import serialize from '../api/resolvers/serial.js' import { sendUserNotification } from '../api/webPush/index.js' import { ANON_USER_ID } from '../lib/constants.js' import { msatsToSats, numWithUnits } from '../lib/format.js' const ITEM_EACH_REWARD = 4.0 const UPVOTE_EACH_REWARD = 4.0 const TOP_PERCENTILE = 33 const TOTAL_UPPER_BOUND_MSATS = 1000000000 const REDUCE_REWARDS = [616, 6030, 946, 4502] export function earn ({ models }) { return async function ({ name }) { console.log('running', name) // compute how much sn earned today const [{ sum: sumDecimal }] = await models.$queryRaw` SELECT coalesce(sum(msats), 0) as sum FROM ( (SELECT ("ItemAct".msats - COALESCE("ReferralAct".msats, 0)) as msats FROM "ItemAct" LEFT JOIN "ReferralAct" ON "ReferralAct"."itemActId" = "ItemAct".id WHERE date_trunc('day', "ItemAct".created_at AT TIME ZONE 'UTC' AT TIME ZONE 'America/Chicago') = date_trunc('day', (now() - interval '1 day') AT TIME ZONE 'America/Chicago') AND "ItemAct".act <> 'TIP') UNION ALL (SELECT sats * 1000 as msats FROM "Donation" WHERE date_trunc('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE 'America/Chicago') = date_trunc('day', (now() - interval '1 day') AT TIME ZONE 'America/Chicago')) UNION ALL -- any earnings from anon's stack that are not forwarded to other users (SELECT "ItemAct".msats FROM "Item" JOIN "ItemAct" ON "ItemAct"."itemId" = "Item".id LEFT JOIN "ItemForward" ON "ItemForward"."itemId" = "Item".id WHERE "Item"."userId" = ${ANON_USER_ID} AND "ItemAct".act = 'TIP' AND date_trunc('day', "ItemAct".created_at AT TIME ZONE 'UTC' AT TIME ZONE 'America/Chicago') = date_trunc('day', (now() - interval '1 day') AT TIME ZONE 'America/Chicago') GROUP BY "ItemAct".id, "ItemAct".msats HAVING COUNT("ItemForward".id) = 0) ) subquery` // XXX primsa will return a Decimal (https://mikemcl.github.io/decimal.js) // because sum of a BIGINT returns a NUMERIC type (https://www.postgresql.org/docs/13/functions-aggregate.html) // and Decimal is what prisma maps it to https://www.prisma.io/docs/concepts/components/prisma-client/raw-database-access#raw-query-type-mapping // so check it before coercing to Number if (!sumDecimal || sumDecimal.lessThanOrEqualTo(0)) { console.log('done', name, 'no sats to award today') return } // extra sanity check on rewards ... if it's more than upper bound, we // probably have a bug somewhere or we've grown A LOT if (sumDecimal.greaterThan(TOTAL_UPPER_BOUND_MSATS)) { console.log('done', name, 'error: too many sats to award today', sumDecimal) return } const sum = Number(sumDecimal) const heads = Math.random() < 0.5 // if this category is selected, double its proportion // if it isn't select, zero its proportion const itemRewardMult = heads ? 0 : 2.0 const upvoteRewardMult = heads ? 2.0 : 0 console.log(name, 'giving away', sum, 'msats', 'rewarding', heads ? 'items' : 'upvotes') /* How earnings (used to) work: 1/3: top 21% posts over last 36 hours, scored on a relative basis 1/3: top 21% comments over last 36 hours, scored on a relative basis 1/3: top upvoters of top posts/comments, scored on: - their trust - how much they tipped - how early they upvoted it - how the post/comment scored Now: 100% of earnings go to either top 33% of comments/posts or top 33% of upvoters */ // get earners { userId, id, type, rank, proportion } const earners = await models.$queryRaw` -- get top 21% of posts and comments WITH item_ratios AS ( SELECT *, CASE WHEN "parentId" IS NULL THEN 'POST' ELSE 'COMMENT' END as type, CASE WHEN "weightedVotes" > 0 THEN "weightedVotes"/(sum("weightedVotes") OVER (PARTITION BY "parentId" IS NULL)) ELSE 0 END AS ratio FROM ( SELECT *, NTILE(100) OVER (PARTITION BY "parentId" IS NULL ORDER BY ("weightedVotes"-"weightedDownVotes") desc) AS percentile, ROW_NUMBER() OVER (PARTITION BY "parentId" IS NULL ORDER BY ("weightedVotes"-"weightedDownVotes") desc) AS rank FROM "Item" WHERE created_at >= now_utc() - interval '36 hours' AND "weightedVotes" > 0 AND "deletedAt" IS NULL AND NOT bio ) x WHERE x.percentile <= ${TOP_PERCENTILE} ), -- get top upvoters of top posts and comments upvoter_islands AS ( SELECT "ItemAct"."userId", item_ratios.id, item_ratios.ratio, item_ratios."parentId", "ItemAct".msats as tipped, "ItemAct".created_at as acted_at, ROW_NUMBER() OVER (partition by item_ratios.id order by "ItemAct".created_at asc) - ROW_NUMBER() OVER (partition by item_ratios.id, "ItemAct"."userId" order by "ItemAct".created_at asc) AS island FROM item_ratios JOIN "ItemAct" on "ItemAct"."itemId" = item_ratios.id WHERE act = 'TIP' ), -- isolate contiguous upzaps from the same user on the same item so that when we take the log -- of the upzaps it accounts for successive zaps and does not disproporionately reward them upvoters AS ( SELECT "userId", id, ratio, "parentId", GREATEST(log(sum(tipped) / 1000), 0) as tipped, min(acted_at) as acted_at FROM upvoter_islands GROUP BY "userId", id, ratio, "parentId", island ), -- the relative contribution of each upvoter to the post/comment -- early multiplier: 10/ln(early_rank + e) -- we also weight by trust in a step wise fashion upvoter_ratios AS ( SELECT "userId", sum(early_multiplier*tipped_ratio*ratio*CASE WHEN users.id = ANY (${REDUCE_REWARDS}) THEN 0.2 ELSE CEIL(users.trust*2)+1 END) as upvoter_ratio, "parentId" IS NULL as "isPost", CASE WHEN "parentId" IS NULL THEN 'TIP_POST' ELSE 'TIP_COMMENT' END as type FROM ( SELECT *, 10.0/LN(ROW_NUMBER() OVER (partition by id order by acted_at asc) + EXP(1.0)) AS early_multiplier, tipped::float/(sum(tipped) OVER (partition by id)) tipped_ratio FROM upvoters ) u JOIN users on "userId" = users.id GROUP BY "userId", "parentId" IS NULL ), proportions AS ( SELECT "userId", NULL as id, type, ROW_NUMBER() OVER (PARTITION BY "isPost" ORDER BY upvoter_ratio DESC) as rank, ${itemRewardMult}*upvoter_ratio/(sum(upvoter_ratio) OVER (PARTITION BY "isPost"))/${UPVOTE_EACH_REWARD} as proportion FROM upvoter_ratios WHERE upvoter_ratio > 0 UNION ALL SELECT "userId", id, type, rank, ${upvoteRewardMult}*ratio/${ITEM_EACH_REWARD} as proportion FROM item_ratios) SELECT "userId", id, type, rank, proportion FROM proportions WHERE proportion > 0.0001` // in order to group earnings for users we use the same createdAt time for // all earnings const now = new Date(new Date().getTime()) // this is just a sanity check because it seems like a good idea let total = 0 const notifications = {} for (const earner of earners) { const earnings = Math.floor(parseFloat(earner.proportion) * sum) total += earnings if (total > sum) { console.log(name, 'total exceeds sum', total, '>', sum) return } console.log('stacker', earner.userId, 'earned', earnings, 'proportion', earner.proportion, 'rank', earner.rank, 'type', earner.type) if (earnings > 0) { await serialize(models, models.$executeRaw`SELECT earn(${earner.userId}::INTEGER, ${earnings}, ${now}::timestamp without time zone, ${earner.type}::"EarnType", ${earner.id}::INTEGER, ${earner.rank}::INTEGER)`) notifications[earner.userId] = { ...notifications[earner.userId], total: earnings + (notifications[earner.userId]?.total || 0), [earner.type]: { msats: earnings, rank: earner.rank } } } } Promise.allSettled(Object.entries(notifications).map(([userId, earnings]) => sendUserNotification(parseInt(userId, 10), buildUserNotification(earnings)) )).catch(console.error) console.log('done', name) } } function buildUserNotification (earnings) { const fmt = msats => numWithUnits(msatsToSats(msats, { abbreviate: false })) const title = `you stacked ${fmt(earnings.total)} in rewards` const tag = 'EARN' let body = '' if (earnings.POST) body += `#${earnings.POST.rank} among posts for ${fmt(earnings.POST.msats)}\n` if (earnings.COMMENT) body += `#${earnings.COMMENT.rank} among comments for ${fmt(earnings.COMMENT.msats)}\n` if (earnings.TIP_POST) body += `#${earnings.TIP_POST.rank} in post zapping for ${fmt(earnings.TIP_POST.msats)}\n` if (earnings.TIP_COMMENT) body += `#${earnings.TIP_COMMENT.rank} in comment zapping for ${fmt(earnings.TIP_COMMENT.msats)}\n` return { title, tag, body } }