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

Conflux is a smart contract platform for decentralized applications (a blockchain). Conflux was founded by David Chow, Fan Long, Ming Wu, and YuanJie Zhang and launched in 2020. Note that this dashboard only includes Conflux Core Space.

CFX holders own and govern the protocol. They currently do not take a cut of the total transaction fees paid by users (revenue).

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Blockchains (L1)

Conflux Core Space

# Conflux Core Space Active addresses (monthly) Methodology

## 1. Overview

Monthly active addresses measures the number of unique wallet addresses that have initiated at least one transaction on the Conflux network within a 30-day rolling window. This metric provides insight into user engagement and network adoption by tracking how many distinct participants are actively using the blockchain each month. The calculation uses a sophisticated rolling window approach with HyperLogLog data structures to efficiently process large volumes of transaction data while maintaining accuracy for unique address counting.

## 2. Data sources

The calculation relies on the following raw data sources:

- **Conflux blockchain transactions**: Raw transaction records from the Conflux network containing transaction hashes, sender addresses, and execution details
- **Block timestamp data**: Temporal information for each transaction indicating when it was included in a block on the Conflux blockchain
- **Transaction sender addresses**: Unique wallet addresses that initiated transactions, representing the active users of the network

## 3. Step-by-step calculation

### Component A: Daily active user extraction
- **Purpose**: Identifies unique wallet addresses that were active each day
- **Logic**: Processes raw Conflux transaction data to extract sender addresses and their corresponding transaction dates. Block timestamps are truncated to day granularity to group transactions by calendar day. Within each day, sender addresses are deduplicated to ensure each unique wallet is counted only once, regardless of how many transactions they sent
- **Key fields**: The `block_timestamp` field provides temporal context, `sender` field identifies the active wallet address, and `transaction_hash` provides transaction uniqueness. Additional metadata includes `chain` identifier set to 'conflux', `user_type` set to 'Transaction sender', and `market_sector_id` set to 'blockchains_l1'

### Component B: HyperLogLog sketch creation
- **Purpose**: Converts daily unique user counts into memory-efficient data structures for large-scale processing
- **Logic**: Takes the daily active user data and creates HyperLogLog sketches for each day, grouped by timestamp, chain identifier, user type, and product identifier. HLL sketches allow for efficient unique counting and merging operations while maintaining statistical accuracy for cardinality estimation
- **Key fields**: The `timestamp` field represents the day, `chain_id` identifies the Conflux network, `user_type` categorizes the type of user activity, and `hll` contains the HyperLogLog sketch data structure

### Component C: Rolling window construction
- **Purpose**: Creates 30-day rolling windows for monthly active user calculation
- **Logic**: Generates a complete date spine to ensure no missing dates in the time series. For each day in the date range, creates associations with that day plus the previous 29 days (total 30-day window). This windowing approach ensures that each monthly calculation captures users active within any 30-day period ending on that specific date
- **Key fields**: The `timestamp` field represents the end date of the 30-day window, and `joinday` represents each individual day within that window that will be used for aggregation

### Component D: Monthly active user aggregation
- **Purpose**: Calculates unique user counts across 30-day periods using HLL merging
- **Logic**: For each 30-day window, merges the HyperLogLog sketches from all days within that window. The HLL merge operation ensures that users active on multiple days within the 30-day period are counted only once. Extracts the final unique count from the merged HLL sketch to produce the monthly active user metric
- **Key fields**: The `timestamp` represents the end of the 30-day period, `user_mau` contains the calculated monthly active user count, and dimension fields like `chain_id`, `user_type`, and `product_id` provide breakdowns across different categories

### Component E: Dimensional breakdowns
- **Purpose**: Provides MAU calculations across multiple analytical dimensions
- **Logic**: Creates separate aggregations for different analytical perspectives including project-level (project_dbt_tag), chain-level, user-type-level, and product-level breakdowns. Each breakdown uses the same HLL merging logic but groups by different combinations of dimensions to enable analysis at various levels of granularity
- **Key fields**: The `dimensions` field indicates the type of breakdown ('project_dbt_tag', 'chain', 'user_type', 'product_id'), while the corresponding dimension-specific fields contain the actual values for that breakdown level

### Final aggregation
- **Combining components**: The various dimensional breakdowns are combined using union operations to create a comprehensive dataset with MAU calculations across all analytical dimensions
- **Currency conversion**: No currency conversion is required as this metric counts addresses rather than financial values
- **Time aggregation**: Uses 30-day rolling windows where each day represents the end of a monthly period, providing daily updates to monthly active address counts
- **Final calculation**: Renames the `user_mau` field to `active_addresses_monthly` to reflect that in blockchain analytics, users are represented by their wallet addresses. Applies standardization through the finalize_metric macro which ensures consistent schema, fills missing periods with zeros, and applies chain availability filters for data quality assurance

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

Unique addresses active over a rolling 30-day window.

Conflux Core SpaceCFX

Archived

Active addresses (monthly)

Active addresses (monthly)

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