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Tron is a smart contract platform for decentralized applications (a blockchain). Tron was founded by Justin Sun and launched in 2018.

TRX holders own and govern the protocol. They currently burn all transaction fees paid by users (revenue). It is important to note that the incentives related to energy and bandwidth are effectively returned as revenue, and this is reflected in the earnings.

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Tron

# Tron Active addresses (daily) Methodology

## 1. Overview

The Tron active addresses daily metric measures the number of unique addresses that initiated at least one transaction on the Tron blockchain within a given day. This is a fundamental blockchain activity metric that provides insights into daily user engagement and network utilization. The calculation identifies all transaction senders and counts them distinctly using probabilistic counting algorithms for efficiency.

## 2. Data sources

- **Tron blockchain transaction records**: Raw transaction data from the Tron blockchain containing transaction metadata including timestamps, transaction hashes, and sender addresses (`from_address`)
- **Chain availability configuration**: Configuration data that determines the time periods when Tron chain data should be included in metric calculations

## 3. Step-by-step calculation

### Component A: User identification
- **Purpose**: Identify all users who initiated transactions on the Tron blockchain
- **Logic**: Extract all transaction sender addresses from Tron blockchain transaction records. Each transaction sender is classified as a 'Transaction sender' user type within the 'blockchains_l1' market sector and 'blockchain' business segment. The system assigns no specific product identification since this is a chain-level metric
- **Key fields**: `block_timestamp` for timing, `from_address` as the user identifier, `transaction_hash` for transaction identification

### Component B: Daily user aggregation  
- **Purpose**: Aggregate unique users by day using efficient probabilistic counting
- **Logic**: Truncate transaction timestamps to daily boundaries and group user addresses by day. Initialize HyperLogLog sketches with precision 15 for each unique user address within each day to enable efficient distinct counting at scale
- **Key fields**: `timestamp` (truncated to day), `user_address` for distinct counting, HyperLogLog sketch data

### Component C: Dimensional breakdowns
- **Purpose**: Create multiple views of the daily active users metric across different dimensions
- **Logic**: Generate four separate dimensional breakdowns from the HyperLogLog sketches: project-level aggregation (combining all Tron activity), chain-level breakdown (Tron-specific), user type breakdown (transaction senders), and product-level breakdown (null for blockchain metrics). Each breakdown merges the HyperLogLog sketches and extracts the final distinct counts
- **Key fields**: `dimensions` to identify breakdown type, `chain_id` for chain-specific metrics, `user_type` for user classification, `user_dau` containing the distinct user count

### Final aggregation
- **Combining components**: Select only the 'chain' and 'project_dbt_tag' dimensional breakdowns from the user DAU aggregations, as these represent the core blockchain-level active addresses
- **Time aggregation**: Data is aggregated at daily boundaries with timestamps representing the start of each day
- **Missing data handling**: Apply the finalize metric macro to standardize the schema and fill any missing days with zero values to ensure complete time series
- **Chain availability filtering**: Apply availability filters to exclude data from time periods when the Tron chain should not be included in calculations
- **Final calculation**: Rename the `user_dau` field to `active_addresses_daily` to match the target metric name, representing the count of unique addresses that initiated at least one transaction on that day

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

Unique active addresses over a fixed 24-hour window.

TronTRX

Active addresses (daily)

Active addresses (daily)

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