add athena query for recent fill premium/discounts
This commit is contained in:
wphan
280
src/athena/repositories/fillQualityAnalytics.ts
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280
src/athena/repositories/fillQualityAnalytics.ts
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import { Athena } from '../client';
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export interface TakerFillVsOracleBpsResult {
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Time: string;
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MarketIndex: string;
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TakerBuyBpsFromOracle_ALL: string | null;
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TakerSellBpsFromOracle_ALL: string | null;
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TakerBuyBpsFromOracle_1e0: string | null;
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TakerBuyBpsFromOracle_1e3: string | null;
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TakerBuyBpsFromOracle_1e4: string | null;
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TakerBuyBpsFromOracle_1e5: string | null;
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TakerBuyBpsFromOracle_1e6: string | null;
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TakerSellBpsFromOracle_1e0: string | null;
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TakerSellBpsFromOracle_1e3: string | null;
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TakerSellBpsFromOracle_1e4: string | null;
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TakerSellBpsFromOracle_1e5: string | null;
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TakerSellBpsFromOracle_1e6: string | null;
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Zero: string;
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}
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export const FillQualityAnalyticsRepository = () => {
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const { query } = Athena();
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/**
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* Get taker fill vs oracle basis points, bucketed by order notional cohorts at place-time size.
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* Returns a rolling average per cohort/direction, partitioned by market.
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* This query returns data for ALL perp markets in a single result set.
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*
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* @param from - Unix timestamp in milliseconds
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* @param to - Unix timestamp in milliseconds
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* @param baseDecimals - Base decimals for the market (default: 9)
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* @param smoothingMinutes - Minutes for rolling average (default: 60)
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* @returns Array of time series data with taker fill vs oracle bps by cohort and market
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*/
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const getTakerFillVsOracleBps = async (
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fromMs: number,
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toMs: number,
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baseDecimals: number = 9,
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smoothingMinutes: number = 60
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): Promise<TakerFillVsOracleBpsResult[]> => {
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// Taker fill vs Oracle bps, bucketed by order notional cohorts at place-time size
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// Final output: latest non-null rolling average per cohort/direction, PARTITIONED BY market
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const queryString = `
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WITH
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from_dt AS (
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SELECT
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date_format(from_unixtime(CAST(${fromMs}/1000 AS BIGINT)) AT TIME ZONE 'UTC','%Y') AS yf,
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date_format(from_unixtime(CAST(${fromMs}/1000 AS BIGINT)) AT TIME ZONE 'UTC','%m') AS mf,
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date_format(from_unixtime(CAST(${fromMs}/1000 AS BIGINT)) AT TIME ZONE 'UTC','%d') AS df
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),
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to_dt AS (
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SELECT
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date_format(from_unixtime(CAST(${toMs}/1000 AS BIGINT)) AT TIME ZONE 'UTC','%Y') AS yt,
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date_format(from_unixtime(CAST(${toMs}/1000 AS BIGINT)) AT TIME ZONE 'UTC','%m') AS mt,
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date_format(from_unixtime(CAST(${toMs}/1000 AS BIGINT)) AT TIME ZONE 'UTC','%d') AS dt
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),
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-- Dedup to the earliest OrderRecord per (txsig,user,orderid,marketindex) to reflect "place" state
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orders_dedup AS (
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SELECT *
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FROM (
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SELECT
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CAST(orx.ts AS BIGINT) AS order_ts_epoch,
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orx.txsig AS txsig,
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orx.user AS user,
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orx."order".orderid AS orderid,
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orx."order".marketindex AS marketindex,
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CAST(orx."order".baseassetamount AS DOUBLE) AS base_asset_amount_raw,
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ROW_NUMBER() OVER (
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PARTITION BY orx.txsig, orx.user, orx."order".orderid, orx."order".marketindex
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ORDER BY CAST(orx.ts AS BIGINT) ASC
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) AS rn
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FROM eventtype_orderrecord orx
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CROSS JOIN from_dt f
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CROSS JOIN to_dt t
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WHERE
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orx."order".markettype = 'perp'
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-- UTC-safe pruning on VARCHAR partitions
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AND orx.year BETWEEN f.yf AND t.yt
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AND (
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orx.year > f.yf
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OR (orx.year = f.yf AND orx.month > f.mf)
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OR (orx.year = f.yf AND orx.month = f.mf AND orx.day >= f.df)
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)
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AND (
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orx.year < t.yt
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OR (orx.year = t.yt AND orx.month < t.mt)
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OR (orx.year = t.yt AND orx.month = t.mt AND orx.day <= t.dt)
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)
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-- absolute time guardrails (ts is epoch seconds in table)
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AND CAST(orx.ts AS BIGINT) BETWEEN CAST(${fromMs}/1000 AS BIGINT) AND CAST(${toMs}/1000 AS BIGINT)
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) t1
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WHERE rn = 1
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),
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-- Trade fills (taker perspective) within the window (all markets)
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trades AS (
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SELECT
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CAST(tr.ts AS BIGINT) AS ts_epoch,
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tr.txsig AS txsig,
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tr.taker AS user,
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tr.takerorderid AS orderid,
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tr.marketindex AS marketindex,
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LOWER(tr.takerorderdirection) AS dir,
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CAST(tr.quoteassetamountfilled AS DOUBLE) AS q_filled,
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CAST(tr.baseassetamountfilled AS DOUBLE) AS b_filled,
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CAST(tr.oracleprice AS DOUBLE) AS oracle_raw
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FROM eventtype_traderecord tr
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CROSS JOIN from_dt f
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CROSS JOIN to_dt t
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WHERE
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LOWER(tr.action) = 'fill'
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AND tr.markettype = 'perp'
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AND LOWER(tr.takerorderdirection) IN ('long','short')
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-- UTC-safe pruning on VARCHAR partitions
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AND tr.year BETWEEN f.yf AND t.yt
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AND (
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tr.year > f.yf
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OR (tr.year = f.yf AND tr.month > f.mf)
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OR (tr.year = f.yf AND tr.month = f.mf AND tr.day >= f.df)
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)
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AND (
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tr.year < t.yt
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OR (tr.year = t.yt AND tr.month < t.mt)
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OR (tr.year = t.yt AND tr.month = t.mt AND tr.day <= t.dt)
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)
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-- absolute time guardrails (ts is epoch seconds in table)
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AND CAST(tr.ts AS BIGINT) BETWEEN CAST(${fromMs}/1000 AS BIGINT) AND CAST(${toMs}/1000 AS BIGINT)
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),
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-- Join fills to the order's initial size; compute notional cohort and taker bps from oracle
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joined AS (
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SELECT
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from_unixtime(tr.ts_epoch) AS Time,
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tr.marketindex AS MarketIndex,
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tr.dir AS dir,
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(
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(
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(tr.q_filled / NULLIF(tr.b_filled, 0))
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* pow(10.0, (${baseDecimals} - 6))
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)
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/ (tr.oracle_raw / 1e6) - 1.0
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) * 10000.0 AS taker_bps_from_oracle,
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( (od.base_asset_amount_raw * 1e-9) * (tr.oracle_raw * 1e-6) ) AS order_value
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FROM trades tr
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JOIN orders_dedup od
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ON od.txsig = tr.txsig
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AND od.user = tr.user
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AND od.orderid = tr.orderid
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AND od.marketindex = tr.marketindex
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),
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-- Bucket into cohorts
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bucketed AS (
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SELECT
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Time,
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MarketIndex,
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dir,
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taker_bps_from_oracle,
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CASE
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WHEN order_value > 0 AND order_value < 1000 THEN '1e0'
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WHEN order_value >= 1000 AND order_value < 10000 THEN '1e3'
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WHEN order_value >= 10000 AND order_value < 100000 THEN '1e4'
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WHEN order_value >= 100000 AND order_value < 1000000 THEN '1e5'
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WHEN order_value >= 1000000 THEN '1e6'
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ELSE 'other'
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END AS cohort
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FROM joined
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),
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-- Compute rolling averages
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rolling_avgs AS (
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SELECT
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Time,
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MarketIndex,
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-- Non-cohort series (ALL fills regardless of cohort)
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AVG(CASE WHEN dir = 'long' THEN taker_bps_from_oracle END)
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OVER (PARTITION BY MarketIndex ORDER BY Time RANGE BETWEEN INTERVAL '${smoothingMinutes}' MINUTE PRECEDING AND CURRENT ROW)
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AS "TakerBuyBpsFromOracle_ALL",
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AVG(CASE WHEN dir = 'short' THEN taker_bps_from_oracle END)
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OVER (PARTITION BY MarketIndex ORDER BY Time RANGE BETWEEN INTERVAL '${smoothingMinutes}' MINUTE PRECEDING AND CURRENT ROW)
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AS "TakerSellBpsFromOracle_ALL",
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-- rolling average by cohort/direction (NULLs ignored by AVG)
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AVG(CASE WHEN dir = 'long' AND cohort = '1e0' THEN taker_bps_from_oracle END)
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OVER (PARTITION BY MarketIndex ORDER BY Time RANGE BETWEEN INTERVAL '${smoothingMinutes}' MINUTE PRECEDING AND CURRENT ROW)
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AS "TakerBuyBpsFromOracle_1e0",
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AVG(CASE WHEN dir = 'long' AND cohort = '1e3' THEN taker_bps_from_oracle END)
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OVER (PARTITION BY MarketIndex ORDER BY Time RANGE BETWEEN INTERVAL '${smoothingMinutes}' MINUTE PRECEDING AND CURRENT ROW)
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AS "TakerBuyBpsFromOracle_1e3",
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AVG(CASE WHEN dir = 'long' AND cohort = '1e4' THEN taker_bps_from_oracle END)
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OVER (PARTITION BY MarketIndex ORDER BY Time RANGE BETWEEN INTERVAL '${smoothingMinutes}' MINUTE PRECEDING AND CURRENT ROW)
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AS "TakerBuyBpsFromOracle_1e4",
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AVG(CASE WHEN dir = 'long' AND cohort = '1e5' THEN taker_bps_from_oracle END)
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OVER (PARTITION BY MarketIndex ORDER BY Time RANGE BETWEEN INTERVAL '${smoothingMinutes}' MINUTE PRECEDING AND CURRENT ROW)
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AS "TakerBuyBpsFromOracle_1e5",
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AVG(CASE WHEN dir = 'long' AND cohort = '1e6' THEN taker_bps_from_oracle END)
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OVER (PARTITION BY MarketIndex ORDER BY Time RANGE BETWEEN INTERVAL '${smoothingMinutes}' MINUTE PRECEDING AND CURRENT ROW)
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AS "TakerBuyBpsFromOracle_1e6",
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AVG(CASE WHEN dir = 'short' AND cohort = '1e0' THEN taker_bps_from_oracle END)
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OVER (PARTITION BY MarketIndex ORDER BY Time RANGE BETWEEN INTERVAL '${smoothingMinutes}' MINUTE PRECEDING AND CURRENT ROW)
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AS "TakerSellBpsFromOracle_1e0",
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AVG(CASE WHEN dir = 'short' AND cohort = '1e3' THEN taker_bps_from_oracle END)
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OVER (PARTITION BY MarketIndex ORDER BY Time RANGE BETWEEN INTERVAL '${smoothingMinutes}' MINUTE PRECEDING AND CURRENT ROW)
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AS "TakerSellBpsFromOracle_1e3",
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AVG(CASE WHEN dir = 'short' AND cohort = '1e4' THEN taker_bps_from_oracle END)
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OVER (PARTITION BY MarketIndex ORDER BY Time RANGE BETWEEN INTERVAL '${smoothingMinutes}' MINUTE PRECEDING AND CURRENT ROW)
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AS "TakerSellBpsFromOracle_1e4",
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AVG(CASE WHEN dir = 'short' AND cohort = '1e5' THEN taker_bps_from_oracle END)
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OVER (PARTITION BY MarketIndex ORDER BY Time RANGE BETWEEN INTERVAL '${smoothingMinutes}' MINUTE PRECEDING AND CURRENT ROW)
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AS "TakerSellBpsFromOracle_1e5",
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AVG(CASE WHEN dir = 'short' AND cohort = '1e6' THEN taker_bps_from_oracle END)
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OVER (PARTITION BY MarketIndex ORDER BY Time RANGE BETWEEN INTERVAL '${smoothingMinutes}' MINUTE PRECEDING AND CURRENT ROW)
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AS "TakerSellBpsFromOracle_1e6",
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ROW_NUMBER() OVER (PARTITION BY MarketIndex ORDER BY Time DESC) AS rn
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FROM bucketed
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WHERE taker_bps_from_oracle IS NOT NULL
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)
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-- Select only the latest row per market
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SELECT
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Time,
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MarketIndex,
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"TakerBuyBpsFromOracle_ALL",
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"TakerSellBpsFromOracle_ALL",
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"TakerBuyBpsFromOracle_1e0",
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"TakerBuyBpsFromOracle_1e3",
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"TakerBuyBpsFromOracle_1e4",
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"TakerBuyBpsFromOracle_1e5",
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"TakerBuyBpsFromOracle_1e6",
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"TakerSellBpsFromOracle_1e0",
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"TakerSellBpsFromOracle_1e3",
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"TakerSellBpsFromOracle_1e4",
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"TakerSellBpsFromOracle_1e5",
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"TakerSellBpsFromOracle_1e6"
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FROM rolling_avgs
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WHERE rn = 1
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ORDER BY MarketIndex;
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`;
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const results = await query(queryString);
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return results.map((result) => ({
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Time: result.Time || '',
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MarketIndex: result.MarketIndex || '',
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TakerBuyBpsFromOracle_ALL: result.TakerBuyBpsFromOracle_ALL,
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TakerSellBpsFromOracle_ALL: result.TakerSellBpsFromOracle_ALL,
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TakerBuyBpsFromOracle_1e0: result.TakerBuyBpsFromOracle_1e0,
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TakerBuyBpsFromOracle_1e3: result.TakerBuyBpsFromOracle_1e3,
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TakerBuyBpsFromOracle_1e4: result.TakerBuyBpsFromOracle_1e4,
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TakerBuyBpsFromOracle_1e5: result.TakerBuyBpsFromOracle_1e5,
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TakerBuyBpsFromOracle_1e6: result.TakerBuyBpsFromOracle_1e6,
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TakerSellBpsFromOracle_1e0: result.TakerSellBpsFromOracle_1e0,
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TakerSellBpsFromOracle_1e3: result.TakerSellBpsFromOracle_1e3,
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TakerSellBpsFromOracle_1e4: result.TakerSellBpsFromOracle_1e4,
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TakerSellBpsFromOracle_1e5: result.TakerSellBpsFromOracle_1e5,
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TakerSellBpsFromOracle_1e6: result.TakerSellBpsFromOracle_1e6,
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Zero: result.Zero || '0',
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}));
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};
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return {
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getTakerFillVsOracleBps,
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};
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};
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