(SELECT block_timestamp as bt, nft_collection as nc, nft_id as nid, buyer as b from flow.core.fact_nft_sales ),

flow as

( SELECT count(*) as total_instances, sum(in_a_day) as total_in_a_day, sum(in_a_week) as total_in_a_week,

total_in_a_week/total_instances*100 as percent_in_a_week,

total_in_a_day/total_instances*100 as percent_in_a_day,

sum(in_a_month) as total_in_a_month,

total_in_a_month/total_instances *100 as percent_in_a_month,

'flow' as chain

from

(SELECT *, case when timestampdiff(sql_tsi_hour, bt, block_timestamp) < 24 then 1 else 0 end as in_a_day,

case when timestampdiff(sql_tsi_hour, bt, block_timestamp) < 24*7 then 1 else 0 end as in_a_week,

case when timestampdiff(sql_tsi_hour, bt, block_timestamp) < 24*30 then 1 else 0 end as in_a_month

from flow.core.fact_nft_sales

inner join a

on block_timestamp > bt and nft_collection = nc and nft_id = nid and b= seller) ),

e as

(SELECT block_timestamp as bt, nft_address as na, tokenid as tid, buyer_address as b from ethereum.core.ez_nft_sales) ,

eth as

(SELECT count(*) as total_instances, sum(in_a_day) as total_in_a_day, sum(in_a_week) as total_in_a_week,

total_in_a_week/total_instances*100 as percent_in_a_week,

total_in_a_day/total_instances*100 as percent_in_a_day,

sum(in_a_month) as total_in_a_month,

total_in_a_month/total_instances *100 as percent_in_a_month,

'eth' as chain

from

(SELECT *, case when timestampdiff(sql_tsi_hour, bt, block_timestamp) < 24 then 1 else 0 end as in_a_day,

case when timestampdiff(sql_tsi_hour, bt, block_timestamp) < 24*7 then 1 else 0 end as in_a_week,

case when timestampdiff(sql_tsi_hour, bt, block_timestamp) < 24*30 then 1 else 0 end as in_a_month from ethereum.core.ez_nft_sales

inner join e

on block_timestamp > bt and nft_address = na and tokenid = tid and b = seller_address )),

s as

(SELECT block_timestamp as bt, purchaser as b, mint as m from solana.core.fact_nft_sales ) ,

sol as

(SELECT count(*) as total_instances, sum(in_a_day) as total_in_a_day, sum(in_a_week) as total_in_a_week,

total_in_a_week/total_instances*100 as percent_in_a_week,