This query reports the amount of business that was billed, shipped, and returned.

The Pricing Summary Report Query provides a summary pricing report for all line items shipped as of a given date. The date is within 60-120 days of the greatest ship date contained in the database.

The query lists totals for extended price, discounted extended price, discounted extended price plus tax, average quantity, average extended price, and average discount. These aggregates are grouped by RETURNFLAG and LINESTATUS, and listed in ascending order of RETURNFLAG and LINESTATUS. A count of the number of line items in each group is included.

select
       l_returnflag,
       l_linestatus,
       sum(l_quantity) as sum_qty,
       sum(l_extendedprice) as sum_base_price,
       sum(l_extendedprice * (1-l_discount)) as sum_disc_price,
       sum(l_extendedprice * (1-l_discount) * (1+l_tax)) as sum_charge,
       avg(l_quantity) as avg_qty,
       avg(l_extendedprice) as avg_price,
       avg(l_discount) as avg_disc,
       count(*) as count_order
 from
       lineitem
 where
       l_shipdate <= mdy (12, 01, 1998 ) - 90 units day
 group by
       l_returnflag,
       l_linestatus
 order by
       l_returnflag,
       l_linestatus;

Values for the following substitution parameter must be generated and used to build the executable query text: 1. DELTA is randomly selected within [60. 120].

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

• 90

Sample Output

This query finds which supplier should be selected to place an order for a given part in a given region

The Minimum Cost Supplier Query finds, in a given region, for each part of a certain type and size, the supplier who can supply it at minimum cost. If several suppliers in that region offer the desired part type and size at the same (minimum) cost, the query lists the parts from suppliers with the 100 highest account balances. For each supplier, the query lists the supplier's account balance, name and nation; the part's number and manufacturer; the supplier's address, phone number and comment information.

Return the first 100 selected rows

SELECT FIRST 100
     s_acctbal,
     s_name,
     n_name,
     p_partkey,
     p_mfgr,
     s_address,
     s_phone,
     s_comment
 FROM part, supplier, partsupp, nation, region
WHERE
     p_partkey = ps_partkey
     AND s_suppkey = ps_suppkey
     AND p_size = 15
     AND p_type LIKE '%BRASS'
     AND s_nationkey = n_nationkey
     AND n_regionkey = r_regionkey
     AND r_name = 'EUROPE'
     AND ps_supplycost = (
		SELECT
			MIN(ps_supplycost)
		FROM
			partsupp,
			supplier,
			nation,
			region
		WHERE
			p_partkey = ps_partkey
			AND s_suppkey = ps_suppkey
			AND s_nationkey = n_nationkey
			AND n_regionkey = r_regionkey
			AND r_name = 'EUROPE'
     )
ORDER BY s_acctbal DESC, n_name, s_name, p_partkey

Values for the following substitution parameter must be generated and used to build the executable query text:

1. SIZE is randomly selected within [1. 50]
2. TYPE is randomly selected within the list Syllable 3 defined for Types in TPCH Clause 4.2.2.13
3. REGION is randomly selected within the list of values defined for R_NAME in 4.2.3.

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. SIZE = 15
2. TYPE = BRASS
3. REGION = EUROPE

Sample Output

This query retrieves the 10 unshipped orders with the highest value.

The Shipping Priority Query retrieves the shipping priority and potential revenue, defined as the sum of l_extendedprice * (1-l_discount), of the orders having the largest revenue among those that had not been shipped as of a given date. Orders are listed in decreasing order of revenue. If more than 10 unshipped orders exist, only the 10 orders with the largest revenue are listed.

Return the first 10 selected rows

SELECT FIRST 10
     l_orderkey,
     SUM(l_extendedprice * (1 - l_discount)) AS revenue,
     o_orderdate,
     o_shippriority
 FROM  customer, orders, lineitem
WHERE c_mktsegment = 'BUILDING'
  AND c_custkey = o_custkey
  AND l_orderkey = o_orderkey
  AND o_orderdate < MDY(3, 15, 1995)
  AND l_shipdate > MDY(3, 15, 1995)
GROUP BY l_orderkey, o_orderdate, o_shippriority
ORDER BY revenue DESC,  o_orderdate

Values for the following substitution parameters must be generated and used to build the executable query text:

1. SEGMENT is randomly selected within the list of values defined for Segments in Clause 4.2.2.13
2. DATE is a randomly selected day within [1995-03-01 .. 1995-03-31].

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. SEGMENT = BUILDING
2. DATE = 1995-03-15

Sample Output

This query determines how well the order priority system is working and gives an assessment of customer satisfaction.

The Order Priority Checking Query counts the number of orders ordered in a given quarter of a given year in which at least one lineitem was received by the customer later than its committed date. The query lists the count of such orders for each order priority sorted in ascending priority order.

SELECT o_orderpriority, COUNT(*) AS order_count
  FROM orders
 WHERE o_orderdate >= MDY (7, 1, 1993)
   AND o_orderdate < MDY (7, 1, 1993) + 3 UNITS MONTH
   AND EXISTS (
      SELECT *
        FROM lineitem
       WHERE l_orderkey = o_orderkey
         AND l_commitdate < l_receiptdate
     )
GROUP BY o_orderpriority
ORDER BY o_orderpriority

Values for the following substitution parameter must be generated and used to build the executable query text:

1. DATE is the first day of a randomly selected month between the first month of 1993 and the 10th month of 1997

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. DATE = 1993-07-01

Sample Output

This query lists the revenue volume done through local suppliers.

The Local Supplier Volume Query lists for each nation in a region the revenue volume that resulted from lineitem transactions in which the customer ordering parts and the supplier filling them were both within that nation. The query is run in order to determine whether to institute local distribution centers in a given region. The query considers only parts ordered in a given year. The query displays the nations and revenue volume in descending order by revenue. Revenue volume for all qualifying lineitems in a particular nation is defined as sum(l_extendedprice * (1 - l_discount)).

SELECT n_name, SUM(l_extendedprice * (1 - l_discount)) AS revenue
  FROM customer, orders, lineitem, supplier, nation, region
 WHERE c_custkey = o_custkey
   AND l_orderkey = o_orderkey
   AND l_suppkey = s_suppkey
   AND c_nationkey = s_nationkey
   AND s_nationkey = n_nationkey
   AND n_regionkey = r_regionkey
   AND r_name = 'ASIA'
   AND o_orderdate >= MDY(1,1,1994)
   AND o_orderdate < MDY(1,1,1994) + 1 UNITS YEAR
GROUP BY n_name
ORDER BY revenue DESC

Values for the following substitution parameters must be generated and used to build the executable query text:

1. REGION is randomly selected within the list of values defined for R_NAME in C;aise 4.2.3
2. DATE is the first of January of a randomly selected year within [1993 .. 1997]

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. REGION = ASIA
2. DATE = 1994-01-01

Sample Output

This query quantifies the amount of revenue increase that would have resulted from eliminating certain companywide discounts in a given percentage range in a given year. Asking this type of "what if" query can be used to look for ways to increase revenues.

The Forecasting Revenue Change Query considers all the lineitems shipped in a given year with discounts between DISCOUNT-0.01 and DISCOUNT+0.01. The query lists the amount by which the total revenue would have increased if these discounts had been eliminated for lineitems with l_quantity less than quantity. Note that the potential revenue increase is equal to the sum of [l_extendedprice * l_discount] for all lineitems with discounts and quantities in the qualifying range.

SELECT
     SUM(l_extendedprice * l_discount) AS revenue
FROM
     lineitem
WHERE
     l_shipdate >= MDY(1,1,1994)
     AND l_shipdate < MDY(1,1,1994) + 1 UNITS YEAR
     AND l_discount BETWEEN .06 - 0.01 AND .06 + 0.010001
     AND l_quantity < 24

Values for the following substitution parameters must be generated and used to build the executable query text:

1. DATE is the first of January of a randomly selected year within [1993 .. 1997]
2. DISCOUNT is randomly selected within [0.02 .. 0.09]
3. QUANTITY is randomly selected within [24 .. 25]

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. DATE = 1994-01-01
2. DISCOUNT = 0.06
3. QUANTITY = 24

Sample Output

This query determines the value of goods shipped between certain nations to help in the re-negotiation of shipping contracts.

The Volume Shipping Query finds, for two given nations, the gross discounted revenues derived from lineitems in which parts were shipped from a supplier in either nation to a customer in the other nation during 1995 and 1996. The query lists the supplier nation, the customer nation, the year, and the revenue from shipments that took place in that year. The query orders the answer by Supplier nation, Customer nation, and year (all ascending).

SELECT
     supp_nation,
     cust_nation,
     l_year,
     SUM(volume) AS revenue
FROM
     (
		SELECT
			n1.n_name AS supp_nation,
			n2.n_name AS cust_nation,
			YEAR(l_shipdate) AS l_year,
			l_extendedprice * (1 - l_discount) AS volume
		FROM
			supplier,
			lineitem,
			orders,
			customer,
			nation n1,
			nation n2
		WHERE
			s_suppkey = l_suppkey
			AND o_orderkey = l_orderkey
			AND c_custkey = o_custkey
			AND s_nationkey = n1.n_nationkey
			AND c_nationkey = n2.n_nationkey
			AND (
				(n1.n_name = 'FRANCE' AND n2.n_name = 'GERMANY')
				OR (n1.n_name = 'GERMANY' AND n2.n_name = 'FRANCE')
			)
			AND l_shipdate BETWEEN MDY(1,1,1995) AND MDY(12,31,1996)
     ) AS shipping
GROUP BY
     supp_nation,
     cust_nation,
     l_year
ORDER BY
     supp_nation,
     cust_nation,
     l_year

Values for the following substitution parameters must be generated and used to build the executable query text:

1. NATION1 is randomly selected within the list of values defined for N_NAME in Clause 4.2.3
2. NATION2 is randomly selected within the list of values defined for N_NAME in Clause 4.2.3 and must be different from the value selected for NATION1 in item 1 above.
3. QUANTITY is randomly selected within [24 .. 25]

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. NATION1 = FRANCE
2. NATION2 = GERMANY

Sample Output

This query determines how the market share of a given nation within a given region has changed over two years for a given part type.

The market share for a given nation within a given region is defined as the fraction of the revenue, the sum of [l_extendedprice * (1-l_discount)], from the products of a specified type in that region that was supplied by suppliers from the given nation. The query determines this for the years 1995 and 1996 presented in this order.

SELECT
     o_year,
     SUM(CASE
		WHEN nation = 'BRAZIL' THEN volume
		ELSE 0
     END) / SUM(volume) AS mkt_share
FROM
     (
		SELECT
			YEAR(o_orderdate) AS o_year,
			l_extendedprice * (1 - l_discount) AS volume,
			n2.n_name AS nation
		FROM
			part,
			supplier,
			lineitem,
			orders,
			customer,
			nation n1,
			nation n2,
			region
		WHERE
			p_partkey = l_partkey
			AND s_suppkey = l_suppkey
			AND l_orderkey = o_orderkey
			AND o_custkey = c_custkey
			AND c_nationkey = n1.n_nationkey
			AND n1.n_regionkey = r_regionkey
			AND r_name = 'AMERICA'
			AND s_nationkey = n2.n_nationkey
			AND o_orderdate BETWEEN CAST ('1995-01-01' AS DATE) AND CAST ('1996-12-31' AS DATE)
			AND p_type = 'ECONOMY ANODIZED STEEL'
     ) AS all_nations
GROUP BY
     o_year
ORDER BY
     o_year

Values for the following substitution parameters must be generated and used to build the executable query text:

1. NATION is randomly selected within the list of values defined for N_NAME in Clause 4.2.3
2. REGION is the value defined in Clause 4.2.3 for R_NAME where R_REGIONKEY corresponds to N_REGIONKEY for the selected NATION in item 1 above.
3. TYPE is randomly selected within the list of 3-syllable strings defined for Types in Clause 4.2.2.13

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. NATION = BRAZIL
2. REGION = AMERICA
3. TYPE = ECONOMY ANODIZED STEEL

Sample Output

This query determines how much profit is made on a given line of parts, broken out by supplier nation and year.

The Product Type Profit Measure Query finds, for each nation and each year, the profit for all parts ordered in that year that contain a specified substring in their names and that were filled by a supplier in that nation. The profit is defined as the sum of [(l_extendedprice*(1-l_discount)) - (ps_supplycost * l_quantity)] for all lineitems describing parts in the specified line. The query lists the nations in ascending alphabetical order and, for each nation, the year and profit in descending order by year (most recent first).

SELECT
     nation,
     o_year,
     SUM(amount) AS sum_profit
FROM
     (
		SELECT
			n_name AS nation,
			YEAR(o_orderdate) AS o_year,
			l_extendedprice * (1 - l_discount) - ps_supplycost * l_quantity AS amount
		FROM
			part,
			supplier,
			lineitem,
			partsupp,
			orders,
			nation
		WHERE
			s_suppkey = l_suppkey
			AND ps_suppkey = l_suppkey
			AND ps_partkey = l_partkey
			AND p_partkey = l_partkey
			AND o_orderkey = l_orderkey
			AND s_nationkey = n_nationkey
			AND p_name LIKE '%green%'
     ) AS profit
GROUP BY
     nation,
     o_year
ORDER BY
     nation,
     o_year DESC

Values for the following substitution parameter must be generated and used to build the executable query text:

1. COLOR is randomly selected within the list of values defined for the generation of P_NAME in Clause 4.2.3

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. COLOR = green

Sample Output

The query identifies customers who might be having problems with the parts that are shipped to them.

The Returned Item Reporting Query finds the top 20 customers, in terms of their effect on lost revenue for a given quarter, who have returned parts. The query considers only parts that were ordered in the specified quarter. The query lists the customer's name, address, nation, phone number, account balance, comment information and revenue lost. The customers are listed in descending order of lost revenue. Revenue lost is defined as sum(l_extendedprice*(1-l_discount)) for all qualifying lineitems.

Return the first 20 selected rows

SELECT FIRST 20
     c_custkey,
     c_name,
     SUM(l_extendedprice * (1 - l_discount)) AS revenue,
     c_acctbal,
     n_name,
     c_address,
     c_phone,
     c_comment
FROM
     customer,
     orders,
     lineitem,
     nation
WHERE
     c_custkey = o_custkey
     AND l_orderkey = o_orderkey
     AND o_orderdate >= MDY  (10,1,1993)
     AND o_orderdate < MDY(10,1,1993) + 3 UNITS MONTH
     AND l_returnflag = 'R'
     AND c_nationkey = n_nationkey
GROUP BY
     c_custkey,
     c_name,
     c_acctbal,
     c_phone,
     n_name,
     c_address,
     c_comment
ORDER BY
     revenue DESC

Values for the following substitution parameter must be generated and used to build the executable query text:

1. DATE is the first day of a randomly selected month from the second month of 1993 to the first month of 1995

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. DATE = 1993-10-01

Sample Output

This query finds the most important subset of suppliers' stock in a given nation.

The Important Stock Identification Query finds, from scanning the available stock of suppliers in a given nation, all the parts that represent a significant percentage of the total value of all available parts. The query displays the part number and the value of those parts in descending order of value.

SELECT
     FIRST 10
     ps_partkey,
     SUM(ps_supplycost * ps_availqty) AS value
FROM
     partsupp,
     supplier,
     nation
WHERE
     ps_suppkey = s_suppkey
     AND s_nationkey = n_nationkey
     AND n_name = 'GERMANY'
GROUP BY
     ps_partkey HAVING
		SUM(ps_supplycost * ps_availqty) > (
			SELECT
				SUM(ps_supplycost * ps_availqty) * 0.0001000000e-2
			FROM
				partsupp,
				supplier,
				nation
			WHERE
				ps_suppkey = s_suppkey
				AND s_nationkey = n_nationkey
				AND n_name = 'GERMANY'
		)
ORDER BY
     value DESC

Values for the following substitution parameter must be generated and used to build the executable query text:

1. NATION is randomly selected within the list of values defined for N_NAME in Clause 4.2.3
2. FRACTION is chosen as 0.0001 / SF

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. NATION = GERMANY
2. FRACTION = 0.0001

Sample Output

This query determines whether selecting less expensive modes of shipping is negatively affecting the critical-priority orders by causing more parts to be received by customers after the committed date.

The Shipping Modes and Order Priority Query counts, by ship mode, for lineitems actually received by customers in a given year, the number of lineitems belonging to orders for which the l_receiptdate exceeds the l_commitdate for two different specified ship modes. Only lineitems that were actually shipped before the l_commitdate are considered. The late lineitems are partitioned into two groups, those with priority URGENT or HIGH, and those with a priority other than URGENT or HIGH.

SELECT
     l_shipmode,
     SUM(CASE
		WHEN o_orderpriority = '1-URGENT'
			OR o_orderpriority = '2-HIGH'
			THEN 1
		ELSE 0
     END) AS high_line_count,
     SUM(CASE
		WHEN o_orderpriority <> '1-URGENT'
			AND o_orderpriority <> '2-HIGH'
			THEN 1
		ELSE 0
     END) AS low_line_count
FROM
     orders,
     lineitem
WHERE
     o_orderkey = l_orderkey
     AND l_shipmode IN ('MAIL', 'SHIP')
     AND l_commitdate < l_receiptdate
     AND l_shipdate < l_commitdate
     AND l_receiptdate >= MDY(1,1, 1994)
     AND l_receiptdate < MDY(1,1,1994) + 1 UNITS YEAR
GROUP BY
     l_shipmode
ORDER BY
     l_shipmode

Values for the following substitution parameters must be generated and used to build the executable query text:

1. SHIPMODE1 is randomly selected within the list of values defined for Modes in Clause 4.2.2.13
2. SHIPMODE2 is randomly selected within the list of values defined for Modes in Clause 4.2.2.13 and must be different from the value selected for SHIPMODE1 in item 1
3. DATE is the first of January of a randomly selected year within [1993 .. 1997]

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. SHIPMODE1 = MAIL
2. SHIPMODE2 = SHIP
3. DATE = 1994-01-01

Sample Output

This query seeks relationships between customers and the size of their orders.

This query determines the distribution of customers by the number of orders they have made, including customers who have no record of orders, past or present. It counts and reports how many customers have no orders, how many have 1, 2, 3, etc. A check is made to ensure that the orders counted do not fall into one of several special categories of orders. Special categories are identified in the order comment column by looking for a particular pattern.

SELECT
          c_count,
          COUNT(*) AS custdist
  FROM (
          SELECT
                  c_custkey,
                  COUNT(o_orderkey) AS c_count
          FROM
                  (SELECT * FROM customer
                  LEFT OUTER JOIN orders ON
                    c_custkey = o_custkey AND
                    o_comment NOT LIKE '%special%requests%') c_customer
          GROUP BY
                  c_custkey
          ) c_orders
  GROUP BY
          c_count
  ORDER BY
          custdist DESC,
          c_count DESC

Values for the following substitution parameters must be generated and used to build the executable query text:

1. WORD1 is randomly selected from 4 possible values: special, pending, unusual, express
2. WORD2 is randomly selected from 4 possible values: packages, requests, accounts, deposits

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. WORD1 = special
2. WORD2 = requests

Sample Output

This query monitors the market response to a promotion such as TV advertisements or a special campaign

The Promotion Effect Query determines what percentage of the revenue in a given year and month was derived from promotional parts. The query considers only parts actually shipped in that month and gives the percentage. Revenue is defined as (l_extendedprice * (1-l_discount)).

SELECT
     100.00 * SUM(CASE
		WHEN p_type LIKE 'PROMO%'
			THEN l_extendedprice * (1 - l_discount)
		ELSE 0
     END) / SUM(l_extendedprice * (1 - l_discount)) AS promo_revenue
FROM
     lineitem,
     part
WHERE
     l_partkey = p_partkey
     AND l_shipdate >= MDY(9,1,1995)
     AND l_shipdate < MDY(9,1,1995) + 1 UNITS MONTH

Values for the following substitution parameters must be generated and used to build the executable query text:

1. DATE is the first day of a month randomly selected from a random year within [1993 .. 1997]

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. DATE = 1995-09-01

Sample Output

This query finds out how many suppliers can supply parts with given attributes. It might be used, for example, to determine whether there is a sufficient number of suppliers for heavily ordered parts

The Parts/Supplier Relationship Query counts the number of suppliers who can supply parts that satisfy a particular customer's requirements. The customer is interested in parts of eight different sizes as long as they are not of a given type, not of a given brand, and not from a supplier who has had complaints registered at the Better Business Bureau. Results must be presented in descending count and ascending brand, type, and size.

SELECT 
     p_brand,
     p_type,
     p_size,
     COUNT(DISTINCT ps_suppkey) AS supplier_cnt
FROM
     partsupp,
     part
WHERE
     p_partkey = ps_partkey
     AND p_brand <> 'Brand#45'
     AND p_type NOT LIKE 'MEDIUM POLISHED%'
     AND p_size IN (49, 14, 23, 45, 19, 3, 36, 9)
     AND ps_suppkey NOT IN (
		SELECT
			s_suppkey
		FROM
			supplier
		WHERE
			s_comment LIKE '%Customer%Complaints%'
     )
GROUP BY
     p_brand,
     p_type,
     p_size
ORDER BY
     supplier_cnt DESC,
     p_brand,
     p_type,
     p_size

Values for the following substitution parameters must be generated and used to build the executable query text:

1. BRAND = Brand#MN where M and N are two single character strings representing two numbers randomly and independently selected within [1 .. 5];
2. TYPE is made of the first 2 syllables of a string randomly selected within the list of 3-syllable strings defined for Types in Clause 4.2.2.13;
3. SIZE1 is randomly selected as a set of eight different values within [1 .. 50];
4. SIZE2 is randomly selected as a set of eight different values within [1 .. 50];
5. SIZE3 is randomly selected as a set of eight different values within [1 .. 50];
6. SIZE4 is randomly selected as a set of eight different values within [1 .. 50];
7. SIZE5 is randomly selected as a set of eight different values within [1 .. 50];
8. SIZE6 is randomly selected as a set of eight different values within [1 .. 50];
9. SIZE7 is randomly selected as a set of eight different values within [1 .. 50];
10. SIZE8 is randomly selected as a set of eight different values within [1 .. 50].

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. BRAND = Brand#45
2. TYPE = MEDIUM POLISHED .
3. SIZE1 = 49
4. SIZE2 = 14
5. SIZE3 = 23
6. SIZE4 = 45
7. SIZE5 = 19
8. SIZE6 = 3
9. SIZE7 = 36
10. SIZE8 = 9.

Sample Output

This query determines how much average yearly revenue would be lost if orders were no longer filled for small quantities of certain parts. This may reduce overhead expenses by concentrating sales on larger shipments.

The Small-Quantity-Order Revenue Query considers parts of a given brand and with a given container type and determines the average lineitem quantity of such parts ordered for all orders (past and pending) in the 7-year database. What would be the average yearly gross (undiscounted) loss in revenue if orders for these parts with a quantity of less than 20% of this average were no longer taken?

SELECT
     SUM(l_extendedprice) / 7.0 AS avg_yearly
FROM
     lineitem,
     part
WHERE
     p_partkey = l_partkey
     AND p_brand = 'Brand#23'
     AND p_container = 'MED BOX'
     AND l_quantity < (
		SELECT
			2e-1 * AVG(l_quantity)
		FROM
			lineitem
		WHERE
			l_partkey = p_partkey
     )

Values for the following substitution parameters must be generated and used to build the executable query text:

1. BRAND = 'Brand#MN' where MN is a two character string representing two numbers randomly and independently selected within [1 .. 5];
2. CONTAINER is randomly selected within the list of 2-syllable strings defined for Containers in Clause 4.2.2.13.

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. BRAND = Brand#23;
2. CONTAINER = MED BOX.

Sample Output

The Large Volume Customer Query ranks customers based on their having placed a large quantity order. Large quantity orders are defined as those orders whose total quantity is above a certain level.

The Large Volume Customer Query finds a list of the top 100 customers who have ever placed large quantity orders.

The query lists the customer name, customer key, the order key, date and total price and the quantity for the order.

select FIRST 100
	c_name,
	c_custkey,
	o_orderkey,
	o_orderdate,
	o_totalprice,
	sum(l_quantity)
from
	customer,
	orders,
	lineitem
where
	o_orderkey in (
	select
	l_orderkey
	from
	lineitem
	group by
	l_orderkey having
		sum(l_quantity) > 300
	)
	and c_custkey = o_custkey
	and o_orderkey = l_orderkey
group by
	c_name,
	c_custkey,
	o_orderkey,
	o_orderdate,
	o_totalprice
order by
	o_totalprice desc,
	o_orderdate

Values for the following substitution parameters must be generated and used to build the executable query text:

1. QUANTITY is randomly selected within [312..315].

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. QUANTITY = 300

Sample Output

The Discounted Revenue Query reports the gross discounted revenue attributed to the sale of selected parts handled in a particular manner. This query is an example of code such as might be produced programmatically by a data mining tool.

The Discounted Revenue query finds the gross discounted revenue for all orders for three different types of parts that were shipped by air and delivered in person. Parts are selected based on the combination of specific brands, a list of containers, and a range of sizes.

SELECT
     SUM(l_extendedprice* (1 - l_discount)) AS revenue
FROM
     lineitem,
     part
WHERE
     (
		p_partkey = l_partkey
		AND p_brand = 'Brand#12'
		AND p_container IN ('SM CASE', 'SM BOX', 'SM PACK', 'SM PKG')
		AND l_quantity >= 1 AND l_quantity <= 1 + 10
		AND p_size BETWEEN 1 AND 5
		AND l_shipmode IN ('AIR', 'AIR REG')
		AND l_shipinstruct = 'DELIVER IN PERSON'
     )
     OR
     (
		p_partkey = l_partkey
		AND p_brand = 'Brand#23'
		AND p_container IN ('MED BAG', 'MED BOX', 'MED PKG', 'MED PACK')
		AND l_quantity >= 10 AND l_quantity <= 10 + 10
		AND p_size BETWEEN 1 AND 10
		AND l_shipmode IN ('AIR', 'AIR REG')
		AND l_shipinstruct = 'DELIVER IN PERSON'
     )
     OR
     (
		p_partkey = l_partkey
		AND p_brand = 'Brand#34'
		AND p_container IN ('LG CASE', 'LG BOX', 'LG PACK', 'LG PKG')
		AND l_quantity >= 20 AND l_quantity <= 20 + 10
		AND p_size BETWEEN 1 AND 15
		AND l_shipmode IN ('AIR', 'AIR REG')
		AND l_shipinstruct = 'DELIVER IN PERSON'
     )

Values for the following substitution parameters must be generated and used to build the executable query text:

1. QUANTITY1 is randomly selected within [1..10]
2. QUANTITY2 is randomly selected within [10..20].
3. QUANTITY3 is randomly selected within [20..30
4. BRAND1, BRAND2, BRAND3 = 'Brand#MN' where each MN is a two character string representing two numbers randomly and independently selected within [1 .. 5]

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. QUANTITY1 = 1
2. QUANTITY2 = 10
3. QUANTITY3 = 20.
4. BRAND1 = Brand#12.
5. BRAND2 = Brand#23.
6. BRAND3 = Brand#34

Sample Output

The Potential Part Promotion Query identifies suppliers in a particular nation having selected parts that may be candidates for a promotional offer.

The Potential Part Promotion query identifies suppliers who have an excess of a given part available; an excess is defined to be more than 50% of the parts like the given part that the supplier shipped in a given year for a given nation. Only parts whose names share a certain naming convention are considered.

SELECT
 	s_name,
     s_address
FROM
     supplier,
     nation
WHERE
     s_suppkey IN (
		SELECT
			ps_suppkey
		FROM
			partsupp
		WHERE
			ps_partkey IN (
				SELECT
					p_partkey
				FROM
					part
				WHERE
					p_name LIKE 'forest%'
			)
			AND ps_availqty > (
				SELECT
					0.5 * SUM(l_quantity)
				FROM
					lineitem
				WHERE
					l_partkey = ps_partkey
					AND l_suppkey = ps_suppkey
					AND l_shipdate >= MDY(1,1,1994)
					AND l_shipdate < MDY(1,1,1994) + 1 UNITS YEAR
			)
     )
     AND s_nationkey = n_nationkey
     AND n_name = 'CANADA'
ORDER BY
     s_name

Values for the following substitution parameters must be generated and used to build the executable query text:

1. COLOR is randomly selected within the list of values defined for the generation of P_NAME.
2. DATE is the first of January of a randomly selected year within 1993..1997.
3. NATION is randomly selected within the list of values defined for N_NAME in Clause 4.2.3.

For validation against the qualification database the query must be executed using the following values for substitution parameters and must produce the following output data:

Values for substitution parameters:

1. COLOR = forest.
2. DATE = 1994-01-01.
3. QUANTITY3 = 20.
4. NATION = CANADA.

Sample Output