# STRUCT Support
### Overview
Euno provides **column-level lineage tracking for BigQuery STRUCT columns**, enabling you to trace data flow through nested and complex data structures. This enhancement allows you to understand exactly which nested fields within STRUCT columns are being used, transformed, and propagated throughout your data pipeline.
### Capabilities
#### 1. Nested Field Discovery
Euno automatically discovers and catalogs all nested fields within STRUCT columns, creating individual column resources for each field path.
**Example Table Structure:**
```sql
CREATE TABLE users (
user_id INT64,
profile STRUCT<
name STRING,
email STRING,
street STRING,
city STRING,
zip STRING
>
)
```
**What You See in Euno:**
In the Data Model screen, you'll see these columns:
* `user_id` (INT64)
* `profile` (STRUCT) - marked with `subtype: struct`
* `profile.name` (STRING)
* `profile.email` (STRING)
* `profile.street` (STRING)
* `profile.city` (STRING)
* `profile.zip` (STRING)
Each nested field appears as a separate, searchable column resource with its own URI, allowing you to track it independently.
#### 2. Column-Level Lineage
When queries reference specific fields within STRUCT columns, Euno traces lineage to the exact nested field, not just the parent STRUCT.
**Example Query:**
```sql
SELECT
user_id,
profile.name AS user_name,
profile.city AS user_city
FROM users
```
**Lineage Tracking:**
* `user_name` column traces back to `users.profile.name` (not just `users.profile`)
#### 3. Accurate Usage Metrics
Column-level usage statistics now include nested STRUCT fields, showing you:
* How many queries reference each nested field
* Usage frequency for each field path
**Example Usage Report:**
| Column | Total Queries | Distinct Users |
| ---------------- | ------------- | -------------- |
| `profile.name` | 1,247 | 23 |
| `profile.email` | 892 | 18 |
| `profile.city` | 456 | 12 |
| `profile.street` | 89 | 5 |
| `profile.zip` | 67 | 4 |
This data helps you:
* **Optimize schemas:** Identify rarely-used nested fields that could be removed
* **Understand access patterns:** See which parts of your STRUCT columns are most valuable
* **Plan migrations:** Know which fields are critical before restructuring
#### 4. Lineage Through Complex Transformations
Euno tracks nested field lineage through complex SQL operations:
**Example: Extracting and Transforming Nested Fields**
```sql
CREATE TABLE customer_summary AS
SELECT
user_id,
profile.name AS customer_name,
UPPER(profile.city) AS city_upper,
profile.zip AS postal_code
FROM users
WHERE profile.city IS NOT NULL
```
**Lineage Captured:**
* `customer_summary.customer_name` traces back to `users.profile.name`
* `customer_summary.city_upper` traces back to `users.profile.city`
* `customer_summary.postal_code` traces back to `users.profile.zip`
**Example: Aggregating Nested Fields**
```sql
CREATE TABLE city_stats AS
SELECT
profile.city,
COUNT(*) AS user_count,
COUNT(DISTINCT profile.email) AS unique_emails
FROM users
GROUP BY profile.city
```
**Lineage Captured:**
* `city_stats.city` traces back to `users.profile.city`
* `city_stats.user_count` is an aggregation with no specific source column
* `city_stats.unique_emails` traces back to `users.profile.email` with aggregation: COUNT DISTINCT
### Viewing STRUCT Columns in Euno
#### In the Data Model Screen
1. **Navigate to a table** with STRUCT columns
2. **Click on the Columns tab** in the resource sidepane
3. **Identify STRUCT columns** by the `struct` badge
4. **Expand nested fields** to see all field paths
5. **Click on any nested field** to view its details and lineage
#### Column Properties
**Root STRUCT Column:**
* **Type:** `column`
* **Subtype:** `struct`
* **Data Type:** `STRUCT<...>` (full schema definition)
* **Normalized Type:** `object`
**Nested Field:**
* **Type:** `column`
* **Name:** Full path (e.g., `profile.city`)
* **Data Type:** The field's actual type (e.g., `STRING`, `INT64`)
* **Parent Container:** The table URI
#### Lineage View
When viewing lineage for a nested field:
1. **Upstream:** Shows the source nested field (e.g., `source_table.profile.city`)
2. **Downstream:** Shows all columns and resources that depend on this nested field
3. **Usage:** Shows query count and user count for the field
### Limitations
1. **ARRAY of STRUCT:** Nested paths through UNNEST are supported, but element-level instance/index lineage is not tracked.
2. **Dynamic Field Access:** Fields accessed via dynamic SQL or UDFs may not be captured.
3. **Complex Unnesting:** Some complex UNNEST operations with multiple levels may not fully resolve.
4. **Cross-Project References:** Nested field lineage is most accurate when metadata and query history are available for all referenced projects.
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