feyikemiNEAR Daily Users Trend
    Updated 2025-03-31
    WITH tb1 AS(
    SELECT
    Date_trunc('day', Block_timestamp) AS Date,
    COUNT(DISTINCT TX_SIGNER) AS Addresses
    FROM near.core.fact_transactions
    WHERE BLOCK_TIMESTAMP::DATE BETWEEN '{{Start_Date}}' AND '{{End_Date}}'
    AND TX_SUCCEEDED = 'true'
    GROUP BY 1
    ),

    tb2 AS (
    SELECT
    min(block_timestamp::date) as Min_date,
    TX_SIGNER AS New_Address
    FROM near.core.fact_transactions
    WHERE TX_SUCCEEDED = 'true'
    GROUP BY 2
    ),

    tb3 AS (
    SELECT
    Min_date,
    COUNT(DISTINCT New_Address) AS New_Addresses_cnt
    FROM tb2
    WHERE Min_date BETWEEN '{{Start_Date}}' AND '{{End_Date}}'
    GROUP BY 1
    )

    SELECT
    Date,
    Addresses AS Active_Addresses,
    New_Addresses_cnt AS New_Addresses
    FROM tb1 a
    JOIN tb3 b ON a.Date = b.Min_date
    Last run: about 2 months ago
    DATE
    ACTIVE_ADDRESSES
    NEW_ADDRESSES
    1
    2024-10-29 00:00:00.0009320528931
    2
    2024-10-27 00:00:00.0009673169304
    3
    2024-10-15 00:00:00.000106145918148
    4
    2024-09-30 00:00:00.000103855956743
    5
    2024-10-02 00:00:00.00093183824889
    6
    2024-09-13 00:00:00.00098841213235
    7
    2024-10-16 00:00:00.000106267212827
    8
    2024-10-25 00:00:00.00093262217358
    9
    2024-09-16 00:00:00.000101817119155
    10
    2024-09-03 00:00:00.00071254425437
    11
    2024-09-12 00:00:00.000100750427996
    12
    2024-10-06 00:00:00.000104811327335
    13
    2024-09-19 00:00:00.00099801118348
    14
    2024-09-06 00:00:00.000102605123670
    15
    2024-10-23 00:00:00.00093224617018
    16
    2024-10-17 00:00:00.000102841419461
    17
    2024-09-01 00:00:00.00068761711096
    18
    2024-10-28 00:00:00.0009238118510
    19
    2024-10-14 00:00:00.000109354621005
    20
    2024-09-29 00:00:00.000102688530065
    61
    2KB
    140s