Linea batches users' transactions and submits them to Ethereum, paying a share of the transaction fees to Ethereum validators (expense).

Linea is an L2 smart contract platform for decentralized applications on Ethereum. Linea was founded by the ConsenSys team and launched in 2023.

ConsenSys team owns and governs the protocol. ConsenSys's investors include ParaFi Capital, Microsoft, Coinbase Ventures, etc.

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Blockchains (L2)

Linea

# Linea Active addresses (monthly) Methodology

## 1. Overview

Monthly active addresses measures the number of unique addresses that have sent at least one transaction on the Linea blockchain within a rolling 30-day period. This metric serves as a key indicator of user engagement and network adoption for the Linea layer-2 blockchain. The calculation uses a 30-day rolling window approach, where each day's value represents the count of distinct addresses that were active (sent transactions) at any point during the previous 30 days including the current day.

## 2. Data sources

The calculation relies on the following data sources:
- **Linea blockchain transaction records**: Complete transaction history from the Linea layer-2 blockchain, including transaction metadata and execution details
- **Transaction sender addresses**: The `from_address` field from each transaction, representing the address that initiated and signed the transaction
- **Block timestamps**: Precise timestamps for when each transaction was included in a block on the Linea blockchain

## 3. Step-by-step calculation

### Component A: Transaction sender extraction
- **Purpose**: Identify all transaction senders from raw Linea blockchain data and prepare them for user activity analysis
- **Logic**: Extract transaction records from Linea blockchain data, focusing on the sender address (`from_address`), transaction hash, and block timestamp. Each transaction sender is classified as 'Transaction sender' user type and associated with the 'linea' chain identifier, 'blockchains_l2' market sector, and 'blockchain' business segment
- **Key fields**: `from_address` becomes `user_address`, `block_timestamp` preserves timing information, `transaction_hash` for transaction identification

### Component B: Daily active user calculation
- **Purpose**: Calculate the number of distinct active addresses for each day
- **Logic**: Group all transaction sender records by day using timestamp truncation to day boundaries. For each day, count the distinct number of unique addresses that sent at least one transaction. This creates a daily snapshot of unique active addresses
- **Key fields**: `timestamp` truncated to day granularity, `user_address` for distinct counting, `user_dau` containing the unique address

### Component C: Monthly active user aggregation using HyperLogLog
- **Purpose**: Calculate 30-day rolling monthly active users using probabilistic counting for efficient computation
- **Logic**: Create a comprehensive datespine covering all days from the first transaction to present. For each day in the datespine, establish a 30-day lookback window (current day minus 29 previous days). Use HyperLogLog probabilistic counting to efficiently track distinct addresses across the 30-day window. Initialize HLL sketches for each day's active users, then merge HLL sketches across each 30-day window to get approximate distinct counts. Generate multiple dimensional breakdowns including overall project level, chain level, user type level, and product level aggregations
- **Key fields**: `timestamp` for the end date of each 30-day window, `hll` for HyperLogLog sketch data, `user_mau` for the final distinct count extracted from merged HLL sketches

### Component D: Final active addresses aggregation
- **Purpose**: Transform monthly active users into the final active addresses monthly metric with proper formatting
- **Logic**: Select only the relevant dimensional breakdowns ('chain' and 'project_dbt_tag' dimensions) from the MAU calculations. Rename the `user_mau` field to `active_addresses_monthly` to reflect that these represent unique addresses rather than traditional user accounts. Apply the finalization macro to ensure proper schema formatting and fill any missing time periods with zero values
- **Key fields**: `active_addresses_monthly` as the final metric value, `dimensions` indicating the aggregation level, `timestamp_grain` set to the appropriate time granularity

### Final aggregation
- **Combining components**: The metric flows sequentially through each component, with daily active addresses feeding into the HyperLogLog MAU calculation, which then feeds into the final active addresses aggregation
- **Currency conversion**: No currency conversion required as this is a count-based metric
- **Time aggregation**: Uses rolling 30-day windows where each day's value represents unique active addresses over the preceding 30 days including the current day
- **Final calculation**: The final active addresses monthly value represents the approximate count of distinct addresses that sent at least one transaction within any 30-day rolling period, calculated using HyperLogLog probabilistic counting for computational efficiency

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

Unique addresses active over a rolling 30-day window.

LineaLINEA

Active addresses (monthly)

Active addresses (monthly)

Competitive landscape

Chain breakdown