with price as ( select DATE_TRUNC( {{frequency}}, RECORDED_HOUR ) AS DATE, avg(case when id = 'ethereum' then close end) as eth_price, avg(case when id = 'avalanche-2' then close end) as avax_price, avg(case when id = 'binancecoin' then close end) as bnb_price, avg(case when id = 'xdai' then close end) as xdai_price, avg(case when id = 'near' then close end) as near_price, avg(case when id = 'optimism' then close end) as op_price, avg(case when id = 'osmosis' then close end) as osmos_price, avg(case when id = 'matic-network' then close end) as matic_price, avg(case when id = 'solana' then close end) as sol_price FROM crosschain.core.fact_hourly_prices group by date ), eth as ( select t.*, p.eth_price as price, p.eth_price * t.fee as fee_usd, ln((fee_usd - lag(fee_usd) over(order by t.date))/lag(fee_usd) over(order by t.date) + 1)as pct_f from (select DATE_TRUNC( {{frequency}}, block_timestamp ) AS DATE, count(DISTINCT(FROM_ADDRESS)) as user, COUNT(TX_HASH) as tx, sum(tx_fee) as fee, ln((user - lag(user) over(order by date))/lag(user) over(order by date) + 1)as pct_u, ln((tx - lag(tx) over(order by date))/lag(tx) over(order by date) + 1)as pct_t from ethereum.core.fact_transactions GROUP by date) t left join price p on t.date = p.date where t.date >= date_trunc('day', {{time_from}}) and t.date < date_trunc('day', {{time_to}}) ), arb as ( select t.*, p.eth_price as price, p.eth_price * t.fee as fee_usd, ln((fee_usd - lag(fee_usd) over(order by t.date))/lag(fee_usd) over(order by t.date) + 1)as pct_f from (select DATE_TRUNC( {{frequency}}, block_timestamp ) AS DATE, count(DISTINCT(FROM_ADDRESS)) as user, COUNT(TX_HASH) as tx, sum(tx_fee) as fee, ln((user - lag(user) over(order by date))/lag(user) over(order by date) + 1)as pct_u, ln((tx - lag(tx) over(order by date))/lag(tx) over(order by date) + 1)as pct_t from arbitrum.core.fact_transactions GROUP by date) t left join price p on t.date = p.date where t.date >= date_trunc('day', {{time_from}}) and t.date < date_trunc('day', {{time_to}}) ), avax as ( select t.*, p.avax_price as price, p.avax_price * t.fee as fee_usd, ln((fee_usd - lag(fee_usd) over(order by t.date))/lag(fee_usd) over(order by t.date) + 1)as pct_f from (select DATE_TRUNC( {{frequency}}, block_timestamp ) AS DATE, count(DISTINCT(FROM_ADDRESS)) as user, COUNT(TX_HASH) as tx, sum(tx_fee) as fee, ln((user - lag(user) over(order by date))/lag(user) over(order by date) + 1)as pct_u, ln((tx - lag(tx) over(order by date))/lag(tx) over(order by date) + 1)as pct_t from avalanche.core.fact_transactions GROUP by date) t left join price p on t.date = p.date where t.date >= date_trunc('day', {{time_from}}) and t.date < date_trunc('day', {{time_to}}) ), bsc as ( select t.*, p.bnb_price as price, price * t.fee as fee_usd, ln((fee_usd - lag(fee_usd) over(order by t.date))/lag(fee_usd) over(order by t.date) + 1)as pct_f from (select DATE_TRUNC( {{frequency}}, block_timestamp ) AS DATE, count(DISTINCT(FROM_ADDRESS)) as user, COUNT(TX_HASH) as tx, sum(tx_fee) as fee, ln((user - lag(user) over(order by date))/lag(user) over(order by date) + 1)as pct_u, ln((tx - lag(tx) over(order by date))/lag(tx) over(order by date) + 1)as pct_t from bsc.core.fact_transactions GROUP by date) t left join price p on t.date = p.date where t.date >= date_trunc('day', {{time_from}}) and t.date < date_trunc('day', {{time_to}}) ), axelar as ( select DATE_TRUNC( {{frequency}}, block_timestamp ) AS DATE, count(DISTINCT(SENDER)) as user, COUNT(TX_ID) as tx, ln((tx - lag(tx) over(order by date))/lag(tx) over(order by date) + 1)as pct_t, ln((user - lag(user) over(order by date))/lag(user) over(order by date) + 1)as pct_u from axelar.core.fact_transfers where date >= date_trunc('day', {{time_from}}) and date < date_trunc('day', {{time_to}}) GROUP by date ), flow as ( select t.* from (select DATE_TRUNC( {{frequency}}, block_timestamp ) AS DATE, count(DISTINCT(PROPOSER)) as user, COUNT(TX_ID) as tx, ln((user - lag(user) over(order by date))/lag(user) over(order by date) + 1)as pct_u, ln((tx - lag(tx) over(order by date))/lag(tx) over(order by date) + 1)as pct_t from flow.core.fact_transactions GROUP by date) t left join price p on t.date = p.date where t.date >= date_trunc('day', {{time_from}}) and t.date < date_trunc('day', {{time_to}}) ), gnosis as ( select t.*, p.xdai_price as price, price * t.fee as fee_usd, ln((fee_usd - lag(fee_usd) over(order by t.date))/lag(fee_usd) over(order by t.date) + 1)as pct_f from (select DATE_TRUNC( {{frequency}}, block_timestamp ) AS DATE, count(DISTINCT(from_address)) as user, COUNT(TX_hash) as tx, sum(TX_FEE) as fee, ln((user - lag(user) over(order by date))/lag(user) over(order by date) + 1)as pct_u, ln((tx - lag(tx) over(order by date))/lag(tx) over(order by date) + 1)as pct_t from gnosis.core.fact_transactions GROUP by date) t left join price p on t.date = p.date where t.date >= date_trunc('day', {{time_from}}) and t.date < date_trunc('day', {{time_to}}) ), near as ( select t.*, p.near_price as price, price * t.fee as fee_usd, ln((fee_usd - lag(fee_usd) over(order by t.date))/lag(fee_usd) over(order by t.date) + 1)as pct_f from (select DATE_TRUNC( {{frequency}}, block_timestamp ) AS DATE, count(DISTINCT(TX_SIGNER)) as user, COUNT(TX_hash) as tx, sum(TRANSACTION_FEE/1e24) as fee, ln((user - lag(user) over(order by date))/lag(user) over(order by date) + 1)as pct_u, ln((tx - lag(tx) over(order by date))/lag(tx) over(order by date) + 1)as pct_t from near.core.fact_transfers GROUP by date) t left join price p on t.date = p.date where t.date >= date_trunc('day', {{time_from}}) and t.date < date_trunc('day', {{time_to}}) ), op as ( select t.*, p.op_price as price, price * t.fee as fee_usd, ln((fee_usd - lag(fee_usd) over(order by t.date))/lag(fee_usd) over(order by t.date) + 1)as pct_f from (select DATE_TRUNC( {{frequency}}, block_timestamp ) AS DATE, count(DISTINCT(FROM_ADDRESS)) as user, COUNT(TX_HASH) as tx, sum(tx_fee) as fee, ln((user - lag(user) over(order by date))/lag(user) over(order by date) + 1)as pct_u, ln((tx - lag(tx) over(order by date))/lag(tx) over(order by date) + 1)as pct_t from optimism.core.fact_transactions GROUP by date) t left join price p on t.date = p.date where t.date >= date_trunc('day', {{time_from}}) and t.date < date_trunc('day', {{time_to}}) ), osmos as ( select t.*, p.osmos_price as price, price * t.fee1 as fee_usd, ln((fee_usd - lag(fee_usd) over(order by t.date))/lag(fee_usd) over(order by t.date) + 1)as pct_f from (select DATE_TRUNC( {{frequency}}, block_timestamp ) AS DATE, count(DISTINCT(TX_FROM)) as user, COUNT(TX_ID) as tx, sum(case when fee LIKE '%uosmo%' then REVERSE(substr(REVERSE(fee),6))/1e6 ELSE 0 END) as fee1, ln((user - lag(user) over(order by date))/lag(user) over(order by date) + 1)as pct_u, ln((tx - lag(tx) over(order by date))/lag(tx) over(order by date) + 1)as pct_t from osmosis.core.fact_transactions GROUP by date) t left join price p on t.date = p.date where t.date >= date_trunc('day', {{time_from}}) and t.date < date_trunc('day', {{time_to}}) ), polygon as ( select t.*, p.matic_price as price, price * t.fee as fee_usd, ln((fee_usd - lag(fee_usd) over(order by t.date))/lag(fee_usd) over(order by t.date) + 1)as pct_f from (select DATE_TRUNC( {{frequency}}, block_timestamp ) AS DATE, count(DISTINCT(FROM_ADDRESS)) as user, COUNT(TX_HASH) as tx, sum(tx_fee) as fee, ln((user - lag(user) over(order by date))/lag(user) over(order by date) + 1)as pct_u, ln((tx - lag(tx) over(order by date))/lag(tx) over(order by date) + 1)as pct_t from polygon.core.fact_transactions GROUP by date) t left join price p on t.date = p.date where t.date >= date_trunc('day', {{time_from}}) and t.date < date_trunc('day', {{time_to}}) ), stark as (select DATE_TRUNC( {{frequency}}, TIMESTAMP ) AS DATE, count(TX_HASH) as tx, ln((tx - lag(tx) over(order by date))/lag(tx) over(order by date) + 1)as pct_t from tokenflow_starknet.decoded.transactions where CHAIN_ID = 'mainnet' and date >= date_trunc('day', {{time_from}}) and date < date_trunc('day', {{time_to}}) GROUP BY date), cal as ( select -- eth eth.date as date, sum(eth.pct_u) over(order by eth.date) as eth_user_pct1, sum(eth.pct_t) over(order by eth.date) as eth_tx_pct1, sum(eth.pct_f) over(order by eth.date) as eth_fee_pct1, round(exp(eth_user_pct1),2)-1 as eth_user_pct, round(exp(eth_tx_pct1),2)-1 as eth_tx_pct, round(exp(eth_fee_pct1),2)-1 as eth_fee_pct, -- arb sum(arb.pct_u) over(order by eth.date) as arb_user_pct1, sum(arb.pct_t) over(order by eth.date) as arb_tx_pct1, sum(arb.pct_f) over(order by eth.date) as arb_fee_pct1, round(exp(arb_user_pct1),2)-1 as arb_user_pct, round(exp(arb_tx_pct1),2)-1 as arb_tx_pct, round(exp(arb_fee_pct1),2)-1 as arb_fee_pct, -- avax sum(avax.pct_u) over(order by eth.date) as avax_user_pct1, sum(avax.pct_t) over(order by eth.date) as avax_tx_pct1, sum(avax.pct_f) over(order by eth.date) as avax_fee_pct1, round(exp(avax_user_pct1),2) -1 as avax_user_pct, round(exp(avax_tx_pct1),2) -1 as avax_tx_pct, round(exp(avax_fee_pct1),2)-1 as avax_fee_pct, -- bsc sum(bsc.pct_u) over(order by eth.date) as bsc_user_pct1, sum(bsc.pct_t) over(order by eth.date) as bsc_tx_pct1, sum(bsc.pct_f) over(order by eth.date) as bsc_fee_pct1, round(exp(bsc_user_pct1),2)-1 as bsc_user_pct, round(exp(bsc_tx_pct1),2)-1 as bsc_tx_pct, round(exp(bsc_fee_pct1),2)-1 as bsc_fee_pct, -- axelar sum(axelar.pct_u) over(order by eth.date) as axelar_user_pct1, sum(axelar.pct_t) over(order by eth.date) as axelar_tx_pct1, round(exp(axelar_user_pct1),2)-1 as axelar_user_pct, round(exp(axelar_tx_pct1),2)-1 as axelar_tx_pct, -- flow sum(flow.pct_u) over(order by eth.date) as flow_user_pct1, sum(flow.pct_t) over(order by eth.date) as flow_tx_pct1, round(exp(flow_user_pct1),2)-1 as flow_user_pct, round(exp(flow_tx_pct1),2)-1 as flow_tx_pct, -- gnosis sum(gnosis.pct_u) over(order by eth.date) as gnosis_user_pct1, sum(gnosis.pct_t) over(order by eth.date) as gnosis_tx_pct1, sum(gnosis.pct_f) over(order by eth.date) as gnosis_fee_pct1, round(exp(gnosis_user_pct1),2)-1 as gnosis_user_pct, round(exp(gnosis_tx_pct1),2)-1 as gnosis_tx_pct, round(exp(gnosis_fee_pct1),2)-1 as gnosis_fee_pct, -- near sum(near.pct_u) over(order by eth.date) as near_user_pct1, sum(near.pct_t) over(order by eth.date) as near_tx_pct1, sum(near.pct_f) over(order by eth.date) as near_fee_pct1, round(exp(near_user_pct1),2)-1 as near_user_pct, round(exp(near_tx_pct1),2)-1 as near_tx_pct, round(exp(near_fee_pct1),2)-1 as near_fee_pct, -- op sum(op.pct_u) over(order by eth.date) as op_user_pct1, sum(op.pct_t) over(order by eth.date) as op_tx_pct1, sum(op.pct_f) over(order by eth.date) as op_fee_pct1, round(exp(op_user_pct1),2)-1 as op_user_pct, round(exp(op_tx_pct1),2)-1 as op_tx_pct, round(exp(op_fee_pct1),2)-1 as op_fee_pct, -- osmos sum(osmos.pct_u) over(order by eth.date) as osmos_user_pct1, sum(osmos.pct_t) over(order by eth.date) as osmos_tx_pct1, sum(osmos.pct_f) over(order by eth.date) as osmos_fee_pct1, round(exp(osmos_user_pct1),2)-1 as osmos_user_pct, round(exp(osmos_tx_pct1),2)-1 as osmos_tx_pct, round(exp(osmos_fee_pct1),2)-1 as osmos_fee_pct, -- polygon sum(polygon.pct_u) over(order by eth.date) as polygon_user_pct1, sum(polygon.pct_t) over(order by eth.date) as polygon_tx_pct1, sum(polygon.pct_f) over(order by eth.date) as polygon_fee_pct1, round(exp(polygon_user_pct1),2)-1 as polygon_user_pct, round(exp(polygon_tx_pct1),2)-1 as polygon_tx_pct, round(exp(polygon_fee_pct1),2)-1 as polygon_fee_pct, -- stark sum(stark.pct_t) over(order by eth.date) as stark_tx_pct1, round(exp(stark_tx_pct1),2)-1 as stark_tx_pct -- sol -- sum(sol.pct_u) over(order by eth.date) as sol_user_pct1, -- sum(sol.pct_t) over(order by eth.date) as sol_tx_pct1, -- sum(sol.pct_f) over(order by eth.date) as sol_fee_pct1, -- round(exp(sol_user_pct1),2)-1 as sol_user_pct, -- round(exp(sol_tx_pct1),2)-1 as sol_tx_pct, -- round(exp(sol_fee_pct1),2)-1 as sol_fee_pct FROM eth left join arb on eth.date = arb.date left join avax on eth.date = avax.date left join bsc on eth.date = bsc.date left join axelar on eth.date = axelar.date left join flow on eth.date = flow.date left join gnosis on eth.date = gnosis.date left join near on eth.date = near.date left join op on eth.date = op.date left join osmos on eth.date = osmos.date left join polygon on eth.date = polygon.date left join stark on eth.date = stark.date -- left join sol on eth.date = sol.date ) select -- eth eth.date as date, avg(cal.eth_user_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as eth_user_ma, avg(cal.eth_tx_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as eth_tx_ma, avg(cal.eth_fee_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as eth_fee_ma, eth.tx as eth_tx, eth.user as eth_user, eth.fee as eth_fee, eth.price as eth_price, eth.fee_usd as eth_fee_usd, avg(eth.tx/eth.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as eth_tx_per_user_ma, avg(eth.fee_usd/eth.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as eth_fee_per_user_ma, avg(eth.fee_usd/eth.tx) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as eth_fee_per_tx_ma, -- arb avg(cal.arb_user_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as arb_user_ma, avg(cal.arb_tx_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as arb_tx_ma, avg(cal.arb_fee_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as arb_fee_ma, arb.tx as arb_tx, arb.user as arb_user, arb.fee as arb_fee, arb.price as eth_price, arb.fee_usd as arb_fee_usd, avg(arb.tx/arb.user ) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as arb_tx_per_user_ma, avg(arb.fee_usd/arb.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as arb_fee_per_user_ma, avg(arb.fee_usd/arb.tx) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as arb_fee_per_tx_ma, -- avax avg(cal.avax_user_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as avax_user_ma, avg(cal.avax_tx_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as avax_tx_ma, avg(cal.avax_fee_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as avax_fee_ma, avax.tx as avax_tx, avax.user as avax_user, avax.fee as av_fee, avax.price as avax_price, avax.fee_usd as avax_fee_usd, avg(avax.tx/avax.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as avax_tx_per_user_ma, avg(avax.fee_usd/avax.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as avax_fee_per_user_ma, avg(avax.fee_usd/avax.tx) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as avax_fee_per_tx_ma, -- bsc avg(cal.bsc_user_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as bsc_user_ma, avg(cal.bsc_tx_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as bsc_tx_ma, avg(cal.bsc_fee_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as bsc_fee_ma, bsc.tx as bsc_tx, bsc.user as bsc_user, bsc.fee as bsc_fee, bsc.price as bsc_price, bsc.fee_usd as bsc_fee_usd, avg(bsc.tx/bsc.user ) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as bsc_tx_per_user_ma, avg(bsc.fee_usd/bsc.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as bsc_fee_per_user_ma, avg(bsc.fee_usd/bsc.tx) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as bsc_fee_per_tx_ma, -- axelar avg(cal.axelar_user_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as axelar_user_ma, avg(cal.axelar_tx_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as axelar_tx_ma, axelar.tx as axelar_tx, axelar.user as axelar_user, avg(axelar.tx/axelar.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as flow_tx_per_user_ma, -- flow avg(cal.flow_user_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as flow_user_ma, avg(cal.flow_tx_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as flow_tx_ma, flow.tx as flow_tx, flow.user as flow_user, avg(flow.tx/flow.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as flow_tx_per_user_ma, -- gnosis avg(cal.gnosis_user_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as gnosis_user_ma, avg(cal.gnosis_tx_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as gnosis_tx_ma, avg(cal.gnosis_fee_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as gnosis_fee_ma, gnosis.tx as gnosis_tx, gnosis.user as gnosis_user, gnosis.fee as gnosis_fee, gnosis.price as gnosis_price, gnosis.fee_usd as gnosis_fee_usd, avg(gnosis.tx/gnosis.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as gnosis_tx_per_user_ma, avg(gnosis.fee_usd/gnosis.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as gnosis_fee_per_user_ma, avg(gnosis.fee_usd/gnosis.tx) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as gnosis_fee_per_tx_ma, -- near avg(cal.near_user_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as near_user_ma, avg(cal.near_tx_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as near_tx_ma, avg(cal.near_fee_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as near_fee_ma, near.tx as near_tx, near.user as near_user, near.fee as near_fee, near.price as near_price, near.fee_usd as near_fee_usd, avg(near.tx/near.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as near_tx_per_user_ma, avg(near.fee_usd/near.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as near_fee_per_user_ma, avg(near.fee_usd/near.tx) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as near_fee_per_tx_ma, -- op avg(cal.op_user_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as op_user_ma, avg(cal.op_tx_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as op_tx_ma, avg(cal.op_fee_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as op_fee_ma, op.tx as op_tx, op.user as op_user, op.fee as op_fee, op.price as op_price, op.fee_usd as op_fee_usd, avg(op.tx/op.user ) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as op_tx_per_user_ma, avg(op.fee_usd/op.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as op_fee_per_user_ma, avg(op.fee_usd/op.tx) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as op_fee_per_tx_ma, -- osmos avg(cal.osmos_user_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as osmos_user_ma, avg(cal.osmos_tx_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as osmos_tx_ma, avg(cal.osmos_fee_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as osmos_fee_ma, osmos.tx as osmos_tx, osmos.user as osmos_user, osmos.fee1 as osmos_fee, osmos.price as osmos_price, osmos.fee_usd as osmos_fee_usd, avg(osmos.tx/osmos.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as osmos_tx_per_user_ma, avg(osmos.fee_usd/osmos.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as osmos_fee_per_user_ma, avg(osmos.fee_usd/osmos.tx) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as osmos_fee_per_tx_ma, -- polygon avg(cal.polygon_user_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as polygon_user_ma, avg(cal.polygon_tx_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as polygon_tx_ma, avg(cal.polygon_fee_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as polygon_fee_ma, polygon.tx as polygon_tx, polygon.user as polygon_user, polygon.fee as polygon_fee, polygon.price as polygon_price, polygon.fee_usd as polygon_fee_usd, avg(polygon.tx/polygon.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as polygon_tx_per_user_ma, avg(polygon.fee_usd/polygon.user) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as polygon_fee_per_user_ma, avg(polygon.fee_usd/polygon.tx) over(ORDER BY eth.date ROWS BETWEEN 9 PRECEDING AND CURRENT ROW) as polygon_fee_per_tx_ma, -- stark avg(cal.stark_tx_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as stark_tx_ma, stark.tx as stark_tx -- sol -- avg(cal.sol_user_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as sol_user_ma, -- avg(cal.sol_tx_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as sol_tx_ma, -- avg(cal.sol_fee_pct) over(ORDER BY eth.date ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)as sol_fee_ma, -- sol.tx as sol_tx, sol.user as sol_user, sol.fee1 as sol_fee, sol.price as sol_price, sol.fee_usd as sol_fee_usd FROM eth left join cal on eth.date = cal.date left join arb on eth.date = arb.date left join avax on eth.date = avax.date left join bsc on eth.date = bsc.date left join axelar on eth.date = axelar.date left join flow on eth.date = flow.date left join gnosis on eth.date = gnosis.date left join near on eth.date = near.date left join op on eth.date = op.date left join osmos on eth.date = osmos.date left join polygon on eth.date = polygon.date left join stark on eth.date = stark.date -- left join sol on eth.date = sol.date

Query	Creator	Created
Velodrome's lock durations optimism l2 evm	xcheng123	Feb 2, 2023
galex bsc arbitrum ethereum optimism avalanche	xcheng123	Dec 20, 2022
gohome gnosis flow axelar near bsc	xcheng123	Nov 28, 2022
optimism hot contract optimism l2 evm	xcheng123	Nov 14, 2022

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