googleapis--mcp-toolbox
wehub-resource-sync
95 行
4.1 KiB
Markdown
95 行
4.1 KiB
Markdown
---
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title: "bigquery-analyze-contribution"
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type: docs
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weight: 1
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description: >
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A "bigquery-analyze-contribution" tool performs contribution analysis in BigQuery.
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---
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## About
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A `bigquery-analyze-contribution` tool performs contribution analysis in
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BigQuery by creating a temporary `CONTRIBUTION_ANALYSIS` model and then querying
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it with `ML.GET_INSIGHTS` to find top contributors for a given metric.
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`bigquery-analyze-contribution` takes the following parameters:
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- **input_data** (string, required): The data that contain the test and control
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data to analyze. This can be a fully qualified BigQuery table ID (e.g.,
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`my-project.my_dataset.my_table`) or a SQL query that returns the data.
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- **contribution_metric** (string, required): The name of the column that
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contains the metric to analyze. This can be SUM(metric_column_name),
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SUM(numerator_metric_column_name)/SUM(denominator_metric_column_name) or
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SUM(metric_sum_column_name)/COUNT(DISTINCT categorical_column_name) depending
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the type of metric to analyze.
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- **is_test_col** (string, required): The name of the column that identifies
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whether a row is in the test or control group. The column must contain boolean
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values.
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- **dimension_id_cols** (array of strings, optional): An array of column names
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that uniquely identify each dimension.
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- **top_k_insights_by_apriori_support** (integer, optional): The number of top
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insights to return, ranked by apriori support. Default to '30'.
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- **pruning_method** (string, optional): The method to use for pruning redundant
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insights. Can be `'NO_PRUNING'` or `'PRUNE_REDUNDANT_INSIGHTS'`. Defaults to
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`'PRUNE_REDUNDANT_INSIGHTS'`.
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The behavior of this tool is influenced by the `writeMode` setting on its
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`bigquery` source:
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- **`allowed` (default) and `blocked`:** These modes do not impose any special
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restrictions on the `bigquery-analyze-contribution` tool.
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- **`protected`:** This mode enables session-based execution. The tool will
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operate within the same BigQuery session as other tools using the same source.
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This allows the `input_data` parameter to be a query that references temporary
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resources (e.g., `TEMP` tables) created within that session.
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The tool's behavior is also influenced by the `allowedDatasets` restriction on
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the `bigquery` source:
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- **Without `allowedDatasets` restriction:** The tool can use any table or query
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for the `input_data` parameter.
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- **With `allowedDatasets` restriction:** The tool verifies that the
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`input_data` parameter only accesses tables within the allowed datasets.
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- If `input_data` is a table ID, the tool checks if the table's dataset is in
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the allowed list.
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- If `input_data` is a query, the tool performs a dry run to analyze the query
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and rejects it if it accesses any table outside the allowed list.
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## Compatible Sources
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{{< compatible-sources >}}
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## Example
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```yaml
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kind: tool
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name: contribution_analyzer
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type: bigquery-analyze-contribution
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source: my-bigquery-source
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description: Use this tool to run contribution analysis on a dataset in BigQuery.
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```
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## Reference
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| **field** | **type** | **required** | **description** |
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|-------------|:--------:|:------------:|----------------------------------------------------|
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| type | string | true | Must be "bigquery-analyze-contribution". |
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| source | string | true | Name of the source the tool should execute on. |
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| description | string | true | Description of the tool that is passed to the LLM. |
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## Advanced Usage
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### Sample Prompt
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You can prepare a sample table following
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https://cloud.google.com/bigquery/docs/get-contribution-analysis-insights.
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And use the following sample prompts to call this tool:
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- What drives the changes in sales in the table
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`bqml_tutorial.iowa_liquor_sales_sum_data`? Use the project id myproject.
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- Analyze the contribution for the `total_sales` metric in the table
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`bqml_tutorial.iowa_liquor_sales_sum_data`. The test group is identified by
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the `is_test` column. The dimensions are `store_name`, `city`, `vendor_name`,
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`category_name` and `item_description`.
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