{"slug":"iceberg-orders-explained","qid":"level_trace","label":"The busiest price and size pairing, half hour by half hour","post_title":"Iceberg Orders Explained: Hidden Liquidity","post_url":"/blog/iceberg-orders-explained#q-level_trace","columns":["et_time","prints","cum_prints"],"rows":[{"et_time":"09:30","prints":67,"cum_prints":67}],"shape":"scalar","sql":"WITH top_level AS\n(\n    SELECT\n        price,\n        size\n    FROM global_markets.stocks_trades\n    WHERE ticker = 'AAPL'\n      AND sip_timestamp >= toDateTime('2026-06-17 04:00:00', 'UTC')\n      AND sip_timestamp <  toDateTime('2026-06-18 04:00:00', 'UTC')\n      AND size >= 200\n    GROUP BY price, size\n    ORDER BY count() DESC, size DESC, price DESC\n    LIMIT 1\n)\nSELECT\n    formatDateTime(toStartOfInterval(toTimeZone(sip_timestamp, 'America/New_York'), INTERVAL 30 MINUTE), '%H:%i') AS et_time,\n    count()                                    AS prints,\n    sum(count()) OVER (ORDER BY et_time)       AS cum_prints\nFROM global_markets.stocks_trades\nWHERE ticker = 'AAPL'\n  AND sip_timestamp >= toDateTime('2026-06-17 04:00:00', 'UTC')\n  AND sip_timestamp <  toDateTime('2026-06-18 04:00:00', 'UTC')\n  AND (price, size) IN (SELECT price, size FROM top_level)\nGROUP BY et_time\nORDER BY et_time","computed_at":"2026-08-06T04:14:24.887149+00:00","elapsed":0.002752635}