answers to the following questions:
 - Where is the data stored?
 - What does the data look like?
 - What do you want to do with your data?
 - What does your output data look like, and where should it go?

 Beam documentation has more information about [pipeline design](https://beam.apache.org/documentation/pipelines/design-your-pipeline/) and about common [pipeline patterns](https://beam.apache.org/documentation/patterns/overview/).

 An Apache Beam program expresses a data processing pipeline, from start to finish. To construct a pipeline using the classes in the Apache Beam SDKs, your program needs to perform the following steps:

 - Create a `Pipeline` object.
 - Use a `Read` or `Create` transform to create one or more `PCollection` objects for your pipeline data.
 - Apply transforms to each `PCollection`.
 - Write or otherwise output the final, transformed `PCollection` objects.
 - Run the pipeline.

 The Apache Beam documentation has more information about [developing](https://beam.apache.org/documentation/programming-guide/) and [executing](https://beam.apache.org/documentation/pipelines/create-your-pipeline/) pipelines.

 Testing pipelines is a particularly important step in developing an effective data processing solution. The indirect nature of the Beam model, in which your user code constructs a pipeline graph to be executed remotely, can make debugging failed runs difficult. For more information about pipeline testing strategies, see [Test Your Pipeline](https://beam.apache.org/documentation/pipelines/test-your-pipeline/).

 Choosing a [runner](https://beam.apache.org/documentation/#choosing-a-runner) is a crucial step in deploying your pipeline. The runner you choose determines where and how your pipeline executes. For more information about pipeline deployment, see [Container environments](https://beam.apache.org/documentation/runtime/environments/).
	Prompt:
	What is a pipeline development lifecycle in Apache Beam?

	Response:
	The Apache Beam pipeline development lifecycle is an iterative process that usually involves the following steps:
	- Design your pipeline.
	- Develop your pipeline code.
	- Test your pipeline.
	- Deploy your pipeline.

	During each iteration, you might need to go back and forth between the different steps to refine your pipeline code and to fix bugs.

	To design a pipeline, you need answers to the following questions:
	- Where is the data stored?
	- What does the data look like?
	- What do you want to do with your data?
	- What does your output data look like, and where should it go?

	Beam documentation has more information about [pipeline design](https://beam.apache.org/documentation/pipelines/design-your-pipeline/) and about common [pipeline patterns](https://beam.apache.org/documentation/patterns/overview/).

	An Apache Beam program expresses a data processing pipeline, from start to finish. To construct a pipeline using the classes in the Apache Beam SDKs, your program needs to perform the following steps:

	- Create a `Pipeline` object.
	- Use a `Read` or `Create` transform to create one or more `PCollection` objects for your pipeline data.
	- Apply transforms to each `PCollection`.
	- Write or otherwise output the final, transformed `PCollection` objects.
	- Run the pipeline.

	The Apache Beam documentation has more information about [developing](https://beam.apache.org/documentation/programming-guide/) and [executing](https://beam.apache.org/documentation/pipelines/create-your-pipeline/) pipelines.

	Testing pipelines is a particularly important step in developing an effective data processing solution. The indirect nature of the Beam model, in which your user code constructs a pipeline graph to be executed remotely, can make debugging failed runs difficult. For more information about pipeline testing strategies, see [Test Your Pipeline](https://beam.apache.org/documentation/pipelines/test-your-pipeline/).

	Choosing a [runner](https://beam.apache.org/documentation/#choosing-a-runner) is a crucial step in deploying your pipeline. The runner you choose determines where and how your pipeline executes. For more information about pipeline deployment, see [Container environments](https://beam.apache.org/documentation/runtime/environments/).