# Groups and Aggregates

Grouping and aggregation for analytics and reporting.

## Overview

Grouping and aggregation enable SQL-like `GROUP BY` operations with aggregate functions (COUNT, SUM, AVG, MIN, MAX) for analytics and reporting queries.

**Common Use Cases:**
- Sales totals by category
- Order counts by customer
- Average rating by product
- Revenue by month
- Inventory by warehouse

## Aggregate Functions

### Count

```json
{
  "aggregates": [
    {
      "path": "*",
      "type": "Count"
    }
  ]
}
```

**SQL Equivalent:** `SELECT COUNT(*)`

**Response:**
```json
{
  "aggregates": [
    {
      "path": "*",
      "type": "Count",
      "value": 150
    }
  ]
}
```

### Sum

```json
{
  "aggregates": [
    {
      "path": "totalAmount",
      "type": "Sum"
    }
  ]
}
```

**SQL Equivalent:** `SELECT SUM(totalAmount)`

**Response:**
```json
{
  "aggregates": [
    {
      "path": "totalAmount",
      "type": "Sum",
      "value": 125430.50
    }
  ]
}
```

### Average

```json
{
  "aggregates": [
    {
      "path": "price",
      "type": "Average"
    }
  ]
}
```

**SQL Equivalent:** `SELECT AVG(price)`

### Min

```json
{
  "aggregates": [
    {
      "path": "price",
      "type": "Min"
    }
  ]
}
```

**SQL Equivalent:** `SELECT MIN(price)`

### Max

```json
{
  "aggregates": [
    {
      "path": "price",
      "type": "Max"
    }
  ]
}
```

**SQL Equivalent:** `SELECT MAX(price)`

## Multiple Aggregates

```json
{
  "aggregates": [
    {
      "path": "*",
      "type": "Count"
    },
    {
      "path": "totalAmount",
      "type": "Sum"
    },
    {
      "path": "totalAmount",
      "type": "Average"
    },
    {
      "path": "totalAmount",
      "type": "Min"
    },
    {
      "path": "totalAmount",
      "type": "Max"
    }
  ]
}
```

**SQL Equivalent:**
```sql
SELECT COUNT(*),
       SUM(totalAmount),
       AVG(totalAmount),
       MIN(totalAmount),
       MAX(totalAmount)
```

**Response:**
```json
{
  "aggregates": [
    { "path": "*", "type": "Count", "value": 450 },
    { "path": "totalAmount", "type": "Sum", "value": 547820.75 },
    { "path": "totalAmount", "type": "Average", "value": 1217.38 },
    { "path": "totalAmount", "type": "Min", "value": 12.50 },
    { "path": "totalAmount", "type": "Max", "value": 9999.99 }
  ]
}
```

## Grouping

### Single Group

```json
{
  "groups": [
    {
      "path": "category"
    }
  ],
  "aggregates": [
    {
      "path": "*",
      "type": "Count"
    }
  ]
}
```

**SQL Equivalent:**
```sql
SELECT category, COUNT(*)
FROM products
GROUP BY category
```

**Response:**
```json
{
  "groupedData": [
    {
      "key": { "category": "Electronics" },
      "count": 125,
      "aggregates": [
        { "path": "*", "type": "Count", "value": 125 }
      ]
    },
    {
      "key": { "category": "Books" },
      "count": 200,
      "aggregates": [
        { "path": "*", "type": "Count", "value": 200 }
      ]
    },
    {
      "key": { "category": "Toys" },
      "count": 75,
      "aggregates": [
        { "path": "*", "type": "Count", "value": 75 }
      ]
    }
  ]
}
```

### Multiple Groups

```json
{
  "groups": [
    {
      "path": "category"
    },
    {
      "path": "status"
    }
  ],
  "aggregates": [
    {
      "path": "*",
      "type": "Count"
    }
  ]
}
```

**SQL Equivalent:**
```sql
SELECT category, status, COUNT(*)
FROM orders
GROUP BY category, status
```

**Response:**
```json
{
  "groupedData": [
    {
      "key": { "category": "Electronics", "status": "Pending" },
      "count": 25,
      "aggregates": [{ "path": "*", "type": "Count", "value": 25 }]
    },
    {
      "key": { "category": "Electronics", "status": "Completed" },
      "count": 100,
      "aggregates": [{ "path": "*", "type": "Count", "value": 100 }]
    },
    {
      "key": { "category": "Books", "status": "Pending" },
      "count": 40,
      "aggregates": [{ "path": "*", "type": "Count", "value": 40 }]
    }
  ]
}
```

## Filtering with Grouping

### Filter Before Grouping (WHERE)

```json
{
  "filters": [
    {
      "path": "orderDate",
      "operator": "GreaterThanOrEqual",
      "value": "2024-01-01T00:00:00Z"
    }
  ],
  "groups": [
    {
      "path": "category"
    }
  ],
  "aggregates": [
    {
      "path": "totalAmount",
      "type": "Sum"
    }
  ]
}
```

**SQL Equivalent:**
```sql
SELECT category, SUM(totalAmount)
FROM orders
WHERE orderDate >= '2024-01-01'
GROUP BY category
```

## Common Scenarios

### Scenario 1: Sales by Category

```json
{
  "groups": [
    {
      "path": "category"
    }
  ],
  "aggregates": [
    {
      "path": "*",
      "type": "Count"
    },
    {
      "path": "totalAmount",
      "type": "Sum"
    },
    {
      "path": "totalAmount",
      "type": "Average"
    }
  ]
}
```

**Response:**
```json
{
  "groupedData": [
    {
      "key": { "category": "Electronics" },
      "count": 150,
      "aggregates": [
        { "path": "*", "type": "Count", "value": 150 },
        { "path": "totalAmount", "type": "Sum", "value": 247350.00 },
        { "path": "totalAmount", "type": "Average", "value": 1649.00 }
      ]
    }
  ]
}
```

### Scenario 2: Orders by Customer

```json
{
  "groups": [
    {
      "path": "customerId"
    }
  ],
  "aggregates": [
    {
      "path": "*",
      "type": "Count"
    },
    {
      "path": "totalAmount",
      "type": "Sum"
    }
  ],
  "sorts": [
    {
      "path": "totalAmount",
      "descending": true
    }
  ]
}
```

### Scenario 3: Monthly Revenue

```json
{
  "filters": [
    {
      "path": "orderDate",
      "operator": "GreaterThanOrEqual",
      "value": "2024-01-01T00:00:00Z"
    }
  ],
  "groups": [
    {
      "path": "month"
    }
  ],
  "aggregates": [
    {
      "path": "totalAmount",
      "type": "Sum"
    },
    {
      "path": "*",
      "type": "Count"
    }
  ]
}
```

### Scenario 4: Product Ratings

```json
{
  "filters": [
    {
      "path": "rating",
      "operator": "GreaterThan",
      "value": 0
    }
  ],
  "groups": [
    {
      "path": "productId"
    }
  ],
  "aggregates": [
    {
      "path": "rating",
      "type": "Average"
    },
    {
      "path": "*",
      "type": "Count"
    }
  ]
}
```

### Scenario 5: Inventory by Warehouse

```json
{
  "groups": [
    {
      "path": "warehouseId"
    },
    {
      "path": "category"
    }
  ],
  "aggregates": [
    {
      "path": "quantity",
      "type": "Sum"
    }
  ]
}
```

## Advanced Examples

### Top Customers by Revenue

```json
{
  "groups": [
    {
      "path": "customerId"
    }
  ],
  "aggregates": [
    {
      "path": "totalAmount",
      "type": "Sum"
    },
    {
      "path": "*",
      "type": "Count"
    }
  ],
  "sorts": [
    {
      "path": "totalAmount",
      "descending": true
    }
  ],
  "page": 1,
  "pageSize": 10
}
```

### Sales Summary by Region and Category

```json
{
  "filters": [
    {
      "path": "orderDate",
      "operator": "GreaterThanOrEqual",
      "value": "2024-01-01T00:00:00Z"
    }
  ],
  "groups": [
    {
      "path": "region"
    },
    {
      "path": "category"
    }
  ],
  "aggregates": [
    {
      "path": "*",
      "type": "Count"
    },
    {
      "path": "totalAmount",
      "type": "Sum"
    },
    {
      "path": "totalAmount",
      "type": "Average"
    }
  ],
  "sorts": [
    {
      "path": "region",
      "descending": false
    },
    {
      "path": "totalAmount",
      "descending": true
    }
  ]
}
```

## Preparing Data for Grouping

### Add Computed Properties

For grouping by month, year, etc., add computed properties to your DTO:

```csharp
public class Order
{
    public int Id { get; set; }
    public DateTime OrderDate { get; set; }
    public decimal TotalAmount { get; set; }
}

public record OrderDto
{
    public int Id { get; init; }
    public DateTime OrderDate { get; init; }
    public decimal TotalAmount { get; init; }

    // Computed properties for grouping
    public int Year => OrderDate.Year;
    public int Month => OrderDate.Month;
    public string YearMonth => $"{OrderDate.Year}-{OrderDate.Month:D2}";
}
```

**Group by Month:**

```json
{
  "groups": [
    {
      "path": "yearMonth"
    }
  ],
  "aggregates": [
    {
      "path": "totalAmount",
      "type": "Sum"
    }
  ]
}
```

## Client-Side Processing

### TypeScript

```typescript
interface GroupedResult<T> {
  groupedData: Array<{
    key: Record<string, any>;
    count: number;
    aggregates: Array<{
      path: string;
      type: string;
      value: number;
    }>;
  }>;
}

async function getSalesByCategory(): Promise<GroupedResult<OrderDto>> {
  const request = {
    groups: [{ path: "category" }],
    aggregates: [
      { path: "*", type: "Count" },
      { path: "totalAmount", type: "Sum" }
    ]
  };

  const response = await fetch('/api/query/orderDynamicQuery', {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify(request)
  });

  return await response.json();
}

// Process results
const result = await getSalesByCategory();
result.groupedData.forEach(group => {
  const category = group.key.category;
  const count = group.aggregates.find(a => a.type === 'Count')?.value;
  const total = group.aggregates.find(a => a.type === 'Sum')?.value;

  console.log(`${category}: ${count} orders, $${total} total`);
});
```

### C# HttpClient

```csharp
public class OrderAnalyticsClient
{
    private readonly HttpClient _httpClient;

    public async Task<GroupedResult<OrderDto>> GetSalesByCategoryAsync()
    {
        var request = new
        {
            groups = new[] { new { path = "category" } },
            aggregates = new[]
            {
                new { path = "*", type = "Count" },
                new { path = "totalAmount", type = "Sum" }
            }
        };

        var response = await _httpClient.PostAsJsonAsync(
            "/api/query/orderDynamicQuery",
            request);

        response.EnsureSuccessStatusCode();

        return await response.Content.ReadFromJsonAsync<GroupedResult<OrderDto>>();
    }
}

public class GroupedResult<T>
{
    public List<GroupedItem> GroupedData { get; set; } = new();
}

public class GroupedItem
{
    public Dictionary<string, object> Key { get; set; } = new();
    public int Count { get; set; }
    public List<AggregateResult> Aggregates { get; set; } = new();
}

public class AggregateResult
{
    public string Path { get; set; } = string.Empty;
    public string Type { get; set; } = string.Empty;
    public decimal Value { get; set; }
}
```

## Performance Considerations

### Add Indexes for Grouped Columns

```csharp
protected override void OnModelCreating(ModelBuilder modelBuilder)
{
    modelBuilder.Entity<Order>(entity =>
    {
        // Index columns used in GROUP BY
        entity.HasIndex(e => e.Category);
        entity.HasIndex(e => e.CustomerId);
        entity.HasIndex(e => e.Status);

        // Composite index for common groupings
        entity.HasIndex(e => new { e.Category, e.Status });
    });
}
```

### Filter Before Grouping

Always apply filters before grouping to reduce the dataset:

```json
{
  "filters": [
    {
      "path": "orderDate",
      "operator": "GreaterThanOrEqual",
      "value": "2024-01-01T00:00:00Z"
    }
  ],
  "groups": [{ "path": "category" }],
  "aggregates": [{ "path": "totalAmount", "type": "Sum" }]
}
```

## Best Practices

### ✅ DO

- Filter data before grouping to reduce dataset
- Add indexes on grouped columns
- Use pagination with grouped results
- Group by indexed columns when possible
- Use multiple aggregates to get comprehensive statistics
- Sort grouped results for better presentation

### ❌ DON'T

- Don't group by high-cardinality columns (like IDs) without pagination
- Don't group without aggregates (just use distinct filtering)
- Don't skip filtering when working with large datasets
- Don't group by computed columns that can't use indexes

## See Also

- [Dynamic Queries Overview](README.md)
- [Getting Started](getting-started.md)
- [Filters and Sorts](filters-and-sorts.md)
- [Queryable Providers](queryable-providers.md)