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Add Table Generation Query for Website Dashboard #1744

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3fbf897
add
MSilb7 Sep 8, 2025
48ac8b1
mod
MSilb7 Sep 9, 2025
daeea4a
Merge branch 'main' into website-query-q325
MSilb7 Sep 9, 2025
d89b2ce
add eth eco flag
MSilb7 Sep 16, 2025
967c307
Merge branch 'main' into website-query-q325
MSilb7 Oct 2, 2025
0654191
push tiles_share
MSilb7 Oct 2, 2025
f6bde9f
mod month
MSilb7 Oct 2, 2025
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330 changes: 330 additions & 0 deletions src/op_analytics/transforms/website_dashboard/generate_tables.sql
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BEGIN
CREATE TEMP TABLE base AS

WITH monthly_chain_activity AS (
SELECT
DATE_TRUNC(dt,MONTH) AS dt_month, chain_key, display_name,
-- attributes
layer, alignment, provider_entity_w_superchain, is_evm, gas_token, da_layer, output_root_layer, l2b_stage
-- value metrics
, MAX_BY(app_tvl_usd,dt) AS latest_app_tvl_usd
, MAX_BY(stables_onchain_usd,dt) AS latest_stables_onchain_usd
, MAX_BY(onchain_value_usd,dt) AS latest_onchain_value_usd
-- activity metrics
, SUM(txs_per_day) as sum_txs
, SUM(total_rev_fees_eth) AS sum_total_rev_txn_fees_eth
, SUM(total_rev_fees_usd) AS sum_total_rev_txn_fees_usd
, SUM(total_dex_volume_usd) as sum_total_dex_volume_usd
-- developers
, MAX_BY(distinct_parent_protocol,dt) AS latest_distinct_parent_protocol
-- -- UX
-- , SUM(median_l2_usd_fees_per_tx*txs_per_day)/SUM(txs_per_day) AS wt_avg_median_l2_usd_fees_per_tx
FROM `oplabs-tools-data.materialized_tables.daily_superchain_health_mv`
WHERE dt >= '2021-01-01'
AND dt < DATE_TRUNC(CURRENT_DATE(),MONTH)
AND layer = 'L2' -- L2s Only
AND eth_eco_l2 -- Ethereum Ecosystem Only (e.g., no known BNB L2s)
GROUP BY 1,2,3,4,5,6,7,8,9,10,11
)
, days_per_mo AS (
SELECT DATE_TRUNC(dt,MONTH) AS dt_month, COUNT(DISTINCT dt) AS unique_dt
FROM `oplabs-tools-data.materialized_tables.daily_superchain_health_mv`
GROUP BY 1
)
, monthly_revshare AS (
SELECT
dt_month, display_name, 'L2' AS layer, 'OP Chain' as alignment
-- revenue
, revshare_estimated AS sum_revshare_estimated_eth
, revshare_estimated_usd AS sum_revshare_estimated_usd
, actual_collective_contribution AS sum_revshare_actual_eth
, actual_collective_contribution_usd AS sum_revshare_actual_usd
, actual_collective_contribution_rec AS sum_actual_collective_contribution_received_eth
, actual_collective_contribution_rec_usd AS sum_actual_collective_contribution_received_usd
FROM `oplabs-tools-data.materialized_tables.monthly_opcollective_revshare_mv`
WHERE 1=1
AND (
(is_flagged IS NULL AND prior_flag IS NULL)
OR
display_name LIKE 'RaaS -%'
)
AND chart_name != 'Unmapped'
AND is_flagged IS NULL
AND alignment = 'OP Chain'
AND dt_month >= '2021-01-01'
AND dt_month < DATE_TRUNC(CURRENT_DATE(),MONTH)
)
, monthly_chain_level AS (
SELECT
COALESCE(a.dt_month,r.dt_month) AS dt_month
, COALESCE(a.display_name, r.display_name) AS display_name
, COALESCE(a.chain_key,lower(coalesce(a.display_name,r.display_name))) AS chain_key
, COALESCE(a.layer, r.layer) AS layer
, COALESCE(a.alignment, r.alignment) AS alignment
, CASE WHEN r.display_name IS NOT NULL THEN 'Optimism: Superchain'
ELSE a.provider_entity_w_superchain
END AS provider_entity_w_superchain
, a.* EXCEPT(dt_month, display_name, layer, alignment,chain_key, provider_entity_w_superchain)
, r.* EXCEPT(dt_month, display_name, layer, alignment)
, d.unique_dt
FROM monthly_chain_activity a
LEFT JOIN days_per_mo d
ON a.dt_month = d.dt_month
FULL OUTER JOIN monthly_revshare r
ON a.dt_month = r.dt_month
AND a.display_name = r.display_name
)
,pre_aggregate_groups AS (
SELECT *, COALESCE(
CASE WHEN provider_entity_w_superchain IN ('Optimism: Superchain','Polygon: CDK', 'Arbitrum: Orbit', 'zkSync: ZK Stack') THEN provider_entity_w_superchain
ELSE NULL
END
, 'Other') AS agg_display_name
FROM monthly_chain_level
)
, aggregates AS (
SELECT dt_month, agg_display_name, display_name,
SUM(latest_app_tvl_usd) AS latest_app_tvl_usd,
SUM(latest_stables_onchain_usd) AS latest_stables_onchain_usd,
SUM(latest_onchain_value_usd) AS latest_onchain_value_usd,
SUM(sum_txs) AS sum_txs,
SUM(sum_txs/unique_dt) AS sum_txs_per_day,
SUM(sum_txs/(unique_dt*(60*60*24))) AS sum_txs_per_sec,
SUM(sum_total_dex_volume_usd) AS sum_dex_volume_usd,
SUM(sum_total_dex_volume_usd/unique_dt) AS sum_dex_volume_usd_per_day,
SUM(sum_total_rev_txn_fees_eth) AS sum_total_rev_txn_fees_eth,
SUM(sum_total_rev_txn_fees_eth/unique_dt) AS sum_total_rev_txn_fees_eth_per_day,
SUM(sum_total_rev_txn_fees_usd) AS sum_total_rev_txn_fees_usd,
SUM(sum_total_rev_txn_fees_usd/unique_dt) AS sum_total_rev_txn_fees_usd_per_day,
SUM(sum_revshare_estimated_eth) AS sum_revshare_estimated_eth,
SUM(sum_revshare_estimated_eth/unique_dt) AS sum_revshare_estimated_eth_per_day,
SUM(sum_revshare_estimated_usd) AS sum_revshare_estimated_usd,
SUM(sum_revshare_estimated_usd/unique_dt) AS sum_revshare_estimated_usd_per_day,
SUM(sum_revshare_actual_eth) AS sum_revshare_actual_eth,
SUM(sum_revshare_actual_eth/unique_dt) AS sum_revshare_actual_eth_per_day,
SUM(sum_revshare_actual_usd) AS sum_revshare_actual_usd,
SUM(sum_revshare_actual_usd/unique_dt) AS sum_revshare_actual_usd_per_day
-- SUM(wt_avg_median_l2_usd_fees_per_tx*sum_txs)/SUM(sum_txs) AS wt_avg_median_l2_usd_fees_per_tx

FROM pre_aggregate_groups
GROUP BY 1,2,3
)
SELECT *
, dense_rank() over (order by dt_month DESC) AS month_recency_rank
FROM aggregates
ORDER BY dt_month DESC;
CREATE TEMP TABLE chain_measurements AS
WITH cte AS (
SELECT
display_name,
SUM(IFNULL(sum_revshare_estimated_eth, 0)) AS estimated_eth,
SUM(IFNULL(sum_revshare_actual_eth, 0)) AS actual_eth
FROM base
WHERE agg_display_name = 'Optimism: Superchain'
GROUP BY 1
)
SELECT
display_name,
STRUCT(
estimated_eth,
actual_eth
) AS all_time_revshare
FROM cte
;
CREATE TEMP TABLE rainbow_figure AS
WITH cte AS (
SELECT
dt_month,
agg_display_name,
SUM(sum_total_rev_txn_fees_usd) AS sum_total_rev_txn_fees_usd,
SUM(sum_txs_per_day) AS sum_txs_per_day
FROM base
GROUP BY 1, 2
)
SELECT
agg_display_name,
ARRAY_AGG(
STRUCT(dt_month, sum_total_rev_txn_fees_usd AS txn_fees_usd, sum_txs_per_day AS txs_per_day)
ORDER BY dt_month DESC
) AS timeline
FROM cte
WHERE dt_month > '2024-06-01'
GROUP BY 1;
CREATE TEMP TABLE tiles AS
WITH tot_superchain AS (
SELECT
dt_month,
SUM(IFNULL(sum_txs, 0)) AS sum_txs,
SUM(IFNULL(sum_txs_per_day, 0)) AS sum_txs_per_day,
SUM(IFNULL(sum_total_rev_txn_fees_usd, 0)) AS sum_total_rev_txn_fees_usd,
SUM(IFNULL(sum_total_rev_txn_fees_eth, 0)) AS sum_total_rev_txn_fees_eth,
SUM(IFNULL(sum_total_rev_txn_fees_usd_per_day, 0)) AS sum_total_rev_txn_fees_usd_per_day,
SUM(IFNULL(sum_total_rev_txn_fees_eth_per_day, 0)) AS sum_total_rev_txn_fees_eth_per_day,
SUM(IFNULL(sum_dex_volume_usd_per_day, 0)) AS sum_dex_volume_usd_per_day,
SUM(IFNULL(latest_app_tvl_usd, 0)) AS latest_app_tvl_usd,
SUM(IFNULL(latest_onchain_value_usd, 0)) AS latest_onchain_value_usd,
SUM(IFNULL(latest_stables_onchain_usd, 0)) AS latest_stables_onchain_usd,
SUM(IFNULL(sum_revshare_estimated_eth, 0)) AS sum_revshare_estimated_eth,
SUM(IFNULL(sum_revshare_estimated_usd, 0)) AS sum_revshare_estimated_usd,
SUM(IFNULL(sum_revshare_actual_eth, 0)) AS sum_revshare_actual_eth,
SUM(IFNULL(sum_revshare_actual_usd, 0)) AS sum_revshare_actual_usd,
FROM base
WHERE agg_display_name = 'Optimism: Superchain'
GROUP BY 1
),
tot_eco AS (
SELECT
dt_month,
SUM(IFNULL(sum_txs, 0)) AS sum_txs,
SUM(IFNULL(sum_total_rev_txn_fees_usd, 0)) AS sum_total_rev_txn_fees_usd,
FROM base
GROUP BY 1
),
cte AS (
SELECT
dt_month,
SAFE_DIVIDE(ts.sum_total_rev_txn_fees_usd, te.sum_total_rev_txn_fees_usd) AS ecosystem_pct_of_l2_rev_fees_usd,
SAFE_DIVIDE(ts.sum_total_rev_txn_fees_usd, te.sum_total_rev_txn_fees_usd)
- LAG(SAFE_DIVIDE(ts.sum_total_rev_txn_fees_usd, te.sum_total_rev_txn_fees_usd), 1) OVER w AS mom_ecosystem_pct_of_l2_rev_fees_usd,
SAFE_DIVIDE(ts.sum_txs, te.sum_txs) AS ecosystem_pct_of_l2_txs,
SAFE_DIVIDE(ts.sum_txs, te.sum_txs) - LAG(SAFE_DIVIDE(ts.sum_txs, te.sum_txs), 1) OVER w AS mom_ecosystem_pct_of_l2_txs,
ts.sum_total_rev_txn_fees_usd_per_day,
ts.sum_total_rev_txn_fees_eth_per_day,
SAFE_DIVIDE(
ts.sum_total_rev_txn_fees_usd_per_day - LAG(ts.sum_total_rev_txn_fees_usd_per_day, 1) OVER w,
LAG(ts.sum_total_rev_txn_fees_usd_per_day, 1) OVER w
) AS mom_sum_total_rev_txn_fees_usd_per_day,
SAFE_DIVIDE(
ts.sum_total_rev_txn_fees_eth_per_day - LAG(ts.sum_total_rev_txn_fees_eth_per_day, 1) OVER w,
LAG(ts.sum_total_rev_txn_fees_eth_per_day, 1) OVER w
) AS mom_sum_total_rev_txn_fees_eth_per_day,
ts.sum_dex_volume_usd_per_day,
SAFE_DIVIDE(
ts.sum_dex_volume_usd_per_day - LAG(ts.sum_dex_volume_usd_per_day, 1) OVER w,
LAG(ts.sum_dex_volume_usd_per_day, 1) OVER w
) AS mom_sum_dex_volume_usd_per_day,
ts.sum_txs_per_day,
SAFE_DIVIDE(
ts.sum_txs_per_day - LAG(ts.sum_txs_per_day, 1) OVER w,
LAG(ts.sum_txs_per_day, 1) OVER w
) AS mom_sum_txs_per_day,
ts.latest_app_tvl_usd,
SAFE_DIVIDE(
ts.latest_app_tvl_usd - LAG(ts.latest_app_tvl_usd, 1) OVER w,
LAG(ts.latest_app_tvl_usd, 1) OVER w
) AS mom_latest_app_tvl_usd,
ts.latest_onchain_value_usd,
SAFE_DIVIDE(
ts.latest_onchain_value_usd - LAG(ts.latest_onchain_value_usd, 1) OVER w,
LAG(ts.latest_onchain_value_usd, 1) OVER w
) AS mom_latest_onchain_value_usd,
ts.latest_stables_onchain_usd,
SAFE_DIVIDE(
ts.latest_stables_onchain_usd - LAG(ts.latest_stables_onchain_usd, 1) OVER w,
LAG(ts.latest_stables_onchain_usd, 1) OVER w
) AS mom_latest_stables_onchain_usd,
SUM(sum_revshare_estimated_eth) OVER w AS all_time_sum_revshare_estimated_eth,
SUM(sum_revshare_estimated_usd) OVER w AS all_time_sum_revshare_estimated_usd,
SUM(sum_revshare_actual_eth) OVER w AS all_time_sum_revshare_actual_eth,
SUM(sum_revshare_actual_usd) OVER w AS all_time_sum_revshare_actual_usd,
FROM tot_superchain ts
INNER JOIN tot_eco te USING(dt_month)
WINDOW w AS (ORDER BY dt_month ASC)
ORDER BY dt_month DESC
)
SELECT
STRUCT(
ecosystem_pct_of_l2_rev_fees_usd AS pct_of_l2_rev_fees_usd,
mom_ecosystem_pct_of_l2_rev_fees_usd AS mom_pct_of_l2_rev_fees_usd,
ecosystem_pct_of_l2_txs AS pct_of_l2_txs,
mom_ecosystem_pct_of_l2_txs AS mom_pct_of_l2_txs
) AS ecosystem,
STRUCT(
sum_total_rev_txn_fees_usd_per_day AS total_usd_per_day,
sum_total_rev_txn_fees_eth_per_day AS total_eth_per_day,
mom_sum_total_rev_txn_fees_usd_per_day AS mom_usd_per_day,
mom_sum_total_rev_txn_fees_eth_per_day AS mom_eth_per_day
) AS txn_fees,
STRUCT(
sum_txs_per_day AS per_day,
mom_sum_txs_per_day AS mom_per_day
) AS txs,
STRUCT(
sum_dex_volume_usd_per_day AS usd_per_day,
mom_sum_dex_volume_usd_per_day AS mom_usd_per_day
) AS dex_volume,
STRUCT(
latest_app_tvl_usd AS app_usd,
mom_latest_app_tvl_usd AS mom_app_usd
) AS tvl,
STRUCT(
latest_onchain_value_usd AS onchain_usd,
mom_latest_onchain_value_usd AS mom_onchain_usd
) AS aop,
STRUCT(
latest_stables_onchain_usd AS onchain_usd,
mom_latest_stables_onchain_usd AS mom_onchain_usd
) AS stables,
STRUCT(
all_time_sum_revshare_estimated_eth AS revshare_estimated_eth,
all_time_sum_revshare_estimated_usd AS revshare_estimated_usd,
all_time_sum_revshare_actual_eth AS revshare_actual_eth,
all_time_sum_revshare_actual_usd AS revshare_actual_usd
) AS all_time_revenue
FROM cte
WHERE dt_month > '2024-06-01'
QUALIFY ROW_NUMBER() OVER(ORDER BY dt_month DESC) = 1
;
CREATE TEMP TABLE tiles_share AS
WITH grouped AS (
SELECT
dt_month,
agg_display_name,
SUM(IFNULL(sum_txs_per_day, 0)) AS sum_txs_per_day,
SUM(IFNULL(sum_total_rev_txn_fees_usd_per_day, 0)) AS sum_total_rev_txn_fees_usd_per_day,
SUM(IFNULL(sum_total_rev_txn_fees_eth_per_day, 0)) AS sum_total_rev_txn_fees_eth_per_day,
SUM(IFNULL(sum_dex_volume_usd_per_day, 0)) AS sum_dex_volume_usd_per_day,
SUM(IFNULL(latest_app_tvl_usd, 0)) AS latest_app_tvl_usd,
SUM(IFNULL(latest_onchain_value_usd, 0)) AS latest_onchain_value_usd,
SUM(IFNULL(latest_stables_onchain_usd, 0)) AS latest_stables_onchain_usd
FROM base
GROUP BY 1, 2
),
totals AS (
SELECT
dt_month,
SUM(sum_txs_per_day) AS tot_sum_txs_per_day,
SUM(sum_total_rev_txn_fees_usd_per_day) AS tot_sum_total_rev_txn_fees_usd_per_day,
SUM(sum_total_rev_txn_fees_eth_per_day) AS tot_sum_total_rev_txn_fees_eth_per_day,
SUM(sum_dex_volume_usd_per_day) AS tot_sum_dex_volume_usd_per_day,
SUM(latest_app_tvl_usd) AS tot_latest_app_tvl_usd,
SUM(latest_onchain_value_usd) AS tot_latest_onchain_value_usd,
SUM(latest_stables_onchain_usd) AS tot_latest_stables_onchain_usd
FROM grouped
GROUP BY 1
)
SELECT
agg_display_name,
ARRAY_AGG(
STRUCT(
g.dt_month,
-- g.sum_txs_per_day AS txs_per_day,
SAFE_DIVIDE(g.sum_txs_per_day, t.tot_sum_txs_per_day) AS txs_per_day_share,
-- g.sum_total_rev_txn_fees_usd_per_day AS txn_fees_usd_per_day,
SAFE_DIVIDE(g.sum_total_rev_txn_fees_usd_per_day, t.tot_sum_total_rev_txn_fees_usd_per_day) AS txn_fees_usd_per_day_share,
-- g.sum_dex_volume_usd_per_day AS dex_volume_usd_per_day,
SAFE_DIVIDE(g.sum_dex_volume_usd_per_day, t.tot_sum_dex_volume_usd_per_day) AS dex_volume_usd_per_day_share,
-- g.latest_app_tvl_usd AS app_tvl_usd,
SAFE_DIVIDE(g.latest_app_tvl_usd, t.tot_latest_app_tvl_usd) AS app_tvl_usd_share,
-- g.latest_onchain_value_usd AS onchain_value_usd,
SAFE_DIVIDE(g.latest_onchain_value_usd, t.tot_latest_onchain_value_usd) AS onchain_value_usd_share,
-- g.latest_stables_onchain_usd AS stables_onchain_usd,
SAFE_DIVIDE(g.latest_stables_onchain_usd, t.tot_latest_stables_onchain_usd) AS stables_onchain_usd_share
)
ORDER BY g.dt_month DESC
) AS popout
FROM grouped g
JOIN totals t USING (dt_month)
WHERE g.dt_month >= '2021-01-01'
GROUP BY 1;
END