prompt stringlengths 169 37.8k | completion stringlengths 30 1.53k | source_tag stringclasses 11
values | evidence stringlengths 0 673 | exec_acc float64 -1 1 | has_cte bool 2
classes | has_window bool 2
classes |
|---|---|---|---|---|---|---|
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: which day had the highest revenue this month | SELECT
c.site_id AS entity,
SUM(c.total) AS net_sales
FROM TRAY_CHECKS c
JOIN TRAY_SITES s ON s.site_id = c.site_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('month', CURRENT_DATE)
AND c.is_deleted = FALSE
GROUP BY c.site_id
ORDER BY net_sales DESC
LIMIT 10; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: tip as percentage of total sales this week | SELECT
e.full_name AS tip,
SUM(c.total) AS net_sales
FROM TRAY_PAYMENTS p
JOIN TRAY_CHECKS c ON c.check_id = p.check_id
JOIN TRAY_EMPLOYEES e ON e.employee_id = c.employee_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('week', CURRENT_DATE)
AND c.is_deleted = FALSE
AND p.tip_amount > 0
GROUP BY e.full_name; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: labor cost as percentage of sales today | SELECT
s.name AS labor,
ROUND(DIV0(SUM(ls.net_sales), NULLIF(SUM(ls.labor_hours), 0)), 2) AS splh
FROM TRAY_LABOR_SUMMARY ls
JOIN TRAY_SITES s ON s.site_id = ls.site_id
WHERE ls.business_date = CURRENT_DATE
GROUP BY s.name; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: discount rate by item category this month | SELECT
i.category_name AS category,
SUM(d.amount) AS discount_amount
FROM INT_TRAY_ITEMS_CLEAN_V1 i
JOIN TRAY_CHECKS c ON c.check_id = i.check_id
JOIN TRAY_DISCOUNTS d ON d.check_id = c.check_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('month', CURRENT_DATE)
AND c.is_deleted = FALSE
GROUP BY i.category_name... | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: sales by revenue center yesterday | SELECT
rc.name AS revenue_center,
SUM(c.total) AS net_sales
FROM TRAY_REVENUE_CENTERS rc
JOIN TRAY_CHECKS c ON c.revenue_center_id = rc.rc_id
WHERE TRY_TO_DATE(c.close_tdt) = CURRENT_DATE - 1
AND c.is_deleted = FALSE
GROUP BY rc.name; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: average check by revenue center this month | SELECT
rc.name AS revenue_center,
ROUND(AVG(c.total), 2) AS avg_check_size
FROM TRAY_REVENUE_CENTERS rc
JOIN TRAY_CHECKS c ON c.revenue_center_id = rc.rc_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('month', CURRENT_DATE)
AND c.is_deleted = FALSE
GROUP BY rc.name; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: tip distribution by payment type this week | SELECT
p.tender_type AS payment,
SUM(p.tip_amount) AS total_tips
FROM TRAY_PAYMENTS p
JOIN TRAY_CHECKS c ON c.check_id = p.check_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('week', CURRENT_DATE)
AND c.is_deleted = FALSE
GROUP BY p.tender_type; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: cash payment total vs card total yesterday | SELECT
p.tender_type AS payment,
SUM(c.total) AS net_sales
FROM TRAY_PAYMENTS p
JOIN TRAY_CHECKS c ON c.check_id = p.check_id
WHERE TRY_TO_DATE(c.close_tdt) = CURRENT_DATE - 1
AND c.is_deleted = FALSE
GROUP BY p.tender_type; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: overtime hours by site this month | SELECT
s.name AS labor,
SUM(GREATEST(ls.actual_hours - 40, 0)) AS overtime_hours,
s.name AS site_name
FROM TRAY_LABOR_SUMMARY ls
JOIN TRAY_SITES s ON s.site_id = ls.site_id
WHERE ls.business_date >= DATE_TRUNC('month', CURRENT_DATE)
GROUP BY s.name, s.name; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: sales per labor hour trend last 14 days | SELECT
s.name AS labor,
ROUND(DIV0(SUM(ls.net_sales), NULLIF(SUM(ls.labor_hours), 0)), 2) AS splh,
ls.business_date AS period
FROM TRAY_LABOR_SUMMARY ls
JOIN TRAY_SITES s ON s.site_id = ls.site_id
WHERE ls.business_date >= CURRENT_DATE - 14
GROUP BY s.name, ls.business_date
ORDER BY ls.business_date; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: labor utilization rate today | SELECT
s.name AS labor,
SUM(ls.actual_hours) AS labor_hours
FROM TRAY_LABOR_SUMMARY ls
JOIN TRAY_SITES s ON s.site_id = ls.site_id
WHERE ls.business_date = CURRENT_DATE
GROUP BY s.name; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: top 10 items by quantity this week | SELECT
i.product_name AS item,
SUM(c.total) AS net_sales
FROM INT_TRAY_ITEMS_CLEAN_V1 i
JOIN TRAY_CHECKS c ON c.check_id = i.check_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('week', CURRENT_DATE)
AND c.is_deleted = FALSE
AND i.action = 'SALE'
GROUP BY i.product_name
ORDER BY net_sales DESC
LIMIT 10; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: revenue per item in dessert category this month | SELECT
i.category_name AS category,
SUM(c.total) AS net_sales
FROM INT_TRAY_ITEMS_CLEAN_V1 i
JOIN TRAY_CHECKS c ON c.check_id = i.check_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('month', CURRENT_DATE)
AND c.is_deleted = FALSE
GROUP BY i.category_name; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: category breakdown of sales this week | SELECT
i.category_name AS category,
'STANDARD', COUNT(DISTINCT c.check_id) AS check_count, SUM(c.total) AS net_sales
FROM INT_TRAY_ITEMS_CLEAN_V1 i
JOIN TRAY_CHECKS c ON c.check_id = i.check_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('week', CURRENT_DATE)
AND c.is_deleted = FALSE
GROUP BY i.category_name; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: void reasons ranked by frequency this month | SELECT
e.full_name AS void,
COUNT(DISTINCT c.check_id) AS check_count
FROM TRAY_CHECKS c
JOIN TRAY_EMPLOYEES e ON e.employee_id = c.employee_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('month', CURRENT_DATE)
AND c.is_deleted = FALSE
GROUP BY e.full_name
ORDER BY check_count DESC
LIMIT 10; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: comp total vs void total this week | SELECT
e.full_name AS void,
COUNT(CASE WHEN c.void_reason IS NOT NULL THEN 1 END) AS void_count
FROM TRAY_CHECKS c
JOIN TRAY_EMPLOYEES e ON e.employee_id = c.employee_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('week', CURRENT_DATE)
AND c.is_deleted = FALSE
GROUP BY e.full_name; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: servers with comps above average this month | SELECT
e.full_name AS server,
SUM(d.amount) AS comp_amount,
COUNT(DISTINCT c.check_id) AS check_count
FROM TRAY_EMPLOYEES e
JOIN TRAY_CHECKS c ON c.employee_id = e.employee_id
JOIN TRAY_DISCOUNTS d ON d.check_id = c.check_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('month', CURRENT_DATE)
AND c.is_delete... | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: discount impact on net sales this week | SELECT
d.discount_type AS discount,
SUM(d.amount) AS discount_amount
FROM TRAY_DISCOUNTS d
JOIN TRAY_CHECKS c ON c.check_id = d.check_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('week', CURRENT_DATE)
AND c.is_deleted = FALSE
GROUP BY d.discount_type; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: average check size by day of week last 30 days | SELECT
c.check_id AS check,
ROUND(AVG(c.total), 2) AS avg_check_size,
DATE_TRUNC('week', TRY_TO_DATE(c.close_tdt)) AS week_start
FROM TRAY_CHECKS c
JOIN TRAY_SITES s ON s.site_id = c.site_id
WHERE TRY_TO_DATE(c.close_tdt) >= CURRENT_DATE - 30
AND c.is_deleted = FALSE
GROUP BY c.check_id, DATE_TRUNC('week', ... | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: largest checks yesterday | SELECT
c.check_id AS check,
COUNT(DISTINCT c.check_id) AS check_count
FROM TRAY_CHECKS c
JOIN TRAY_SITES s ON s.site_id = c.site_id
WHERE TRY_TO_DATE(c.close_tdt) = CURRENT_DATE - 1
AND c.is_deleted = FALSE
GROUP BY c.check_id; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: net sales by site ranked this month | SELECT
s.name AS site,
SUM(f.NET_SALES_AMOUNT) AS net_sales
FROM FACT_TRAY_CHECK_DAY_V1 f
JOIN TRAY_SITES s ON s.site_id = f.SITE_ID
WHERE f.BUSINESS_DATE >= DATE_TRUNC('month', CURRENT_DATE)
AND f.CHECK_CLASS != 'VOIDED'
GROUP BY s.name
ORDER BY net_sales DESC
LIMIT 10; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: guest count by site today | SELECT
s.name AS site,
SUM(f.POSTRAFFICCOUNT) AS guest_count
FROM FACT_TRAY_CHECK_DAY_V1 f
JOIN TRAY_SITES s ON s.site_id = f.SITE_ID
WHERE f.BUSINESS_DATE = CURRENT_DATE
AND f.CHECK_CLASS != 'VOIDED'
GROUP BY s.name; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: sales compared to same day last week | SELECT
e.full_name AS comp,
SUM(c.total) AS net_sales
FROM TRAY_CHECKS c
JOIN TRAY_EMPLOYEES e ON e.employee_id = c.employee_id
JOIN TRAY_DISCOUNTS d ON d.check_id = c.check_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('week', CURRENT_DATE - 7)
AND TRY_TO_DATE(c.close_tdt) < DATE_TRUNC('week', CURRENT_DATE... | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: year over year growth this month | WITH current_period AS (
SELECT
c.site_id AS entity,
SUM(c.total) AS net_sales
FROM TRAY_CHECKS c
JOIN TRAY_SITES s ON s.site_id = c.site_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('week', CURRENT_DATE)
AND c.is_deleted = FALSE
GROUP BY c.site_id
),
prior_period AS (
SEL... | tray_hard | -1 | true | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: server efficiency: sales divided by hours worked this week | SELECT
DATE_PART('hour', TRY_TO_TIMESTAMP(c.close_tdt)) AS hour_of_day,
e.full_name AS server,
SUM(c.total) AS net_sales
FROM TRAY_EMPLOYEES e
JOIN TRAY_CHECKS c ON c.employee_id = e.employee_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('week', CURRENT_DATE)
AND c.is_deleted = FALSE
AND e.is_active = T... | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: fleet summary with sales labor and voids this week | SELECT
e.full_name AS void,
SUM(c.total) AS net_sales
FROM TRAY_CHECKS c
JOIN TRAY_EMPLOYEES e ON e.employee_id = c.employee_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('week', CURRENT_DATE)
AND c.is_deleted = FALSE
GROUP BY e.full_name; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: average check size per server this month | SELECT
e.full_name AS server,
ROUND(AVG(c.total), 2) AS avg_check_size,
COUNT(DISTINCT c.check_id) AS check_count
FROM TRAY_EMPLOYEES e
JOIN TRAY_CHECKS c ON c.employee_id = e.employee_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('month', CURRENT_DATE)
AND c.is_deleted = FALSE
AND e.is_active = TRUE
GR... | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: tip total by server yesterday | SELECT
e.full_name AS server,
SUM(p.tip_amount) AS total_tips
FROM TRAY_EMPLOYEES e
JOIN TRAY_CHECKS c ON c.employee_id = e.employee_id
JOIN TRAY_PAYMENTS p ON p.check_id = c.check_id
WHERE TRY_TO_DATE(c.close_tdt) = CURRENT_DATE - 1
AND c.is_deleted = FALSE
AND e.is_active = TRUE
GROUP BY e.full_name
HAVING ... | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: server comp rate this week | SELECT
e.full_name AS server,
ROUND(DIV0(SUM(d.amount), SUM(c.total)) * 100, 2) AS comp_rate_pct,
COUNT(DISTINCT c.check_id) AS check_count
FROM TRAY_EMPLOYEES e
JOIN TRAY_CHECKS c ON c.employee_id = e.employee_id
JOIN TRAY_DISCOUNTS d ON d.check_id = c.check_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC(... | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: which server has the most checks today | SELECT
e.full_name AS server,
COUNT(DISTINCT c.check_id) AS check_count,
COUNT(DISTINCT c.check_id) AS check_count
FROM TRAY_EMPLOYEES e
JOIN TRAY_CHECKS c ON c.employee_id = e.employee_id
WHERE TRY_TO_DATE(c.close_tdt) = CURRENT_DATE
AND c.is_deleted = FALSE
AND e.is_active = TRUE
GROUP BY e.full_name
HA... | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: servers with zero voids this week | SELECT
e.full_name AS server,
COUNT(CASE WHEN c.void_reason IS NOT NULL THEN 1 END) AS void_count,
COUNT(DISTINCT c.check_id) AS check_count
FROM TRAY_EMPLOYEES e
JOIN TRAY_CHECKS c ON c.employee_id = e.employee_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('week', CURRENT_DATE)
AND c.is_deleted = FALSE
... | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: item count by category this week | SELECT
i.category_name AS category,
COUNT(DISTINCT c.check_id) AS check_count
FROM INT_TRAY_ITEMS_CLEAN_V1 i
JOIN TRAY_CHECKS c ON c.check_id = i.check_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('week', CURRENT_DATE)
AND c.is_deleted = FALSE
GROUP BY i.category_name; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: hourly sales breakdown today | SELECT
s.name AS labor,
'LABOR', COUNT(DISTINCT ls.site_id) AS check_count, SUM(ls.net_sales) AS net_sales
FROM TRAY_LABOR_SUMMARY ls
JOIN TRAY_SITES s ON s.site_id = ls.site_id
WHERE ls.business_date = CURRENT_DATE
GROUP BY s.name; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: labor hours by day this month | SELECT
s.name AS labor,
SUM(ls.actual_hours) AS labor_hours,
ls.business_date AS period
FROM TRAY_LABOR_SUMMARY ls
JOIN TRAY_SITES s ON s.site_id = ls.site_id
WHERE ls.business_date >= DATE_TRUNC('month', CURRENT_DATE)
GROUP BY s.name, ls.business_date
ORDER BY ls.business_date; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: normalized labor cost across all sites this month | SELECT
s.name AS labor,
ROUND(DIV0(SUM(ls.net_sales), NULLIF(SUM(ls.labor_hours), 0)), 2) AS splh,
ROUND(DIV0(splh, NULLIF(SUM(splh) OVER (), 0)) * 100, 2) AS splh_pct_of_total
FROM TRAY_LABOR_SUMMARY ls
JOIN TRAY_SITES s ON s.site_id = ls.site_id
WHERE ls.business_date >= DATE_TRUNC('month', CURRENT_DATE)
... | tray_hard | -1 | false | true | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: payment breakdown by type this week | SELECT
p.tender_type AS payment,
'STANDARD', COUNT(DISTINCT c.check_id) AS check_count, SUM(c.total) AS net_sales
FROM TRAY_PAYMENTS p
JOIN TRAY_CHECKS c ON c.check_id = p.check_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('week', CURRENT_DATE)
AND c.is_deleted = FALSE
GROUP BY p.tender_type; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: average tip per check today | SELECT
c.check_id AS check,
SUM(p.tip_amount) AS total_tips
FROM TRAY_CHECKS c
JOIN TRAY_SITES s ON s.site_id = c.site_id
JOIN TRAY_PAYMENTS p ON p.check_id = c.check_id
WHERE TRY_TO_DATE(c.close_tdt) = CURRENT_DATE
AND c.is_deleted = FALSE
GROUP BY c.check_id; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: total tips this month | SELECT
e.full_name AS tip,
SUM(p.tip_amount) AS total_tips
FROM TRAY_PAYMENTS p
JOIN TRAY_CHECKS c ON c.check_id = p.check_id
JOIN TRAY_EMPLOYEES e ON e.employee_id = c.employee_id
WHERE TRY_TO_DATE(c.close_tdt) >= DATE_TRUNC('month', CURRENT_DATE)
AND c.is_deleted = FALSE
AND p.tip_amount > 0
GROUP BY e.full... | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: total void amount yesterday | SELECT
e.full_name AS void,
SUM(CASE WHEN c.void_reason IS NOT NULL THEN c.total ELSE 0 END) AS void_amount
FROM TRAY_CHECKS c
JOIN TRAY_EMPLOYEES e ON e.employee_id = c.employee_id
WHERE TRY_TO_DATE(c.close_tdt) = CURRENT_DATE - 1
AND c.is_deleted = FALSE
GROUP BY e.full_name; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: discount trending by hour today | SELECT
DATE_PART('hour', TRY_TO_TIMESTAMP(c.close_tdt)) AS hour_of_day,
d.discount_type AS discount,
SUM(d.amount) AS discount_amount
FROM TRAY_DISCOUNTS d
JOIN TRAY_CHECKS c ON c.check_id = d.check_id
WHERE TRY_TO_DATE(c.close_tdt) = CURRENT_DATE
AND c.is_deleted = FALSE
GROUP BY DATE_PART('hour', TRY_TO_T... | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: average check size today | SELECT
c.check_id AS check,
ROUND(AVG(c.total), 2) AS avg_check_size
FROM TRAY_CHECKS c
JOIN TRAY_SITES s ON s.site_id = c.site_id
WHERE TRY_TO_DATE(c.close_tdt) = CURRENT_DATE
AND c.is_deleted = FALSE
GROUP BY c.check_id; | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Question: guest count trend last 30 days | SELECT
c.site_id AS entity,
SUM(1) AS guest_count,
DATE_TRUNC('week', TRY_TO_DATE(c.close_tdt)) AS week_start
FROM TRAY_CHECKS c
JOIN TRAY_SITES s ON s.site_id = c.site_id
WHERE TRY_TO_DATE(c.close_tdt) >= CURRENT_DATE - 30
AND c.is_deleted = FALSE
GROUP BY c.site_id, DATE_TRUNC('week', TRY_TO_DATE(c.close_... | tray_hard | -1 | false | false | |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Schema:
-- FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1
-- One row per (SITE_ID, CHECKID, BUSINESS_DATE). All monetary values in USD.
CREATE TABLE FACT_TRAY_CHECK_DAY_V1 (
SITE_ID ... | WITH weekly AS (
SELECT
SITE_ID,
DATE_TRUNC('week', BUSINESS_DATE) AS WEEK_START,
SUM(NET_SALES_AMOUNT) AS NET_SALES
FROM FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1
WHERE BUSINESS_DATE >= DATEADD('week', -4, DATE_TRUNC('week', CURRENT_DATE()))
AND CHECK_CLASS = 'STANDARD'
GROUP BY... | tray | LAG window function with PARTITION BY SITE_ID computes prior week for each site independently. | -1 | true | true |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Schema:
-- FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1
-- One row per (SITE_ID, CHECKID, BUSINESS_DATE). All monetary values in USD.
CREATE TABLE FACT_TRAY_CHECK_DAY_V1 (
SITE_ID ... | WITH daily AS (
SELECT
SITE_ID,
BUSINESS_DATE,
SUM(NET_SALES_AMOUNT) AS NET_SALES
FROM FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1
WHERE BUSINESS_DATE >= DATEADD('day', -30, CURRENT_DATE())
AND CHECK_CLASS = 'STANDARD'
GROUP BY SITE_ID, BUSINESS_DATE
),
stats AS (
SELECT
... | tray | Z-score = (value - mean) / stddev. Z < -2 is a 95th percentile low day. CTE pattern: compute daily sums, then stats, then join + filter. | -1 | true | false |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Schema:
-- FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1
-- One row per (SITE_ID, CHECKID, BUSINESS_DATE). All monetary values in USD.
CREATE TABLE FACT_TRAY_CHECK_DAY_V1 (
SITE_ID ... | WITH emp_stats AS (
SELECT
EMPLOYEEID,
COUNT(DISTINCT CHECKID) AS CHECK_COUNT,
SUM(NET_DISCOUNT_COMP_AMOUNT) AS TOTAL_DISCOUNTS,
SUM(SALES_SCOPE_GROSS_AMOUNT) AS GROSS_SALES,
ROUND(
100.0 * SUM(NET_DISCOUNT_COMP_AMOUNT) / NULLIF(SUM(SALES_SCOPE_GROSS_AMOUNT), 0),
... | tray | Unusually high = Z-score > 2 above mean across all employees. CROSS JOIN overall computes z-score without a window function. HAVING >= 10 checks prevents noise from low-volume employees. | -1 | true | false |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Schema:
-- FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1
-- One row per (SITE_ID, CHECKID, BUSINESS_DATE). All monetary values in USD.
CREATE TABLE FACT_TRAY_CHECK_DAY_V1 (
SITE_ID ... | SELECT
FULL_NAME,
SUM(NET_SALES) AS TOTAL_SALES_REVENUE,
SUM(TOTAL_ORDERS) AS INTEGER_OF_ORDERS,
ROUND(SUM(NET_SALES) / NULLIF(SUM(TOTAL_ORDERS), 0), 2) AS AVERAGE_ORDER_VALUE
FROM VW_SERVER_PERFORMANCE
WHERE BUSINESS_DATE BETWEEN DATEADD('day', -6, CURRENT_DATE()) AND CURRENT_DATE()
GROUP BY FULL_NAME
... | tray | VW_SERVER_PERFORMANCE grain: SERVER_GUID + BUSINESS_DATE + LOCATION_ID. This week = last 7 days. FULL_NAME aggregates across all locations the server worked. SUM(NET_SALES)/NULLIF(SUM(TOTAL_ORDERS),0) gives correct weighted avg (not AVG of AVG which ignores volume). Observed real result: Bar Bar $10,537 (129 orders), 1... | -1 | false | false |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Schema:
-- FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1
-- One row per (SITE_ID, CHECKID, BUSINESS_DATE). All monetary values in USD.
CREATE TABLE FACT_TRAY_CHECK_DAY_V1 (
SITE_ID ... | SELECT
FULL_NAME,
COUNT(DISTINCT BUSINESS_DATE) AS DAYS_WORKED,
SUM(TOTAL_ORDERS) AS TOTAL_ORDERS,
ROUND(SUM(NET_SALES) / NULLIF(SUM(TOTAL_ORDERS), 0), 2) AS AVG_CHECK_SIZE
FROM VW_SERVER_PERFORMANCE
WHERE BUSINESS_DATE >= DATEADD('day', -30, CURRENT_DATE())
GROUP BY FULL_NAME
HAVING SUM(TOTAL_ORDERS) >... | tray | At this view grain, weighted average check size = SUM(NET_SALES) / NULLIF(SUM(TOTAL_ORDERS), 0). Do not use AVG(AVG_SALES_PER_CHECK): that equal-weights days and ignores order volume. HAVING >= 10 orders removes low-volume noise. | -1 | false | false |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Schema:
-- FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1
-- One row per (SITE_ID, CHECKID, BUSINESS_DATE). All monetary values in USD.
CREATE TABLE FACT_TRAY_CHECK_DAY_V1 (
SITE_ID ... | SELECT
FULL_NAME,
SUM(NET_SALES) AS TOTAL_SALES,
SUM(TOTAL_ORDERS) AS ORDERS,
SUM(TOTAL_GUESTS_SERVED) AS GUESTS,
ROUND(SUM(TOTAL_TIPS) / NULLIF(SUM(NET_SALES), 0) * 100, 1) AS TIP_PCT,
ROUND(
SUM(AVG_TURN_TIME_MINUTES * TOTAL_ORDERS)
/ NULLIF(SUM(TOTAL_ORDERS), 0),
1... | tray | VW_SERVER_PERFORMANCE has: TOTAL_TIPS, TOTAL_GUESTS_SERVED, AVG_TURN_TIME_MINUTES. Tip % = tips / net_sales * 100. Turn time: use SUM(AVG_TURN_TIME_MINUTES * TOTAL_ORDERS) / NULLIF(SUM(TOTAL_ORDERS), 0) so high-order days weigh more than quiet days (AVG(AVG_TURN_TIME_MINUTES) would equal-weight rows). | -1 | false | false |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Schema:
-- FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1
-- One row per (SITE_ID, CHECKID, BUSINESS_DATE). All monetary values in USD.
CREATE TABLE FACT_TRAY_CHECK_DAY_V1 (
SITE_ID ... | SELECT
LOCATION_NAME,
FULL_NAME,
SUM(TOTAL_ORDERS) AS ORDERS,
SUM(NET_SALES) AS NET_SALES,
ROUND(ROUND(SUM(NET_SALES) / NULLIF(SUM(TOTAL_ORDERS), 0), 2), 2) AS AVG_ORDER_VALUE,
ROUND(SUM(TOTAL_TIPS) / NULLIF(SUM(NET_SALES), 0) * 100, 1) AS TIP_PCT
FROM VW_SERVER_PERFORMANCE
WHERE BUSINESS_DATE B... | tray | GROUP BY LOCATION_NAME + FULL_NAME shows each server's contribution within their site. | -1 | false | false |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Schema:
-- FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1
-- One row per (SITE_ID, CHECKID, BUSINESS_DATE). All monetary values in USD.
CREATE TABLE FACT_TRAY_CHECK_DAY_V1 (
SITE_ID ... | SELECT
FULL_NAME,
LOCATION_NAME,
SUM(TOTAL_ORDERS) AS TOTAL_ORDERS,
ROUND(ROUND(SUM(NET_SALES) / NULLIF(SUM(TOTAL_ORDERS), 0), 2), 2) AS AVG_ORDER_VALUE,
SUM(NET_SALES) AS NET_SALES
FROM VW_SERVER_PERFORMANCE
WHERE BUSINESS_DATE >= DATEADD('day', -30, CURRENT_DATE())
GROUP BY FULL_NAME, LOCATION_NAM... | tray | Most orders = ORDER BY TOTAL_ORDERS DESC LIMIT 1. Include LOCATION_NAME to identify which site the top server works at. | -1 | false | false |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Schema:
-- FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1
-- One row per (SITE_ID, CHECKID, BUSINESS_DATE). All monetary values in USD.
CREATE TABLE FACT_TRAY_CHECK_DAY_V1 (
SITE_ID ... | SELECT
t.SITE_ID,
SUM(te.HOURS_WORKED * ep.HOURLY_RATE) AS LABOR_COST,
SUM(t.NET_SALES_AMOUNT) AS NET_SALES,
ROUND(SUM(te.HOURS_WORKED * ep.HOURLY_RATE) / NULLIF(SUM(t.NET_SALES_AMOUNT), 0) * 100, 2) AS LABOR_COST_PCT
FROM FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1 t
LEFT JOIN FLORAOS.TRAY.INT_TRAY_TIME_ENTRIE... | tray | Labor cost % = labor cost / net sales × 100 per site. Join time entries to check facts. | -1 | false | false |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Schema:
-- FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1
-- One row per (SITE_ID, CHECKID, BUSINESS_DATE). All monetary values in USD.
CREATE TABLE FACT_TRAY_CHECK_DAY_V1 (
SITE_ID ... | WITH baseline AS (
SELECT SITE_ID,
AVG(SUM(NET_SALES_AMOUNT)) OVER (PARTITION BY SITE_ID) AS BASELINE_AVG,
STDDEV(SUM(NET_SALES_AMOUNT)) OVER (PARTITION BY SITE_ID) AS BASELINE_STD
FROM FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1
WHERE BUSINESS_DATE >= DATEADD('day', -30, CURRENT_DATE())
... | tray | Baseline = 30-day history before this week. Deviations = z-score > 1.5 this week. | -1 | true | true |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Schema:
-- FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1
-- One row per (SITE_ID, CHECKID, BUSINESS_DATE). All monetary values in USD.
CREATE TABLE FACT_TRAY_CHECK_DAY_V1 (
SITE_ID ... | WITH emp_stats AS (
SELECT
EMPLOYEEID,
COUNT(DISTINCT CHECKID) AS TOTAL_CHECKS,
COUNT_IF(COMP_APPLIED_AMOUNT > 0) AS COMP_CHECKS,
COUNT_IF(VOID_AMOUNT > 0) AS VOID_CHECKS,
ROUND(COUNT_IF(COMP_APPLIED_AMOUNT > 0) / NULLIF(COUNT(DISTINCT CHECKID), 0), 4) AS COMP_RATE,
R... | tray | Bare 'any fraud today' query. Surfaces employees with comp_rate > 15% or void_rate > 10% on today's date. Must route to fraud_detection not daily_summary. | -1 | true | false |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Schema:
-- FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1
-- One row per (SITE_ID, CHECKID, BUSINESS_DATE). All monetary values in USD.
CREATE TABLE FACT_TRAY_CHECK_DAY_V1 (
SITE_ID ... | WITH site_stats AS (
SELECT
SITE_ID,
BUSINESS_DATE,
SUM(NET_SALES_AMOUNT) AS DAILY_NET_SALES,
AVG(SUM(NET_SALES_AMOUNT)) OVER (PARTITION BY SITE_ID
ORDER BY BUSINESS_DATE ROWS BETWEEN 13 PRECEDING AND 1 PRECEDING
) AS ROLLING_14D_AVG,
STDDEV(SUM(NET_SALES_... | tray | Generic 'anything unusual' maps to anomaly_detection. Flags sites where this week's daily sales deviate >2 std devs from their 14-day rolling baseline. | -1 | true | true |
You are a Tray POS SQL expert. Generate a valid Snowflake SQL SELECT query for the question below. Output the SQL only — no explanation.
Schema:
-- FLORAOS.TRAY.FACT_TRAY_CHECK_DAY_V1
-- One row per (SITE_ID, CHECKID, BUSINESS_DATE). All monetary values in USD.
CREATE TABLE FACT_TRAY_CHECK_DAY_V1 (
SITE_ID ... | SELECT
EMPLOYEE_ID,
ROUND(SUM(HOURS_WORKED), 2) AS TOTAL_HOURS
FROM FLORAOS.TRAY.INT_TRAY_TIME_ENTRIES_V1
WHERE BUSINESS_DATE = DATEADD('day', -1, CURRENT_DATE())
GROUP BY EMPLOYEE_ID
ORDER BY TOTAL_HOURS DESC | tray | Hours worked from time clock entries. INT_TRAY_TIME_ENTRIES_V1 has HOURS_WORKED per EMPLOYEE_ID per BUSINESS_DATE. | -1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T2.title FROM sales AS T1 INNER JOIN titles AS T2 ON T1.title_id = T2.title_id WHERE STRFTIME('%Y', T1.ord_date) = '1992' ORDER BY T1.qty DESC LIMIT 1 | bird_train | total quantity refers to qty; most ordered quantity refers to order with the highest quantity where MAX(count(qty)); date refers to ord_date; year 1992 refers to YEAR(ord_date) = 1992 | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T2.title, T2.price, T2.pubdate FROM sales AS T1 INNER JOIN titles AS T2 ON T1.title_id = T2.title_id WHERE T1.payterms = 'ON invoice' | bird_train | publication date refers to pubdate; payment terms refers to payterms; payterms = 'ON invoice' | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.title FROM titles AS T1 INNER JOIN roysched AS T2 ON T1.title_id = T2.title_id WHERE T2.lorange = 0 AND T2.royalty >= 10 | bird_train | at least 10% royalty refers to royalty > = 10; minimum range is synonym for low range which refers to lorange; without minimum range amount refers to lorange <> 0 | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.title, T2.lorange FROM titles AS T1 INNER JOIN roysched AS T2 ON T1.title_id = T2.title_id ORDER BY T2.royalty DESC LIMIT 1 | bird_train | minimum range is synonym for low range which refers to lorange | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.title, T2.pub_name FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T2.country = 'USA' | bird_train | publisher name refers to pub_name; | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.title, T2.qty FROM titles AS T1 INNER JOIN sales AS T2 ON T1.title_id = T2.title_id INNER JOIN stores AS T3 ON T2.stor_id = T3.stor_id WHERE T2.qty > 20 AND T3.state = 'CA' | bird_train | qty is abbreviation for quantity; sales of quantity more than 20 refers to qty>20; store refers to stor_name | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T3.stor_id, T2.title FROM sales AS T1 INNER JOIN titles AS T2 ON T1.title_id = T2.title_id INNER JOIN stores AS T3 ON T3.stor_id = T1.stor_id WHERE T3.stor_id = ( SELECT stor_id FROM sales GROUP BY stor_id ORDER BY SUM(qty) DESC LIMIT 1 ) GROUP BY T3.stor_id, T2.title ORDER BY SUM(T1.qty) ASC LIMIT 1 | bird_train | qty is abbreviation for quantity; highest quantity refers to MAX(qty); least quantity refers to MIN(qty) | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T2.stor_name , CAST(SUM(CASE WHEN payterms = 'Net 30' THEN qty ELSE 0 END) AS REAL) * 100 / SUM(qty) FROM sales AS T1 INNER JOIN stores AS T2 ON T1.stor_id = T2.stor_id WHERE T1.stor_id = '7066' GROUP BY T2.stor_name | bird_train | store with ID 7066 refers to stor_ID = '7066'; 'Net 60' payment terms refers to payterm = 'Net 60'; qty is abbreviation for quantity; percentage = DIVIDE(payterms = 'Net 60', sum(qty))*100 | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T2.pub_name, AVG(T1.ytd_sales) FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T1.pub_id = '0877' GROUP BY T2.pub_name | bird_train | publisher id refers to pub_id; publisher name refers to pub_name; average year to date sales = AVG(ytd_sales) | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT STRFTIME('%Y', hire_date) FROM employee GROUP BY STRFTIME('%Y', hire_date) ORDER BY COUNT(emp_id) DESC LIMIT 1 | bird_train | most hired employees refers to MAX(count(emp_id)) | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.fname, T1.lname FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id WHERE T1.job_lvl = T2.max_lvl | bird_train | maximum level in their job designation refers to job_lvl = MAX(max_lvl) | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.fname, T1.lname, T3.job_desc FROM employee AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id INNER JOIN jobs AS T3 ON T1.job_id = T3.job_id WHERE T2.pub_name = 'GGG&G' | bird_train | name = fname, lname; job description refers to job_desc; publisher refers pub_name | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT DISTINCT T2.pub_name, T1.type FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id ORDER BY T2.pub_name | bird_train | publisher name refers to pub_name | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T2.pub_name FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE STRFTIME('%Y', T1.pubdate) = '1991' GROUP BY T1.pub_id, T2.pub_name ORDER BY COUNT(T1.title_id) DESC LIMIT 1 | bird_train | most title published refers to MAX(count(title_id); published in 1991 refers to YEAR(pubdate) = 1991 | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.title FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T2.pub_name = 'Binnet & Hardley' ORDER BY T1.price DESC LIMIT 1 | bird_train | published by refers to pub_name | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T3.au_fname, T3.au_lname FROM titles AS T1 INNER JOIN titleauthor AS T2 ON T1.title_id = T2.title_id INNER JOIN authors AS T3 ON T2.au_id = T3.au_id WHERE T1.type = 'business' | bird_train | business title refers to title under business where type = 'business' | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.title_id, T1.ytd_sales FROM titles AS T1 INNER JOIN titleauthor AS T2 ON T1.title_id = T2.title_id INNER JOIN authors AS T3 ON T2.au_id = T3.au_id WHERE T3.contract = 0 | bird_train | year to date sales refers to ytd_sales; not on contract refers to contract = 0 | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.title FROM titles AS T1 INNER JOIN titleauthor AS T2 ON T1.title_id = T2.title_id INNER JOIN authors AS T3 ON T2.au_id = T3.au_id WHERE T3.contract = 0 AND T3.state = 'CA' ORDER BY T1.ytd_sales DESC LIMIT 1 | bird_train | year to date sales refers to ytd_sales; on contract refers to contract = 1 | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT CAST(SUM(CASE WHEN T2.job_desc IN ('Editor', 'Designer') THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.job_id) FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id | bird_train | Editor or Auditor are job description which refers to job_desc; percentage = DIVIDE(count(job_desc = 'Editor' or job_desc = 'Auditor'), count(emp_id))*100 | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.title FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T1.ytd_sales > ( SELECT AVG(ytd_sales) FROM titles ) | bird_train | year to date sales refers to ytd_sales; average order = AVG(ytd_sales) | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T2.max_lvl FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id ORDER BY T1.hire_date LIMIT 1 | bird_train | highest job level refers to MAX(job_lvl); hired the earliest refers to MIN(hire_date) | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T2.city FROM sales AS T1 INNER JOIN stores AS T2 ON T1.stor_id = T2.stor_id GROUP BY T2.city ORDER BY SUM(T1.qty) DESC LIMIT 1 | bird_train | qty is abbreviation for quantity; highest sales quantity refers to MAX(qty) | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T2.stor_name FROM sales AS T1 INNER JOIN stores AS T2 ON T1.stor_id = T2.stor_id INNER JOIN titles AS T3 ON T1.title_id = T3.title_id WHERE T3.title = 'Life Without Fear' | bird_train | store name refers to stor_name | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT COUNT(T1.stor_id) FROM sales AS T1 INNER JOIN stores AS T2 ON T1.stor_id = T2.stor_id INNER JOIN titles AS T3 ON T1.title_id = T3.title_id WHERE T2.state = 'Massachusetts' | bird_train | Massachusetts is a state | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T2.country FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T1.title = 'Life Without Fear' | bird_train | Life Without Fear is book title | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T2.pub_name FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id ORDER BY T1.price DESC LIMIT 1 | bird_train | most expensive book refers to MAX(price) | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT COUNT(DISTINCT T1.pub_id) FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T2.country = 'USA' AND T1.price > 15 | bird_train | are over $15 refers to price>15 | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT CAST(SUM(T2.qty) AS REAL) / COUNT(T1.title_id) FROM titles AS T1 INNER JOIN sales AS T2 ON T1.title_id = T2.title_id WHERE T1.title = 'Life Without Fear' | bird_train | qty is abbreviation for quantity; average quantity order = AVG(qty) | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT title FROM titles WHERE type = 'business' ORDER BY price LIMIT 1 | bird_train | business books refers to type = 'business'; cheapest book refers to MIN(price) | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT emp_id FROM employee WHERE minit = '' ORDER BY job_lvl DESC LIMIT 1 | bird_train | highest employee refers to employee with the highest job level; MAX(job_lvl) | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.contract FROM authors AS T1 INNER JOIN titleauthor AS T2 ON T1.au_id = T2.au_id INNER JOIN titles AS T3 ON T2.title_id = T3.title_id WHERE T3.title = 'Sushi, Anyone?' | bird_train | contract = 1 means on contract; contract = 0 means not on contract | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.fname, T1.minit, T1.lname FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id ORDER BY T1.job_lvl DESC LIMIT 1 | bird_train | highest job level refers to MAX(job_lvl) | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T2.job_desc FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id WHERE T1.fname = 'Pedro' AND T1.minit = 'S' AND T1.lname = 'Afonso' | bird_train | job title means job description which refers to job_desc | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T2.max_lvl - T1.job_lvl FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id WHERE T1.fname = 'Diego' AND T1.minit = 'W' AND T1.lname = 'Roel' | bird_train | max level for his position refers to max_lvl; job level refers to job_lvl; level left to reach the max = SUBTRACT(max_lvl, job_lvl) | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT DISTINCT T1.type FROM titles AS T1 INNER JOIN sales AS T2 ON T1.title_id = T2.title_id WHERE STRFTIME('%Y-%m-%d', T2.ord_date) = '1993-05-29' | bird_train | sold on refers to ord_date | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.pr_info FROM pub_info AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T2.country = 'France' | bird_train | French publisher means publisher in France where country = 'France' | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T2.city FROM employee AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T1.fname = 'Victoria' AND T1.minit = 'P' AND T1.lname = 'Ashworth' | bird_train | 1 | false | false | |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT COUNT(T1.ord_num) FROM sales AS T1 INNER JOIN stores AS T2 ON T1.stor_id = T2.stor_id WHERE T2.city = 'Remulade' | bird_train | Remulade is a city; sales in the store refers to ord_num | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT DISTINCT T1.title, T1.type, T1.price FROM titles AS T1 INNER JOIN roysched AS T2 ON T1.title_id = T2.title_id WHERE T2.royalty > ( SELECT CAST(SUM(royalty) AS REAL) / COUNT(title_id) FROM roysched ) | bird_train | average royalty rate = DIVIDE(SUM(royalty), COUNT(title_id)) | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT DISTINCT T1.title, T1.type, T1.price FROM titles AS T1 INNER JOIN sales AS T2 ON T1.title_id = T2.title_id WHERE T2.ord_date LIKE '1994%' AND T2.Qty < ( SELECT CAST(SUM(T4.qty) AS REAL) / COUNT(T3.title_id) FROM titles AS T3 INNER JOIN sales AS T4 ON T3.title_id = T4.title_id ) | bird_train | orders in 1994 refers to YEAR(ord_date) = 1994; order quantity refers to number of order expressed by ord_num; average order quantity = DIVIDE(SUM(ord_num), COUNT(title_id)) | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.title, T1.type, T1.price FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T2.pub_name = 'New Moon Books' ORDER BY T1.price | bird_train | Eric the Read Books is a publisher which refers to pub_name; | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.title FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id INNER JOIN roysched AS T3 ON T1.title_id = T3.title_id WHERE T2.country = 'USA' ORDER BY T1.royalty DESC | bird_train | US publisher refers publisher in the US where country = 'USA'; | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.title, T2.pub_name, T1.price FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T1.notes = 'Helpful hints on how to use your electronic resources to the best advantage.' | bird_train | publisher refers to pub_name; about the title refers to notes | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE authors
(
au_id TEXT
primary key,
au_lname TEXT not null,
au_fname TEXT not null,
phone TEXT not null,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
... | SELECT T1.title, T2.pub_name, T1.ytd_sales FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T1.notes = 'Carefully researched study of the effects of strong emotions on the body. Metabolic charts included.' | bird_train | year to date sales refers to ytd_sales; about the title refers to notes | 1 | false | false |
You are an expert SQL assistant. Convert the question to a valid SQL query.
Database schema:
CREATE TABLE state
(
StateCode TEXT
constraint state_pk
primary key,
State TEXT,
Region TEXT
)
CREATE TABLE callcenterlogs
(
"Date received" DATE,
"Complaint ID" TEXT,
"rand ... | SELECT `Date received` FROM callcenterlogs WHERE ser_time = ( SELECT MAX(ser_time) FROM callcenterlogs ) | bird_train | day received refers to "Date received"; most verbose complaint refers to MAX(ser_time); | 1 | false | false |
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