DEX aggregators

Oku Trade

# Oku Trade Active users (weekly) Methodology

## 1. Overview

Weekly Active Users (WAU) measures the number of distinct users who performed trading activities on the okutrade protocol within a 7-day rolling window. This metric combines users from both swap transactions and flash loan operations, providing a comprehensive view of protocol engagement. The calculation uses HyperLogLog data structures to efficiently count distinct users across multiple dimensions while avoiding double-counting users who are active on multiple days within the week.

## 2. Data sources

The calculation relies on the following raw blockchain data sources:
- **Flash loan events**: Parsed `Pool_Flash_event` logs from okutrade v3 contracts on the XDC blockchain, containing flash loan transaction details
- **Swap events**: Parsed `Pool_Swap_event` logs from okutrade v3 contracts on the XDC blockchain, containing trading transaction details  
- **Transaction data**: XDC blockchain transaction records used to identify the originating user addresses for flash loan events

## 3. Step-by-step calculation

### Component A: Flash loan user extraction
- **Purpose**: Identifies users who performed flash loan operations on okutrade
- **Logic**: Extracts flash loan events from okutrade v3 pool contracts on XDC blockchain. Joins with XDC transaction records to map flash loan events to their originating user addresses, as the flash loan events contain the sender address but need the transaction originator. Filters to distinct events and standardizes the data format with chain, business line, and product metadata.
- **Key fields**: `block_timestamp` for daily aggregation, `user_address` from transaction records for user identification, `contract_user_address` from flash loan events, `transaction_hash` for joining, chain set to 'xdc', product_id set to 'v3'

### Component B: Swap user extraction  
- **Purpose**: Identifies users who performed trading/swap operations on okutrade
- **Logic**: Extracts swap events from okutrade v3 pool contracts on XDC blockchain. Uses the `sender` field directly from swap events as the user address since swap events contain the actual user address. Standardizes the data format with consistent metadata for chain, business line, and product information.
- **Key fields**: `block_timestamp` for daily aggregation, `sender` field as `contract_user_address` for user identification, chain set to 'xdc', product_id set to 'v3', `token0_amount` and `token1_amount` for swap details

### Component C: Daily active user consolidation
- **Purpose**: Combines flash loan and swap users into a unified daily active user dataset
- **Logic**: Unions the user addresses from both flash loan and swap activities, truncating timestamps to day level for daily aggregation. Classifies all users as 'Trader' type regardless of activity type. Uses UNION DISTINCT to ensure users who perform both flash loans and swaps on the same day are only counted once per day.
- **Key fields**: `timestamp` truncated to day, `chain` identifier, `user_type` set to 'Trader', `product_id` for product classification, `user_dau` containing the distinct user address

### Component D: HyperLogLog sketch creation
- **Purpose**: Converts daily active user data into HyperLogLog sketches for efficient distinct counting
- **Logic**: Groups daily active users by timestamp, chain, user type, and product dimensions. Initializes HyperLogLog sketches with precision 15 for each group to enable approximate distinct counting across multiple days without storing individual user addresses.
- **Key fields**: `timestamp` for daily grouping, dimensional fields for breakdowns, `hll` containing the HyperLogLog sketch of users

### Component E: Rolling window construction  
- **Purpose**: Creates 7-day rolling windows for weekly active user calculation
- **Logic**: Generates a datespine covering all days from the first DAU record to yesterday to handle missing dates. For each day in the datespine, creates a 7-day window by generating timestamps for the current day plus the 6 preceding days. Joins this window structure with the daily HLL sketches to collect all relevant user data for each 7-day period.
- **Key fields**: `timestamp` for the target day, `joinday` for each day in the 7-day window, dimensional breakdown fields, `hll` sketches for each day in the window

### Final aggregation
- **Combining components**: Merges HyperLogLog sketches across the 7-day window using `hll_count.merge_partial()` to combine user counts without double-counting users who appear on multiple days within the window
- **Dimensional breakdowns**: Calculates WAU across four different dimensional views - project level (all dimensions null), chain level (grouped by chain), user type level (grouped by user type), and product level (grouped by product_id)  
- **Final calculation**: Extracts the final distinct user count from merged HLL sketches using `hll_count.extract()` to produce the weekly active user count for each dimensional breakdown
- **Schema standardization**: Applies the `finalize_metric_user_wau` macro to standardize the output schema, add metadata fields, and fill missing days with zero values to ensure complete time series data

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

Unique revenue-generating users over a rolling 7-day window.

Oku Trade

Active users (weekly)

Active users (weekly)

Competitive landscape

Chain breakdown