adriaparcerisasflow stats: avg tx fee (over time) weekly
    Updated 1 day ago
    WITH evm_data AS (
    SELECT
    DATE_TRUNC('day', BLOCK_TIMESTAMP) AS date,
    COUNT(TX_HASH) AS total_transactions,
    SUM(CASE WHEN tx_succeeded = 'TRUE' THEN 1 ELSE 0 END) AS successful_transactions,
    successful_transactions/total_transactions as success_rate,
    SUM(tx_fee) AS fees,
    AVG(tx_fee) AS avg_tx_fee,
    COUNT(DISTINCT FROM_ADDRESS) AS unique_users,
    avg(DATEDIFF(MINUTE, INSERTED_TIMESTAMP, BLOCK_TIMESTAMP)) AS latency_MINUTEs
    FROM
    flow.core_evm.fact_transactions
    --WHERE
    -- BLOCK_TIMESTAMP >= DATEADD(day, -30, CURRENT_DATE) and block_timestamp<current_date
    GROUP BY
    1
    ),
    non_evm_data AS (
    SELECT
    DATE_TRUNC('day', x.BLOCK_TIMESTAMP) AS date,
    COUNT(distinct x.TX_ID) AS total_transactions,
    SUM(CASE WHEN x.TX_SUCCEEDED = 'TRUE' THEN 1 ELSE 0 END) AS successful_transactions,
    successful_transactions/total_transactions as success_rate,
    SUM(y.event_data:amount) AS fees,
    AVG(y.event_data:amount) AS avg_tx_fee,
    COUNT(DISTINCT x.PAYER) AS unique_users,
    avg(DATEDIFF(MINUTE, x.INSERTED_TIMESTAMP, x.BLOCK_TIMESTAMP)) AS latency_MINUTEs
    FROM
    flow.core.fact_transactions x
    join flow.core.fact_events y on x.tx_id=y.tx_id
    WHERE
    -- x.BLOCK_TIMESTAMP >= DATEADD(day, -30, CURRENT_DATE) and
    event_contract='A.f919ee77447b7497.FlowFees'
    and event_Type='FeesDeducted' and x.block_timestamp<current_date
    GROUP BY
    1
    Last run: 1 day ago
    MONTH
    AVG_TX_FEE_FLOW
    AVG_TX_FEE_USD
    1
    2022-04-04 00:00:00.0000.0000099144659350.00006682217854
    2
    2022-04-11 00:00:00.0000.0000098339604920.00005753230857
    3
    2022-04-18 00:00:00.0000.0000098173421580.00005636014521
    4
    2022-04-25 00:00:00.0000.000009713823890.00004977392497
    5
    2022-05-02 00:00:00.0000.0000098458546760.00004538982353
    6
    2022-05-09 00:00:00.0000.0000093266256230.00003107953345
    7
    2022-05-16 00:00:00.0000.0000098707419210.00002844405534
    8
    2022-05-23 00:00:00.0000.0000099051617650.00002570637657
    9
    2022-05-30 00:00:00.0000.0000080364408510.0000205489855
    10
    2022-06-06 00:00:00.0000.0000062055756940.00001444907036
    11
    2022-06-13 00:00:00.0000.0000089663215240.00001332722221
    12
    2022-06-20 00:00:00.0000.0000073656587520.00001161781716
    13
    2022-06-27 00:00:00.0000.000010212098810.00001616938612
    14
    2022-07-04 00:00:00.0000.000015649845590.00002535198037
    15
    2022-07-11 00:00:00.0000.000021463448660.00003291202761
    16
    2022-07-18 00:00:00.0000.000031580196160.00005803608536
    17
    2022-07-25 00:00:00.0000.00001913710070.00003462226203
    18
    2022-08-01 00:00:00.0000.000024384846030.00005579632272
    19
    2022-08-08 00:00:00.0000.000025662093540.00007635115802
    20
    2022-08-15 00:00:00.0000.000032724863530.00008218465703
    ...
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    10KB
    279s