DT | P25 | P50 | P95 | |
---|---|---|---|---|
1 | 2025-03-05 08:00:00.000 | 0.000005 | 0.000005529 | 0.000105 |
2 | 2025-02-25 13:00:00.000 | 0.000005 | 0.000005665 | 0.000115 |
3 | 2025-02-18 20:00:00.000 | 0.000005 | 0.0000077 | 0.000182154 |
4 | 2025-02-19 09:00:00.000 | 0.000005 | 0.0000053 | 0.000105 |
5 | 2025-02-20 06:00:00.000 | 0.000005 | 0.000006 | 0.0001175 |
6 | 2025-03-07 20:00:00.000 | 0.000005 | 0.000007481 | 0.000278338 |
7 | 2025-02-24 05:00:00.000 | 0.000005 | 0.000005924 | 0.0001118935 |
8 | 2025-03-04 02:00:00.000 | 0.000005 | 0.000006218 | 0.00011735335 |
9 | 2025-03-09 13:00:00.000 | 0.000005 | 0.0000056 | 0.0001 |
10 | 2025-03-01 15:00:00.000 | 0.000005 | 0.0000055 | 0.000105 |
11 | 2025-02-13 03:00:00.000 | 0.000005001 | 0.000008417 | 0.00041 |
12 | 2025-02-19 14:00:00.000 | 0.000005 | 0.000005958 | 0.0001689817 |
13 | 2025-02-24 14:00:00.000 | 0.000005 | 0.000005924 | 0.000125 |
14 | 2025-03-04 19:00:00.000 | 0.000005 | 0.000005546 | 0.000105 |
15 | 2025-02-20 02:00:00.000 | 0.000005 | 0.000006626 | 0.0002325 |
16 | 2025-02-26 09:00:00.000 | 0.000005 | 0.000006736 | 0.000105 |
17 | 2025-02-25 07:00:00.000 | 0.000005 | 0.000007838 | 0.0002730659 |
18 | 2025-02-22 02:00:00.000 | 0.000005 | 0.000006 | 0.000205 |
19 | 2025-02-16 13:00:00.000 | 0.000005 | 0.000007017 | 0.000146068 |
20 | 2025-03-09 12:00:00.000 | 0.000005 | 0.000005634 | 0.000088266 |
MostlyData_Solana Stats - Fee vs time (global)
Updated 2025-03-10
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-- forked from Solana Stats - Fee rewards distribution vs time @ https://flipsidecrypto.xyz/studio/queries/02fadac4-c64d-41dc-9d25-3a4634a83263
with date_filter as (
select
case
when '{{n_days}}' != 0 then current_date() - interval '{{n_days}} days'
else cast('{{start_date}}' as timestamp)
end as start_date,
case
when '{{n_days}}' != 0 then current_date()
else cast('{{end_date}}' as timestamp)
end as end_date
)
,txs_info as(
select
rf.tx_id,
date_trunc('hour',rf.block_timestamp) as dt,
rf.fee * pow(10,-9) as fee
from solana.core.fact_transactions rf
join date_filter df
on rf.block_timestamp between df.start_date and df.end_date
)
,group_fee_rewards as(
select
dt,
percentile_cont(0.25) within group (order by fee) as p25,
percentile_cont(0.5) within group (order by fee) as p50,
percentile_cont(0.95) within group (order by fee) as p95
from txs_info
group by dt
Last run: about 1 month ago
...
721
42KB
395s