tokens by volume

h4wktokens by volume

Updated 6 days ago

-- forked from top 10 token by volume @ https://flipsidecrypto.xyz/studio/queries/8ea13bfb-189a-441b-af3f-1e22b76178e6

-- forked from total @ https://flipsidecrypto.xyz/studio/queries/b3ea3c98-fc79-4c60-a18d-816fe5a0e26d

-- forked from base @ https://flipsidecrypto.xyz/studio/queries/b3c76ba9-e256-42ee-af38-467881c899e8

with bonk_price as (

select hour,

symbol,

token_address,

price

from solana.price.ez_prices_hourly

where token_address = 'DezXAZ8z7PnrnRJjz3wXBoRgixCa6xjnB7YaB1pPB263'

)

, base as (

select a.block_timestamp,

a.tx_id,

swapper as user_address,

swap_from_mint,

swap_from_amount,

case when c.symbol is null then 'Unknown' else c.symbol end as swap_from_symbol,

swap_to_amount as bonk_amount,

swap_to_amount * price as volume_bonk_usd,

amount * 3 as fee_amount, -- Fees split into 3 addresses equally, so we just multiply by 3

amount * 3 * price as fee_amount_usd,

0.00203928 as rent_returned

from solana.defi.fact_swaps_jupiter_summary a

join bonk_price on (date_trunc('hour', a.block_timestamp) = hour)

join (select * from solana.core.fact_transfers

where tx_to = 'CbX9HYvyHBa2RuotGN8Y8hCKow6xppdrhAh6RL6i2BEf' -- Fee collected address (one of the three)

and mint = 'DezXAZ8z7PnrnRJjz3wXBoRgixCa6xjnB7YaB1pPB263'

and block_timestamp >= '2024-01-12') b on (swapper = tx_from and a.tx_id = b.tx_id)

left join solana.price.ez_asset_metadata c on (swap_from_mint = c.token_address)

where swap_to_mint = 'DezXAZ8z7PnrnRJjz3wXBoRgixCa6xjnB7YaB1pPB263'

and a.block_timestamp >= '2024-01-12'

-- order by block_timestamp desc limit 10

Last run: 6 days ago

	SWAP_FROM_SYMBOL	SWAP_FROM_MINT	TX_COUNT	USER_COUNT	BONK_SCOOP_USD
1	WIF	EKpQGSJtjMFqKZ9KQanSqYXRcF8fBopzLHYxdM65zcjm	459	383	241745.91
2	JUP	JUPyiwrYJFskUPiHa7hkeR8VUtAeFoSYbKedZNsDvCN	843	760	37876.75
3	BOZO	BoZoQQRAmYkr5iJhqo7DChAs7DPDwEZ5cv1vkYC9yzJG	1085	1046	29446.65
4	SNS	SNSNkV9zfG5ZKWQs6x4hxvBRV6s8SqMfSGCtECDvdMd	27	26	27795.71
5	MEW	MEW1gQWJ3nEXg2qgERiKu7FAFj79PHvQVREQUzScPP5	388	355	25831.26
6	MUMU	5LafQUrVco6o7KMz42eqVEJ9LW31StPyGjeeu5sKoMtA	419	375	25495.95
7	BERN	CKfatsPMUf8SkiURsDXs7eK6GWb4Jsd6UDbs7twMCWxo	1096	1058	23029.42
8	$WEN	WENWENvqqNya429ubCdR81ZmD69brwQaaBYY6p3LCpk	1022	924	20514.67
9	SHDW	SHDWyBxihqiCj6YekG2GUr7wqKLeLAMK1gHZck9pL6y	390	371	19680.62
10	PAJAMAS	FvER7SsvY5GqAMawf7Qfb5MnUUmDdbPNPg4nCa4zHoLw	14	13	14321.67
11	DRAKO	drakduQWnTS89CdTUdgHmZzEkN6reBLYqrk8rzVhU53	1064	1029	14189.11
12	TNSR	TNSRxcUxoT9xBG3de7PiJyTDYu7kskLqcpddxnEJAS6	84	81	13302.04
13	ACS	5MAYDfq5yxtudAhtfyuMBuHZjgAbaS9tbEyEQYAhDS5y	296	209	12739.93
14	MUZKI	C1kzNkFfgdtP8VF1pFYA4S32RLPqk5KPaurCaQJwxfWb	15	10	12522.51
15	$CWIF	7atgF8KQo4wJrD5ATGX7t1V2zVvykPJbFfNeVf1icFv1	4234	3614	12467.84
16	CHONKY	H7ed7UgcLp3ax4X1CQ5WuWDn6d1pprfMMYiv5ejwLWWU	444	416	10348.11
17	GECKO	6CNHDCzD5RkvBWxxyokQQNQPjFWgoHF94D7BmC73X6ZK	427	394	9481.7
18	JTO	jtojtomepa8beP8AuQc6eXt5FriJwfFMwQx2v2f9mCL	499	410	9437.33
19	RAY	4k3Dyjzvzp8eMZWUXbBCjEvwSkkk59S5iCNLY3QrkX6R	465	416	9144.79
20	STAN	CQSzJzwW5H1oyWrp6QhfUKYYwyovbSiVDKnAxNfb1tJC	42	39	8911.14

...

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