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Add information about the Merlin DAG
Define the important terms of the DAG.
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docs/source/about-dag.md

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# About the Merlin Directed Acyclic Graph
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Merlin uses a directed acyclic graph (DAG) to represent operations on data such as filtering or bucketing and to represent operations in a recommender system such as creating an ensemble or filtering candidate items during inference.
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Understanding the Merlin DAG is helpful if you want to develop your own operator (Op) or building a recommender system with Merlin.
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## DAG Terminology
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node
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: A node in the DAG is a group of columns and at least one _operator_.
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The columns are specified with a _column selector_.
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column selector
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: A column selector specifies the columns to select from a dataset using column names or _tags_.
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operator
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: An operator performs a transformation on data and return a new _node_.
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The data is identified by the _column selector_.
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Some simple operators like `+` and `-` add or remove columns.
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More complex operations are applied by shifting the operators onto the column selector with the `>>` notation.
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schema
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: A Merlin schema is metadata that describes the columns in a dataset.
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Each column has its own schema that identifies the column name and can specify _tags_ and properties.
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tag
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: A Merlin tag categorizes information about a column.
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Adding a tag to a column enables you to select columns for operations by tag rather than name.
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For example, you can add the `USER_ID` and `ITEM_ID` tags to columns.
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Modeling and inference operations can use that information to act accordingly on the dataset.

docs/source/toc.yaml

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title: Deploy the HugeCTR Model with Triton
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- file: examples/scaling-criteo/04-Triton-Inference-with-Merlin-Models-TensorFlow.ipynb
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title: Deploy the TensorFlow Model with Triton
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- file: about-dag.md
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title: Merlin DAG
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- file: containers.rst
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- file: support_matrix/index.rst

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