Validators process transactions and receive fees from users (supply-side fees).

Mina is a smart contract platform for decentralized applications (a blockchain). Mina was founded by Evan Shapiro & Izaak Meckler and launched in 2017.

Mina’s investors include Pantera Capital, FTX Ventures, Circle Ventures, etc.

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Mina Protocol

# Mina Protocol Active addresses (weekly) Methodology

## 1. Overview

Weekly active addresses measures the number of unique addresses that sent at least one transaction on the Mina blockchain within a rolling 7-day window. This metric provides insight into network engagement and user activity levels over time. The calculation uses HyperLogLog sketches to efficiently count distinct addresses across sliding weekly windows, ensuring accurate counting even with large address volumes.

## 2. Data sources

- **Mina blockchain transactions**: Raw transaction data from the Mina blockchain including transaction metadata, timestamps, and sender addresses
- **Transaction records**: Complete transaction history with `block_timestamp`, `transaction_hash`, and `sender` fields

## 3. Step-by-step calculation

### Component A: Daily active user extraction
- **Purpose**: Identifies unique sender addresses active each day on the Mina blockchain
- **Logic**: From raw Mina transaction data, extracts the `sender` field from each transaction and groups by day using `block_timestamp` truncated to day boundaries. Each unique sender address on a given day becomes a daily active user. All users are classified with user type 'Transaction sender' since the calculation focuses on addresses that initiate transactions
- **Key fields**: `block_timestamp` for temporal grouping, `sender` for user identification, `user_address` as the final user identifier

### Component B: HyperLogLog sketch creation
- **Purpose**: Creates efficient data structures for counting distinct addresses across time windows
- **Logic**: For each day's set of active user addresses, creates HyperLogLog (HLL) sketches using precision parameter 15. These sketches enable memory-efficient approximate counting of distinct addresses, which is essential for handling large volumes of unique addresses without excessive memory usage
- **Key fields**: `hll` sketch containing the compressed representation of daily unique addresses

### Component C: Rolling window construction
- **Purpose**: Builds 7-day sliding windows to capture weekly active address patterns
- **Logic**: Uses a datespine to ensure complete date coverage from the earliest transaction date to yesterday. For each date in the spine, creates joins to the 6 preceding days plus the current day, forming 7-day lookback windows. This approach ensures that every day has a complete 7-day window for weekly calculations, even if some days had no transactions
- **Key fields**: `timestamp` for the window end date, `joinday` for each day within the 7-day window

### Component D: Weekly distinct address counting
- **Purpose**: Calculates the number of unique addresses active within each 7-day window
- **Logic**: For each 7-day window, merges the HLL sketches from all days within that window using `hll_count.merge_partial()`, then extracts the distinct count using `hll_count.extract()`. This provides an approximate but highly accurate count of unique addresses that were active at any point during the 7-day period
- **Key fields**: `user_wau` containing the distinct address count for each weekly window

### Component E: Dimensional breakdowns
- **Purpose**: Provides weekly active address counts across different aggregation levels
- **Logic**: Creates separate aggregations for different dimensional views: by chain (Mina-specific), by project dbt tag (project-level aggregation), by user type (transaction senders), and by product (null for Mina). Each breakdown maintains the same weekly distinct counting logic but groups results differently to support various analytical needs
- **Key fields**: `dimensions` indicating the aggregation level, `user_wau` with the distinct count for each dimension

### Final aggregation
- **Combining components**: Selects only the 'chain' and 'project_dbt_tag' dimensional breakdowns from the WAU calculation, as these provide the most relevant aggregation levels for weekly active addresses reporting
- **Currency conversion**: Not applicable - this metric counts addresses, not financial values
- **Time aggregation**: Uses rolling 7-day windows where each day represents the end point of a weekly calculation period. No further time aggregation is performed
- **Final calculation**: Renames the `user_wau` field to `active_addresses_weekly` to reflect the metric's purpose. Applies the `finalize_metric_active_addresses_weekly` macro to standardize schema and fill missing dates with zeros, ensuring consistent time series output. The final result represents the count of unique Mina addresses that sent at least one transaction within each rolling 7-day period

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

Unique active addresses over a rolling 7-day window.

Mina ProtocolMINA

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Active addresses (weekly)

Active addresses (weekly)

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