This topic walks you through a complete TPC-H performance test on AnalyticDB for PostgreSQL V6.0 — from generating a 1 TB dataset and creating tables to loading data from OSS and running all 22 queries. By the end, you will have reproducible benchmark results on an MPP cluster of 32 compute nodes.
The tests described in this topic are based on the TPC-H benchmark but do not satisfy all of its requirements. Results cannot be compared with officially published TPC-H benchmark results.
About TPC-H
The following description is quoted from the TPC Benchmark™ H (TPC-H) specification:
"TPC-H is a decision support benchmark. It consists of a suite of business-oriented ad hoc queries and concurrent data modifications. The queries and the data populating the database have been chosen to have broad industry-wide relevance. This benchmark illustrates decision support systems that examine large volumes of data, execute queries with a high degree of complexity, and give answers to critical business questions."
For the full specification, see
Prerequisites
Before you begin, ensure that you have:
-
An AnalyticDB for PostgreSQL instance. For more information, see Create an instance.
-
An Elastic Compute Service (ECS) instance. For more information, see Creation methods.
-
Object Storage Service (OSS) activated, with a bucket created. For more information, see Create buckets.
-
The ECS instance IP address added to the AnalyticDB for PostgreSQL instance IP address whitelist. For more information, see Configure an IP address whitelist.
-
psql installed on the ECS instance. For more information, see the psql section of the client connection topic.
Test environment used in this topic
The AnalyticDB for PostgreSQL instance has the following specifications:
| Parameter | Value |
|---|---|
| Engine version | 6.0 Standard Edition |
| Compute node specifications | 2 cores, 16 GB |
| Number of compute nodes | 32 |
| Disk type | Enhanced SSD (ESSD) |
| Storage capacity per compute node | 200 GB |
The ECS instance has the following specifications:
| Parameter | Value |
|---|---|
| Instance type | ecs.g6e.4xlarge |
| Operating system | CentOS 7.x |
| System disk | PL1 ESSD, 40 GiB |
| Data disk | PL3 ESSD, 2,048 GiB |
Initialize the ECS data disk before use. For more information, see Initialize a data disk whose size does not exceed 2 TiB on a Linux instance.
Schema overview
The TPC-H benchmark uses 8 tables that model a product supply chain. Two small dimension tables (NATION and REGION) are replicated across all compute nodes. The other six tables are distributed by a primary key to spread data across nodes.
The tables relate to each other as follows: LINEITEM is the central fact table, linked to ORDERS by order key and to PART and SUPPLIER by part key and supplier key. ORDERS links to CUSTOMER by customer key. PARTSUPP represents many-to-many relationships between PART and SUPPLIER. Both SUPPLIER and CUSTOMER link to NATION, which in turn links to REGION.
| Table | Distribution | Role |
|---|---|---|
| LINEITEM | DISTRIBUTED BY (L_ORDERKEY) | Largest fact table; one row per order line item |
| ORDERS | DISTRIBUTED BY (O_ORDERKEY) | Order header records |
| CUSTOMER | DISTRIBUTED BY (C_CUSTKEY) | Customer records |
| PART | DISTRIBUTED BY (P_PARTKEY) | Part catalog |
| SUPPLIER | DISTRIBUTED BY (S_SUPPKEY) | Supplier records |
| PARTSUPP | DISTRIBUTED BY (PS_PARTKEY) | Part-supplier relationships and costs |
| NATION | DISTRIBUTED Replicated | 25-row dimension table |
| REGION | DISTRIBUTED Replicated | 5-row dimension table |
All tables use append-only columnar storage with LZ4 compression (APPENDONLY=TRUE, ORIENTATION=COLUMN, COMPRESSTYPE=LZ4, COMPRESSLEVEL=9). ORDERS and LINEITEM also define sort key columns to accelerate range queries on order date and ship date.
Generate test data
-
Log on to the ECS instance. For more information, see Connect to an instance.
-
Download the TPC-H DBGEN source code to the data disk and compile it. In this example, the data disk is mounted at
/mnt.wget https://github.com/electrum/tpch-dbgen/archive/refs/heads/master.zip yum install -y unzip zip unzip master.zip cd tpch-dbgen-master/ echo "#define EOL_HANDLING 1" >> config.h # Removes trailing | from each row make ./dbgen --help -
Generate a 1 TB dataset (scale factor 1000). Split the data into 32 files — one per compute node — so each node can import its own file in parallel.
Note-
In TPC-H, scale factor (SF) maps directly to data volume: 1 SF = 1 GB, so SF 1000 = 1 TB. Each SF covers 8 tables, excluding index storage. Reserve at least 1 SF of additional disk space.
-
Generation takes significant time. Check progress with
ps -fHU $USER | grep dbgen.
for((i=1;i<=32;i++)); do ./dbgen -s 1000 -S $i -C 32 -f & done -
Create test tables
-
Connect to the AnalyticDB for PostgreSQL instance using psql. For more information, see the psql section of the client connection topic.
-
Create the 8 TPC-H tables:
CREATE TABLE NATION ( N_NATIONKEY INTEGER NOT NULL, N_NAME CHAR(25) NOT NULL, N_REGIONKEY INTEGER NOT NULL, N_COMMENT VARCHAR(152) ) WITH (APPENDONLY=TRUE, ORIENTATION=COLUMN, COMPRESSTYPE=LZ4, COMPRESSLEVEL=9) DISTRIBUTED Replicated ; CREATE TABLE REGION ( R_REGIONKEY INTEGER NOT NULL, R_NAME CHAR(25) NOT NULL, R_COMMENT VARCHAR(152) ) WITH (APPENDONLY=TRUE, ORIENTATION=COLUMN, COMPRESSTYPE=LZ4, COMPRESSLEVEL=9) DISTRIBUTED Replicated ; CREATE TABLE PART ( P_PARTKEY INTEGER NOT NULL, P_NAME VARCHAR(55) NOT NULL, P_MFGR CHAR(25) NOT NULL, P_BRAND CHAR(10) NOT NULL, P_TYPE VARCHAR(25) NOT NULL, P_SIZE INTEGER NOT NULL, P_CONTAINER CHAR(10) NOT NULL, P_RETAILPRICE DECIMAL(15,2) NOT NULL, P_COMMENT VARCHAR(23) NOT NULL ) WITH (APPENDONLY=TRUE, ORIENTATION=COLUMN, COMPRESSTYPE=LZ4, COMPRESSLEVEL=9) DISTRIBUTED BY (P_PARTKEY) ; CREATE TABLE SUPPLIER ( S_SUPPKEY INTEGER NOT NULL, S_NAME CHAR(25) NOT NULL, S_ADDRESS VARCHAR(40) NOT NULL, S_NATIONKEY INTEGER NOT NULL, S_PHONE CHAR(15) NOT NULL, S_ACCTBAL DECIMAL(15,2) NOT NULL, S_COMMENT VARCHAR(101) NOT NULL ) WITH (APPENDONLY=TRUE, ORIENTATION=COLUMN, COMPRESSTYPE=LZ4, COMPRESSLEVEL=9) DISTRIBUTED BY (S_SUPPKEY) ; CREATE TABLE PARTSUPP ( PS_PARTKEY INTEGER NOT NULL, PS_SUPPKEY INTEGER NOT NULL, PS_AVAILQTY INTEGER NOT NULL, PS_SUPPLYCOST DECIMAL(15,2) NOT NULL, PS_COMMENT VARCHAR(199) NOT NULL ) WITH (APPENDONLY=TRUE, ORIENTATION=COLUMN, COMPRESSTYPE=LZ4, COMPRESSLEVEL=9) DISTRIBUTED BY (PS_PARTKEY) ; CREATE TABLE CUSTOMER ( C_CUSTKEY INTEGER NOT NULL, C_NAME VARCHAR(25) NOT NULL, C_ADDRESS VARCHAR(40) NOT NULL, C_NATIONKEY INTEGER NOT NULL, C_PHONE CHAR(15) NOT NULL, C_ACCTBAL DECIMAL(15,2) NOT NULL, C_MKTSEGMENT CHAR(10) NOT NULL, C_COMMENT VARCHAR(117) NOT NULL ) WITH (APPENDONLY=TRUE, ORIENTATION=COLUMN, COMPRESSTYPE=LZ4, COMPRESSLEVEL=9) DISTRIBUTED BY (C_CUSTKEY) ; CREATE TABLE ORDERS ( O_ORDERKEY BIGINT NOT NULL, O_CUSTKEY INTEGER NOT NULL, O_ORDERSTATUS "char" NOT NULL, O_TOTALPRICE DECIMAL(15,2) NOT NULL, O_ORDERDATE DATE NOT NULL, O_ORDERPRIORITY CHAR(15) NOT NULL, O_CLERK CHAR(15) NOT NULL, O_SHIPPRIORITY INTEGER NOT NULL, O_COMMENT VARCHAR(79) NOT NULL ) WITH (APPENDONLY=TRUE, ORIENTATION=COLUMN, COMPRESSTYPE=LZ4, COMPRESSLEVEL=9) DISTRIBUTED BY (O_ORDERKEY) ORDER BY(O_ORDERDATE) ; CREATE TABLE LINEITEM ( L_ORDERKEY BIGINT NOT NULL, L_PARTKEY INTEGER NOT NULL, L_SUPPKEY INTEGER NOT NULL, L_LINENUMBER INTEGER NOT NULL, L_QUANTITY DECIMAL(15,2) NOT NULL, L_EXTENDEDPRICE DECIMAL(15,2) NOT NULL, L_DISCOUNT DECIMAL(15,2) NOT NULL, L_TAX DECIMAL(15,2) NOT NULL, L_RETURNFLAG "char" NOT NULL, L_LINESTATUS "char" NOT NULL, L_SHIPDATE DATE NOT NULL, L_COMMITDATE DATE NOT NULL, L_RECEIPTDATE DATE NOT NULL, L_SHIPINSTRUCT CHAR(25) NOT NULL, L_SHIPMODE CHAR(10) NOT NULL, L_COMMENT VARCHAR(44) NOT NULL ) WITH (APPENDONLY=TRUE, ORIENTATION=COLUMN, COMPRESSTYPE=LZ4, COMPRESSLEVEL=9) DISTRIBUTED BY (L_ORDERKEY) ORDER BY(L_SHIPDATE) ;
Import data
The NATION and REGION tables are small enough to import directly from the ECS instance. The remaining six larger tables must go through OSS, because the COPY statement writes data serially through the coordinator node and cannot parallelize large imports. Using OSS lets all compute nodes load data in parallel.
Import NATION and REGION
Execute the following statements in psql:
\copy nation from '/mnt/tpch-dbgen-master/nation.tbl' DELIMITER '|';
\copy region from '/mnt/tpch-dbgen-master/region.tbl' DELIMITER '|';
Replace /mnt/tpch-dbgen-master with the actual path to your .tbl files.
Import the remaining six tables via OSS
-
Download ossutil on the ECS instance:
wget http://gosspublic.alicdn.com/ossutil/1.7.3/ossutil64 -
Grant execute permissions:
chmod 755 ossutil64 -
Upload the
.tblfiles for each of the six tables to your OSS bucket. Replace the placeholders with your actual endpoint, AccessKey ID, Access Key Secret, and bucket name:ls <table_name>.tbl* | while read line; do ~/ossutil64 -e <EndPoint> -i <AccessKey ID> -k <Access Key Secret> cp $line oss://<OSS Bucket>/<Directory>/ & done -
After all files are uploaded, import them into the AnalyticDB for PostgreSQL database. For more information about the COPY statement syntax, see Use the COPY or UNLOAD statement to import or export data between OSS foreign tables and AnalyticDB for PostgreSQL tables. Replace
<OSS Bucket>,<Directory>,<AccessKey ID>,<Access Key Secret>, and<EndPoint>with your actual values.COPY customer FROM 'oss://<OSS Bucket>/<Directory>/customer.tbl' ACCESS_KEY_ID '<AccessKey ID>' SECRET_ACCESS_KEY '<Access Key Secret>' FORMAT AS text "delimiter" '|' "null" '' ENDPOINT '<EndPoint>' FDW 'oss_fdw' ; COPY lineitem FROM 'oss://<OSS Bucket>/<Directory>/lineitem.tbl' ACCESS_KEY_ID '<AccessKey ID>' SECRET_ACCESS_KEY '<Access Key Secret>' FORMAT AS text "delimiter" '|' "null" '' ENDPOINT '<EndPoint>' FDW 'oss_fdw' ; -- Sort lineitem by its sort key column after import. sort lineitem; COPY orders FROM 'oss://<OSS Bucket>/<Directory>/orders.tbl' ACCESS_KEY_ID '<AccessKey ID>' SECRET_ACCESS_KEY '<Access Key Secret>' FORMAT AS text "delimiter" '|' "null" '' ENDPOINT '<EndPoint>' FDW 'oss_fdw' ; -- Sort orders by its sort key column after import. sort orders; COPY part FROM 'oss://<OSS Bucket>/<Directory>/part.tbl' ACCESS_KEY_ID '<AccessKey ID>' SECRET_ACCESS_KEY '<Access Key Secret>' FORMAT AS text "delimiter" '|' "null" '' ENDPOINT '<EndPoint>' FDW 'oss_fdw' ; COPY supplier FROM 'oss://<OSS Bucket>/<Directory>/supplier.tbl' ACCESS_KEY_ID '<AccessKey ID>' SECRET_ACCESS_KEY '<Access Key Secret>' FORMAT AS text "delimiter" '|' "null" '' ENDPOINT '<EndPoint>' FDW 'oss_fdw' ; COPY partsupp FROM 'oss://<OSS Bucket>/<Directory>/partsupp.tbl' ACCESS_KEY_ID '<AccessKey ID>' SECRET_ACCESS_KEY '<Access Key Secret>' FORMAT AS text "delimiter" '|' ENDPOINT '<EndPoint>' FDW 'oss_fdw' ;
Run queries
All 22 queries use the laser extension (Odyssey), AnalyticDB for PostgreSQL's vector compute acceleration engine. Enable it with set laser.enable = on; before each query, or create it once at the start of the session with create extension if not exists laser;.
Two methods are available: a shell script that times all 22 queries automatically, or running queries one by one in psql.
Run all queries with a shell script
-
Download the tpch_query.tar.gz package and extract it to the
/tpch_querydirectory. -
Create a file named
query.shwith the following content. The script runs Q1 through Q22 in sequence, recording each query's execution time and the cumulative total.#!/bin/bash total_cost=0 for i in {1..22} do echo "begin run Q${i}, tpch_query/q$i.sql , `date`" begin_time=`date +%s.%N` ./psql ${Instance endpoint} -p ${Port number} -U ${Database username} -f ~/tpch_query/q${i}.sql > ~/log/log_q${i}.out rc=$? end_time=`date +%s.%N` cost=`echo "$end_time-$begin_time"|bc` total_cost=`echo "$total_cost+$cost"|bc` if [ $rc -ne 0 ] ; then printf "run Q%s fail, cost: %.2f, totalCost: %.2f, `date`\n" $i $cost $total_cost else printf "run Q%s succ, cost: %.2f, totalCost: %.2f, `date`\n" $i $cost $total_cost fi done -
Run the script in the background:
nohup bash ~/query.sh > /tmp/tpch.log & -
View the results:
cat /tmp/tpch.log
Run queries individually in psql
The following table lists the business question each TPC-H query answers. Use this to identify which queries are most relevant to your evaluation.
| Query | Business question |
|---|---|
| Q1 | What is the aggregate pricing summary for all line items shipped by a given date? |
| Q2 | Which supplier should be selected for a given part in a given region to minimize cost? |
| Q3 | What are the top unshipped orders with the highest revenue for a given market segment and date? |
| Q4 | How well are orders being prioritized within a given quarter? |
| Q5 | How much revenue did each nation's suppliers generate within a given region and year? |
| Q6 | How much revenue was forgone due to discount decisions in a given year? |
| Q7 | How much revenue flows between a pair of nations through shipping in a given period? |
| Q8 | How does a given supplier nation's market share change over time within a region? |
| Q9 | What is the profit breakdown by nation and year for a given product color? |
| Q10 | Which customers have returned items and how much revenue did they generate in a given quarter? |
| Q11 | Which parts represent a significant portion of the total supply value for a given nation? |
| Q12 | How do shipping modes affect order priority counts in a given year? |
| Q13 | How is the customer order count distributed across all customers? |
| Q14 | What percentage of revenue in a given month comes from promotional parts? |
| Q15 | Which supplier contributed the most revenue in a given quarter? |
| Q16 | How many suppliers can supply parts matching specific brand, type, and size criteria? |
| Q17 | What is the estimated annual revenue loss from selling below the average quantity threshold for a given part? |
| Q18 | Which customers placed large-volume orders exceeding a given quantity threshold? |
| Q19 | What is the total discounted revenue for air-shipped parts meeting specific brand and container criteria? |
| Q20 | Which suppliers have excess inventory of a given part compared to a threshold derived from shipment history? |
| Q21 | Which suppliers failed to deliver orders on time in a given nation? |
| Q22 | How many potential customers in specific country codes have above-average balances but have never placed an order? |
After connecting to the database, execute the following statements. Each query begins with set laser.enable = on; to activate the Odyssey vector compute engine.
-- Create the Laser vector compute engine.
create extension if not exists laser;
-- Q1: Pricing summary report
set laser.enable = on;
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 <= date '1998-12-01' - interval '93 day'
group by
l_returnflag,
l_linestatus
order by
l_returnflag,
l_linestatus;
-- Q2: Minimum cost supplier
set laser.enable = on;
select
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 = 23
and p_type like '%STEEL'
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
limit 100;
-- Q3: Shipping priority
set laser.enable = on;
select
l_orderkey,
sum(l_extendedprice * (1 - l_discount)) as revenue,
o_orderdate,
o_shippriority
from
customer,
orders,
lineitem
where
c_mktsegment = 'MACHINERY'
and c_custkey = o_custkey
and l_orderkey = o_orderkey
and o_orderdate < date '1995-03-24'
and l_shipdate > date '1995-03-24'
group by
l_orderkey,
o_orderdate,
o_shippriority
order by
revenue desc,
o_orderdate
limit 10;
-- Q4: Order priority checking
set laser.enable = on;
select
o_orderpriority,
count(*) as order_count
from
orders
where
o_orderdate >= date '1996-08-01'
and o_orderdate < date '1996-08-01' + interval '3' month
and exists (
select
*
from
lineitem
where
l_orderkey = o_orderkey
and l_commitdate < l_receiptdate
)
group by
o_orderpriority
order by
o_orderpriority;
-- Q5: Local supplier volume
set laser.enable = on;
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 = 'MIDDLE EAST'
and o_orderdate >= date '1994-01-01'
and o_orderdate < date '1994-01-01' + interval '1' year
group by
n_name
order by
revenue desc;
-- Q6: Forecasting revenue change
set laser.enable = on;
select
sum(l_extendedprice * l_discount) as revenue
from
lineitem
where
l_shipdate >= date '1994-01-01'
and l_shipdate < date '1994-01-01' + interval '1' year
and l_discount between 0.06 - 0.01 and 0.06 + 0.01
and l_quantity < 24;
-- Q7: Volume shipping
set laser.enable = on;
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,
extract(year from 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 = 'JORDAN' and n2.n_name = 'INDONESIA')
or (n1.n_name = 'INDONESIA' and n2.n_name = 'JORDAN')
)
and l_shipdate between date '1995-01-01' and date '1996-12-31'
) as shipping
group by
supp_nation,
cust_nation,
l_year
order by
supp_nation,
cust_nation,
l_year;
-- Q8: National market share
set laser.enable = on;
select
o_year,
sum(case
when nation = 'INDONESIA' then volume
else 0
end) / sum(volume) as mkt_share
from
(
select
extract(year from 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 = 'ASIA'
and s_nationkey = n2.n_nationkey
and o_orderdate between date '1995-01-01' and date '1996-12-31'
and p_type = 'STANDARD BRUSHED BRASS'
) as all_nations
group by
o_year
order by
o_year;
-- Q9: Product type profit measure
set laser.enable = on;
select
nation,
o_year,
sum(amount) as sum_profit
from
(
select
n_name as nation,
extract(year from 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 '%chartreuse%'
) as profit
group by
nation,
o_year
order by
nation,
o_year desc;
-- Q10: Returned item reporting
set laser.enable = on;
select
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 >= date '1994-08-01'
and o_orderdate < date '1994-08-01' + interval '3' 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
limit 20;
-- Q11: Important stock identification
set laser.enable = on;
select
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 = 'INDONESIA'
group by
ps_partkey having
sum(ps_supplycost * ps_availqty) > (
select
sum(ps_supplycost * ps_availqty) * 0.0001000000
from
partsupp,
supplier,
nation
where
ps_suppkey = s_suppkey
and s_nationkey = n_nationkey
and n_name = 'INDONESIA'
)
order by
value desc;
-- Q12: Shipping modes and order priority
set laser.enable = on;
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 ('REG AIR', 'TRUCK')
and l_commitdate < l_receiptdate
and l_shipdate < l_commitdate
and l_receiptdate >= date '1994-01-01'
and l_receiptdate < date '1994-01-01' + interval '1' year
group by
l_shipmode
order by
l_shipmode;
-- Q13: Customer distribution
set laser.enable = on;
select
c_count,
count(*) as custdist
from
(
select
c_custkey,
count(o_orderkey)
from
customer left outer join orders on
c_custkey = o_custkey
and o_comment not like '%pending%requests%'
group by
c_custkey
) as c_orders (c_custkey, c_count)
group by
c_count
order by
custdist desc,
c_count desc;
-- Q14: Promotion effect
set laser.enable = on;
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 >= date '1994-11-01'
and l_shipdate < date '1994-11-01' + interval '1' month;
-- Q15: Top supplier
set laser.enable = on;
create view revenue0 (supplier_no, total_revenue) as
select
l_suppkey,
sum(l_extendedprice * (1 - l_discount))
from
lineitem
where
l_shipdate >= date '1997-10-01'
and l_shipdate < date '1997-10-01' + interval '3' month
group by
l_suppkey;
select
s_suppkey,
s_name,
s_address,
s_phone,
total_revenue
from
supplier,
revenue0
where
s_suppkey = supplier_no
and total_revenue = (
select
max(total_revenue)
from
revenue0
)
order by
s_suppkey;
drop view revenue0;
-- Q16: Parts/supplier relationship
set laser.enable = on;
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#44'
and p_type not like 'SMALL BURNISHED%'
and p_size in (36, 27, 34, 45, 11, 6, 25, 16)
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;
-- Q17: Small-quantity order revenue
set laser.enable = on;
select
sum(l_extendedprice) / 7.0 as avg_yearly
from
lineitem,
part
where
p_partkey = l_partkey
and p_brand = 'Brand#42'
and p_container = 'JUMBO PACK'
and l_quantity < (
select
0.2 * avg(l_quantity)
from
lineitem
where
l_partkey = p_partkey
);
-- Q18: Large volume customer
set laser.enable = on;
select
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) > 312
)
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
limit 100;
-- Q19: Discounted revenue
set laser.enable = on;
select
sum(l_extendedprice* (1 - l_discount)) as revenue
from
lineitem,
part
where
(
p_partkey = l_partkey
and p_brand = 'Brand#43'
and p_container in ('SM CASE', 'SM BOX', 'SM PACK', 'SM PKG')
and l_quantity >= 5 and l_quantity <= 5 + 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#45'
and p_container in ('MED BAG', 'MED BOX', 'MED PKG', 'MED PACK')
and l_quantity >= 12 and l_quantity <= 12 + 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#11'
and p_container in ('LG CASE', 'LG BOX', 'LG PACK', 'LG PKG')
and l_quantity >= 24 and l_quantity <= 24 + 10
and p_size between 1 and 15
and l_shipmode in ('AIR', 'AIR REG')
and l_shipinstruct = 'DELIVER IN PERSON'
);
-- Q20: Potential part promotion
set laser.enable = on;
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 'magenta%'
)
and ps_availqty > (
select
0.5 * sum(l_quantity)
from
lineitem
where
l_partkey = ps_partkey
and l_suppkey = ps_suppkey
and l_shipdate >= date '1996-01-01'
and l_shipdate < date '1996-01-01' + interval '1' year
)
)
and s_nationkey = n_nationkey
and n_name = 'RUSSIA'
order by
s_name;
-- Q21: Suppliers who kept orders waiting
set laser.enable = on;
select
s_name,
count(*) as numwait
from
supplier,
lineitem l1,
orders,
nation
where
s_suppkey = l1.l_suppkey
and o_orderkey = l1.l_orderkey
and o_orderstatus = 'F'
and l1.l_receiptdate > l1.l_commitdate
and exists (
select
*
from
lineitem l2
where
l2.l_orderkey = l1.l_orderkey
and l2.l_suppkey <> l1.l_suppkey
)
and not exists (
select
*
from
lineitem l3
where
l3.l_orderkey = l1.l_orderkey
and l3.l_suppkey <> l1.l_suppkey
and l3.l_receiptdate > l3.l_commitdate
)
and s_nationkey = n_nationkey
and n_name = 'MOZAMBIQUE'
group by
s_name
order by
numwait desc,
s_name
limit 100;
-- Q22: Global sales opportunity
set laser.enable = on;
select
cntrycode,
count(*) as numcust,
sum(c_acctbal) as totacctbal
from
(
select
substring(c_phone from 1 for 2) as cntrycode,
c_acctbal
from
customer
where
substring(c_phone from 1 for 2) in
('13', '31', '23', '29', '30', '18', '17')
and c_acctbal > (
select
avg(c_acctbal)
from
customer
where
c_acctbal > 0.00
and substring(c_phone from 1 for 2) in
('13', '31', '23', '29', '30', '18', '17')
)
and not exists (
select
*
from
orders
where
o_custkey = c_custkey
)
) as custsale
group by
cntrycode
order by
cntrycode;