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 (weekly) Methodology

## 1. Overview

Weekly active addresses measures the number of unique wallet addresses that initiated at least one transaction on the Linea blockchain within a 7-day rolling window. This metric provides insight into the size of the active user base and user engagement patterns on the Linea Layer 2 network. The calculation uses a rolling 7-day window approach with HyperLogLog probabilistic counting to accurately handle overlapping users across different days without double-counting.

## 2. Data sources

The calculation relies on the following raw data sources:
- **Linea transaction records**: Complete transaction history from the Linea blockchain containing transaction metadata, timestamps, and sender addresses
- **Chain availability data**: Configuration data that defines periods when the Linea network was operational and reliable for metrics calculation

## 3. Step-by-step calculation

### Component A: User extraction from transactions
- **Purpose**: Identifies all unique user addresses that sent transactions each day
- **Logic**: Extracts the sender address (`from_address`) from each Linea transaction record along with the block timestamp. Each transaction sender is classified as a "Transaction sender" user type and tagged with Linea chain metadata including market sector "blockchains_l2" and business segment "blockchain". The block timestamp is preserved for daily aggregation.
- **Key fields**: `from_address` becomes the `user_address`, `block_timestamp` for temporal grouping, transaction metadata for classification

### Component B: Daily active user calculation  
- **Purpose**: Creates daily snapshots of unique active addresses
- **Logic**: Groups all user addresses by day using timestamp truncation to day boundaries. Takes distinct user addresses within each day to eliminate duplicate counting when users make multiple transactions. Each unique address-day combination becomes one record representing that address being active on that specific day. Applies incremental processing to handle new data efficiently.
- **Key fields**: `timestamp` (day-truncated), `user_address` (deduplicated daily), `user_type`, chain and product metadata

### Component C: HyperLogLog sketch creation
- **Purpose**: Converts daily user sets into probabilistic data structures for efficient weekly aggregation
- **Logic**: For each day's set of unique user addresses, creates a HyperLogLog sketch using `hll_count.init()` with precision parameter 15. This allows approximate but highly accurate counting of unique users across time windows without storing individual addresses. Groups by timestamp, chain, user type, and product dimensions to enable multi-dimensional breakdowns.
- **Key fields**: `hll` sketch containing compressed user set, dimensional grouping fields

### Component D: Rolling window generation
- **Purpose**: Creates 7-day rolling windows for each date to calculate weekly active users
- **Logic**: Generates a complete datespine covering all days from the earliest data to yesterday. For each date in the datespine, creates a 7-day window spanning from 6 days prior through the current day. Uses cross-join logic between the datespine and a 7-day range generator to create all date-window combinations. This ensures consistent 7-day windows even when some days have no activity.
- **Key fields**: `timestamp` (target date), `joinday` (each day within the 7-day window)

### Component E: Weekly aggregation with deduplication
- **Purpose**: Merges daily user sets across 7-day windows to count unique weekly active addresses
- **Logic**: For each target date's 7-day window, joins the daily HyperLogLog sketches for all days in that window. Merges the HyperLogLog sketches using `hll_count.merge_partial()` to combine user sets across the 7 days, automatically handling users who were active on multiple days within the window. Extracts the final unique count using `hll_count.extract()`. This produces a rolling 7-day unique user count for each date.
- **Key fields**: `user_wau` (weekly active users), dimensional breakdowns

### Component F: Multi-dimensional breakdown
- **Purpose**: Provides weekly active address counts across different analytical dimensions  
- **Logic**: Calculates weekly active addresses separately for four different dimensional breakdowns: chain-level (Linea chain totals), project-level (project_dbt_tag aggregation), user-type-level (breakdown by transaction sender types), and product-level (breakdown by product categories). Each breakdown uses the same HyperLogLog merging logic but groups by different dimensional fields. Results are combined using union operations to create a unified dataset with dimension indicators.
- **Key fields**: `dimensions` (indicates breakdown type), `chain_id`, `user_type`, `product_id`, `user_wau`

### Final aggregation
- **Combining components**: The multi-dimensional weekly active user calculations are unioned together and filtered to include only chain-level and project-level dimensions for the active addresses metric. The `user_wau` field is renamed to `active_addresses_weekly` to reflect the metric naming convention.
- **Currency conversion**: Not applicable for this address-counting metric
- **Time aggregation**: Uses 7-day rolling windows calculated daily, where each date represents the count of unique addresses active in that date's 7-day lookback period
- **Final calculation**: The final weekly active addresses value represents the count of unique wallet addresses that initiated at least one transaction within the 7-day period ending on the given date, calculated using HyperLogLog probabilistic counting for accuracy and efficiency

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

Unique active addresses over a rolling 7-day window.

LineaLINEA

Active addresses (weekly)

Active addresses (weekly)

Competitive landscape

Chain breakdown