Beam Template

• Sunbeam Template
• Bear Template For Kids
• Beam Template

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Use beams tools to add load-bearing structural elements to building models.

• Structure tabStructure panel (Beam)

• About the Structural Usage of Beams
  The Structural Usage property of a beam is typically automatically assigned based on the structural elements that support the beam. However, structural usage can be changed before or after the beam is placed.
• About Placing Beams
  It is good practice to first add grids and columns before creating beams.
• Sketch a Beam
  Use the Beam tool to sketch individual instances of beams.
• Place Beams with the Grid Tool
  Use the Grid tool to select grid lines to place beams automatically between other structural elements such as columns, structural walls, and other beams.
• Sketch a Curved Beam
  Sketch curved beams in either a plan or elevation view.
• Beam Modification
  You can align, move, copy, and adjust beams using common element editing tools.
• About Beam Handles
  Beam handles are also the attachment points of the beam. Beam handles display as small filled circles that indicate where the end of the selected beam is attached to a column or wall.
• Display Moment Symbols
  Specify a beam to display moment frames or cantilever connection symbols.
• Place Multiple Framing Tags and Spot Elevations
  Place multiple beam tags, annotations, and spot elevations on selected beams or all beams in the current view and linked models.
• Upgrade Steel Beam and Brace Families
  Projects created prior to Autodesk Revit 2014 will need a manual upgrade of steel beam families to fully remove legacy parameters and their behaviors.
• Beam Instance Properties
  Modify beam instance properties to change level offsets, geometry justification, phasing data, and more.
• Beam Analysis Properties
  Modify the analytical properties of the beam to accommodate structural analysis tools and procedures.
• Beam Type Properties
  Modify beam type properties to change flange width, web thickness, identity data, and more.
• Beam Family Properties
  Modify an beam family to define specific behaviors or Identity Data that apply across all types in that family.

Cloud Dataflow templates use runtime parameters to accept values that are only available during pipeline execution. To customize the execution of a templated pipeline, you can pass these parameters to functions that run within the pipeline (such as a DoFn).

To create a template from your Apache Beam pipeline, you must modify your pipeline code to support runtime parameters:

• Use ValueProvider for all pipeline options that you want to set or use at runtime.
• Call I/O methods that accept runtime parameters wherever you want to parameterize your pipeline.
• Use DoFn objects that accept runtime parameters.

Then, create and stage your template.

Runtime parameters and the ValueProvider interface

The ValueProvider interface allows pipelines to accept runtime parameters. Apache Beam provides three types of ValueProvider objects.

Modifying your code to use runtime parameters

This section walks through how to use ValueProvider, StaticValueProvider, and NestedValueProvider.

Using ValueProvider in your pipeline options

Use ValueProvider for all pipeline options that you want to set or use at runtime.

For example, the following WordCount code snippet does not support runtime parameters. The code adds an input file option, creates a pipeline, and reads lines from the input file:

To add runtime parameter support, modify the input file option to use ValueProvider.

Java: SDK 2.x

Use ValueProvider<String> instead of String for the type of the input file option.

Python

Replace add_argument with add_value_provider_argument.

Java: SDK 1.x

Use ValueProvider<String> instead of String for the type of the input file option.

Using ValueProvider in your functions

To use runtime parameter values in your own functions, update the functions to use ValueProvider parameters.

The following example contains an integer ValueProvider option, and a simple function that adds an integer. The function depends on the ValueProvider integer. During execution, the pipeline applies MySumFn to every integer in a PCollection that contains [1, 2, 3]. If the runtime value is 10, the resulting PCollection contains [11, 12, 13].

Using StaticValueProvider

To provide a static value to your pipeline, use StaticValueProvider.

This example uses MySumFn, which is a DoFn that takes a ValueProvider<Integer>. If you know the value of the parameter ahead of time, you can use StaticValueProvider to specify your static value as a ValueProvider.

Java: SDK 2.x

This code gets the value at pipeline runtime:

Instead, you can use StaticValueProvider with a static value:

Python

This code gets the value at pipeline runtime:

Instead, you can use StaticValueProvider with a static value:

Java: SDK 1.x

This code gets the value at pipeline runtime:

Instead, you can use StaticValueProvider with a static value:

You can also use StaticValueProvider when you implement an I/O module that supports both regular parameters and runtime parameters. StaticValueProvider reduces the code duplication from implementing two similar methods.

Java: SDK 2.x

The source code for this example is from Apache Beam's TextIO.java on GitHub.

Sunbeam Template

Python

Bear Template For Kids

In this example, there is a single constructor that accepts both a string or a ValueProvider argument. If the argument is a string, it is converted to a StaticValueProvider.

Java: SDK 1.x

The source code for this example is from Apache Beam's TextIO.java on GitHub.

Using NestedValueProvider

Note: The Apache Beam SDK for Python does not support NestedValueProvider.

To compute a value from another ValueProvider object, use NestedValueProvider.

NestedValueProvider takes a ValueProvider and a SerializableFunction translator as input. When you call .get() on a NestedValueProvider, the translator creates a new value based on the ValueProvider value. This translation allows you to use a ValueProvider value to create the final value that you want:

• Example 1: The user provides a file name file.txt. The transform prepends the file path gs://directory_name/ to the file name. Calling .get() returns gs://directory_name/file.txt.
• Example 2: The user provides a substring for a BigQuery query, such as a specific date. The transform uses the substring to create the full query. Calling .get() returns the full query.

Note:NestedValueProvider accepts only one value input. You can't use a NestedValueProvider to combine two different values.

The following code uses NestedValueProvider to implement the first example: the user provides a file name, and the transform prepends the file path to the file name.

Python

The Apache Beam SDK for Python does not support NestedValueProvider.

Metadata

You can extend your templates with additional metadata so that custom parameters are validated when the template executes. If you want to create metadata for your template, you need to:

1. Create a JSON-formatted file named <template-name>_metadata using the parameters from the table below.

   Note: Do not name the file you create <template-name>_metadata.json. While the file contains JSON, it cannot end in the .json file extension.

2. Store the JSON file in Cloud Storage in the same folder as the template.

   Note: The template should be stored in <template-name> and the metadata should be stored in <template-name>_metadata.

Metadata parameters

Example metadata file

The Cloud Dataflow service uses the following metadata to validate the WordCount template's custom parameters:

You can download this metadata file from the Cloud Dataflow template directory.

Pipeline I/O and runtime parameters

Java: SDK 2.x

Some I/O connectors contain methods that accept ValueProvider objects. To determine support for a specific connector and method, see the API reference documentation for the I/O connector. Supported methods have an overload with a ValueProvider. If a method does not have an overload, the method does not support runtime parameters. The following I/O connectors have at least partial ValueProvider support:

• File-based IOs: TextIO, AvroIO, FileIO, TFRecordIO, XmlIO
• BigQueryIO*
• BigtableIO (requires SDK 2.3.0 or later)
• PubSubIO
• SpannerIO

* Note: If you want to run a batch pipelinethat reads from BigQuery, you must use.withTemplateCompatibility() on all BigQuery reads.

Python

Some I/O connectors contain methods that accept ValueProvider objects. To determine support for I/O connectors and their methods, see the API reference documentation for the connector. The following I/O connectors accept runtime parameters:

• File-based IOs: textio, avroio, tfrecordio

Java: SDK 1.x

The following table contains the complete list of methods that accept runtime parameters.

* You can only execute BigQuery batch pipeline templates one time, as the BigQuery job ID is set at template creation time.

Creating and staging templates

After you write your pipeline, you must create and stage your template file. Use the command for your SDK version.

Note: After you create and stage a template, thestaging location contains additional files that are necessary to execute yourtemplate. If you delete the staging location, template execution will fail.

Java: SDK 2.x

This Maven command creates and stages a template at the Cloud Storage location specified with --templateLocation.

• Replace YOUR_PROJECT_ID with your project ID.

• Replace YOUR_BUCKET_NAME with the name of your Cloud Storage bucket.

• Replace YOUR_TEMPLATE_NAME with the name of your template.

• Replace com.example.myclass with your Java class.

• Verify that the templateLocation path is correct.

Beam Template

Python

This Python command creates and stages a template at the Cloud Storage location specified with --template_location. Make the following changes to the command:

• Replace YOUR_PROJECT_ID with your project ID.

• Replace YOUR_BUCKET_NAME with the name of your Cloud Storage bucket.

• Replace YOUR_TEMPLATE_NAME with the name of your template.

• Replace examples.mymodule with your Python module.

• Verify that the template_location path is correct.

Java: SDK 1.x

This Maven command creates and stages a template at the Cloud Storage location specified with --dataflowJobFile.

• Replace YOUR_PROJECT_ID with your project ID.

• Replace YOUR_BUCKET_NAME with the name of your Cloud Storage bucket.

• Replace YOUR_TEMPLATE_NAME with the name of your template.

• Replace com.example.myclass with your Java class.

• Verify that the dataflowJobFile path is correct.

After you create and stage your template, your next step is to execute the template.