- TPC-H Benchmark
TPC-H Benchmark
TPC-H is a decision support benchmark (Decision Support Benchmark), which consists of a set of business-oriented special query and concurrent data modification. The data that is queried and populates the database has broad industry relevance. This benchmark demonstrates a decision support system that examines large amounts of data, executes highly complex queries, and answers key business questions. The performance index reported by TPC-H is called TPC-H composite query performance index per hour (QphH@Size), which reflects multiple aspects of the system’s ability to process queries. These aspects include the database size chosen when executing the query, the query processing capability when the query is submitted by a single stream, and the query throughput when the query is submitted by many concurrent users.
This document mainly introduces the performance of Doris on the TPC-H 100G test set.
Note 1: The standard test set including TPC-H is usually far from the actual business scenario, and some tests will perform parameter tuning for the test set. Therefore, the test results of the standard test set can only reflect the performance of the database in a specific scenario. We suggest users use actual business data for further testing.
Note 2: The operations involved in this document are all tested on CentOS 7.x.
Note 3: Doris starting from version 1.2.2, the page cache is turned off by default to reduce memory usage, which has a certain impact on performance. For performance testing, enable the page cache by adding disable_storage_page_cache=false to be.conf.
On 22 queries on the TPC-H standard test data set, we conducted a comparison test based on Apache Doris 1.2.0-rc01, Apache Doris 1.1.3 and Apache Doris 0.15.0 RC04 versions. Compared with Apache Doris 1.1.3, the overall performance of Apache Doris 1.2.0-rc01 has been improved by nearly 3 times, and by nearly 11 times compared with Apache Doris 0.15.0 RC04.
1. Hardware Environment
Hardware | Configuration Instructions |
---|---|
Number of mMachines | 4 Tencent Cloud Virtual Machine(1FE,3BEs) |
CPU | Intel Xeon(Cascade Lake) Platinum 8269CY 16C (2.5 GHz/3.2 GHz) |
Memory | 64G |
Network | 5Gbps |
Disk | ESSD Cloud Hard Disk |
2. Software Environment
- Doris Deployed 3BEs and 1FE
- Kernel Version: Linux version 5.4.0-96-generic (buildd@lgw01-amd64-051)
- OS version: CentOS 7.8
- Doris software version: Apache Doris 1.2.0-rc01、 Apache Doris 1.1.3 、 Apache Doris 0.15.0 RC04
- JDK: openjdk version “11.0.14” 2022-01-18
3. Test Data Volume
The TPCH 100G data generated by the simulation of the entire test are respectively imported into Apache Doris 1.2.0-rc01, Apache Doris 1.1.3 and Apache Doris 0.15.0 RC04 for testing. The following is the relevant description and data volume of the table.
TPC-H Table Name | Rows | Size after Import | Annotation |
---|---|---|---|
REGION | 5 | 400KB | Region |
NATION | 25 | 7.714 KB | Nation |
SUPPLIER | 1,000,000 | 85.528 MB | Supplier |
PART | 20,000,000 | 752.330 MB | Parts |
PARTSUPP | 20,000,000 | 4.375 GB | Parts Supply |
CUSTOMER | 15,000,000 | 1.317 GB | Customer |
ORDERS | 1,50,000,000 | 6.301 GB | Orders |
LINEITEM | 6,00,000,000 | 20.882 GB | Order Details |
4. Test SQL
TPCH 22 test query statements : TPCH-Query-SQL
Notice:
The following four parameters in the above SQL do not exist in Apache Doris 0.15.0 RC04. When executing, please remove:
1. enable_vectorized_engine=true,
2. batch_size=4096,
3. disable_join_reorder=false
4. enable_projection=true
5. Test Results
Here we use Apache Doris 1.2.0-rc01, Apache Doris 1.1.3 and Apache Doris 0.15.0 RC04 for comparative testing. In the test, we use Query Time(ms) as the main performance indicator. The test results are as follows:
Query | Apache Doris 1.2.0-rc01 (ms) | Apache Doris 1.1.3 (ms) | Apache Doris 0.15.0 RC04 (ms) |
---|---|---|---|
Q1 | 2.12 | 3.75 | 28.63 |
Q2 | 0.20 | 4.22 | 7.88 |
Q3 | 0.62 | 2.64 | 9.39 |
Q4 | 0.61 | 1.5 | 9.3 |
Q5 | 1.05 | 2.15 | 4.11 |
Q6 | 0.08 | 0.19 | 0.43 |
Q7 | 0.58 | 1.04 | 1.61 |
Q8 | 0.72 | 1.75 | 50.35 |
Q9 | 3.61 | 7.94 | 16.34 |
Q10 | 1.26 | 1.41 | 5.21 |
Q11 | 0.15 | 0.35 | 1.72 |
Q12 | 0.21 | 0.57 | 5.39 |
Q13 | 2.62 | 8.15 | 20.88 |
Q14 | 0.16 | 0.3 | |
Q15 | 0.30 | 0.66 | 1.86 |
Q16 | 0.38 | 0.79 | 1.32 |
Q17 | 0.65 | 1.51 | 26.67 |
Q18 | 2.28 | 3.364 | 11.77 |
Q19 | 0.20 | 0.829 | 1.71 |
Q20 | 0.21 | 2.77 | 5.2 |
Q21 | 1.17 | 4.47 | 10.34 |
Q22 | 0.46 | 0.9 | 3.22 |
Total | 19.64 | 51.253 | 223.33 |
- Result Description
- The data set corresponding to the test results is scale 100, about 600 million.
- The test environment is configured as the user’s common configuration, with 4 cloud servers, 16-core 64G SSD, and 1 FE 3 BEs deployment.
- Select the user’s common configuration test to reduce the cost of user selection and evaluation, but the entire test process will not consume so many hardware resources.
- Apache Doris 0.15 RC04 failed to execute Q14 in the TPC-H test, unable to complete the query.
6. Environmental Preparation
Please refer to the official document to install and deploy Doris to obtain a normal running Doris cluster (at least 1 FE 1 BE, 1 FE 3 BE is recommended).
7. Data Preparation
7.1 Download and Install TPC-H Data Generation Tool
Execute the following script to download and compile the tpch-tools tool.
sh build-tpch-dbgen.sh
After successful installation, the dbgen
binary will be generated under the TPC-H_Tools_v3.0.0/
directory.
7.2 Generating the TPC-H Test Set
Execute the following script to generate the TPC-H dataset:
sh gen-tpch-data.sh
Note 1: Check the script help via
sh gen-tpch-data.sh -h
.Note 2: The data will be generated under the
tpch-data/
directory with the suffix.tbl
. The total file size is about 100GB and may need a few minutes to an hour to generate.Note 3: A standard test data set of 100G is generated by default.
7.3 Create Table
7.3.1 Prepare the doris-cluster.conf
File
Before import the script, you need to write the FE’s ip port and other information in the doris-cluster.conf
file.
The file is located under ${DORIS_HOME}/tools/tpch-tools/conf/
.
The content of the file includes FE’s ip, HTTP port, user name, password and the DB name of the data to be imported:
# Any of FE host
export FE_HOST='127.0.0.1'
# http_port in fe.conf
export FE_HTTP_PORT=8030
# query_port in fe.conf
export FE_QUERY_PORT=9030
# Doris username
export USER='root'
# Doris password
export PASSWORD=''
# The database where TPC-H tables located
export DB='tpch1'
Execute the Following Script to Generate and Create TPC-H Table
sh create-tpch-tables.sh
Or copy the table creation statement in create-tpch-tables.sql and excute it in Doris.
7.4 Import Data
Please perform data import with the following command:
sh ./load-tpch-data.sh
7.5 Check Imported Data
Execute the following SQL statement to check that the imported data is consistent with the above data.
select count(*) from lineitem;
select count(*) from orders;
select count(*) from partsupp;
select count(*) from part;
select count(*) from customer;
select count(*) from supplier;
select count(*) from nation;
select count(*) from region;
select count(*) from revenue0;
7.6 Query Test
7.6.1 Executing Query Scripts
Execute the above test SQL or execute the following command
./run-tpch-queries.sh
Notice:
At present, the query optimizer and statistics functions of Doris are not so perfect, so we rewrite some queries in TPC-H to adapt to the execution framework of Doris, but it does not affect the correctness of the results
Doris’ new query optimizer will be released in future versions
Set
set exec_mem_limit=8G
before executing the query
7.6.2 Single SQL Execution
The following is the SQL statement used in the test, you can also get the latest SQL from the code base.
--Q1
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=8, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=false, enable_cost_based_join_reorder=false, enable_projection=false) */
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 '90' day
group by
l_returnflag,
l_linestatus
order by
l_returnflag,
l_linestatus;
--Q2
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=1, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=true, enable_cost_based_join_reorder=false, enable_projection=true) */
s_acctbal,
s_name,
n_name,
p_partkey,
p_mfgr,
s_address,
s_phone,
s_comment
from
partsupp join
(
select
ps_partkey as a_partkey,
min(ps_supplycost) as a_min
from
partsupp,
part,
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'
and p_size = 15
and p_type like '%BRASS'
group by a_partkey
) A on ps_partkey = a_partkey and ps_supplycost=a_min ,
part,
supplier,
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'
order by
s_acctbal desc,
n_name,
s_name,
p_partkey
limit 100;
--Q3
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=8, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=true, enable_cost_based_join_reorder=false, enable_projection=true, runtime_filter_wait_time_ms=10000) */
l_orderkey,
sum(l_extendedprice * (1 - l_discount)) as revenue,
o_orderdate,
o_shippriority
from
(
select l_orderkey, l_extendedprice, l_discount, o_orderdate, o_shippriority, o_custkey from
lineitem join orders
where l_orderkey = o_orderkey
and o_orderdate < date '1995-03-15'
and l_shipdate > date '1995-03-15'
) t1 join customer c
on c.c_custkey = t1.o_custkey
where c_mktsegment = 'BUILDING'
group by
l_orderkey,
o_orderdate,
o_shippriority
order by
revenue desc,
o_orderdate
limit 10;
--Q4
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=4, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=true, enable_cost_based_join_reorder=false, enable_projection=true) */
o_orderpriority,
count(*) as order_count
from
(
select
*
from
lineitem
where l_commitdate < l_receiptdate
) t1
right semi join orders
on t1.l_orderkey = o_orderkey
where
o_orderdate >= date '1993-07-01'
and o_orderdate < date '1993-07-01' + interval '3' month
group by
o_orderpriority
order by
o_orderpriority;
--Q5
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=8, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=false, enable_cost_based_join_reorder=false, enable_projection=true) */
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 >= date '1994-01-01'
and o_orderdate < date '1994-01-01' + interval '1' year
group by
n_name
order by
revenue desc;
--Q6
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=1, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=false, enable_cost_based_join_reorder=false, enable_projection=true) */
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 .06 - 0.01 and .06 + 0.01
and l_quantity < 24;
--Q7
select /*+SET_VAR(exec_mem_limit=458589934592, parallel_fragment_exec_instance_num=2, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=false, enable_cost_based_join_reorder=false, enable_projection=true) */
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 = 'FRANCE' and n2.n_name = 'GERMANY')
or (n1.n_name = 'GERMANY' and n2.n_name = 'FRANCE')
)
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
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=8, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=true, enable_cost_based_join_reorder=false, enable_projection=true) */
o_year,
sum(case
when nation = 'BRAZIL' 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
lineitem,
orders,
customer,
supplier,
part,
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 date '1995-01-01' and date '1996-12-31'
and p_type = 'ECONOMY ANODIZED STEEL'
) as all_nations
group by
o_year
order by
o_year;
--Q9
select/*+SET_VAR(exec_mem_limit=37179869184, parallel_fragment_exec_instance_num=2, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=false, enable_cost_based_join_reorder=false, enable_projection=true, enable_remove_no_conjuncts_runtime_filter_policy=true, runtime_filter_wait_time_ms=100000) */
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
lineitem join orders on o_orderkey = l_orderkey
join[shuffle] part on p_partkey = l_partkey
join[shuffle] partsupp on ps_partkey = l_partkey
join[shuffle] supplier on s_suppkey = l_suppkey
join[broadcast] nation on s_nationkey = n_nationkey
where
ps_suppkey = l_suppkey and
p_name like '%green%'
) as profit
group by
nation,
o_year
order by
nation,
o_year desc;
--Q10
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=4, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=true, enable_cost_based_join_reorder=false, enable_projection=true) */
c_custkey,
c_name,
sum(t1.l_extendedprice * (1 - t1.l_discount)) as revenue,
c_acctbal,
n_name,
c_address,
c_phone,
c_comment
from
customer,
(
select o_custkey,l_extendedprice,l_discount from lineitem, orders
where l_orderkey = o_orderkey
and o_orderdate >= date '1993-10-01'
and o_orderdate < date '1993-10-01' + interval '3' month
and l_returnflag = 'R'
) t1,
nation
where
c_custkey = t1.o_custkey
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
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=2, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=false, enable_cost_based_join_reorder=true, enable_projection=true) */
ps_partkey,
sum(ps_supplycost * ps_availqty) as value
from
partsupp,
(
select s_suppkey
from supplier, nation
where s_nationkey = n_nationkey and n_name = 'GERMANY'
) B
where
ps_suppkey = B.s_suppkey
group by
ps_partkey having
sum(ps_supplycost * ps_availqty) > (
select
sum(ps_supplycost * ps_availqty) * 0.000002
from
partsupp,
(select s_suppkey
from supplier, nation
where s_nationkey = n_nationkey and n_name = 'GERMANY'
) A
where
ps_suppkey = A.s_suppkey
)
order by
value desc;
--Q12
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=2, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=false, enable_cost_based_join_reorder=true, enable_projection=true) */
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 >= date '1994-01-01'
and l_receiptdate < date '1994-01-01' + interval '1' year
group by
l_shipmode
order by
l_shipmode;
--Q13
select /*+SET_VAR(exec_mem_limit=45899345920, parallel_fragment_exec_instance_num=16, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=true, enable_cost_based_join_reorder=true, enable_projection=true) */
c_count,
count(*) as custdist
from
(
select
c_custkey,
count(o_orderkey) as c_count
from
orders right outer join customer on
c_custkey = o_custkey
and o_comment not like '%special%requests%'
group by
c_custkey
) as c_orders
group by
c_count
order by
custdist desc,
c_count desc;
--Q14
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=8, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=true, enable_cost_based_join_reorder=true, enable_projection=true, runtime_filter_mode=OFF) */
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
part,
lineitem
where
l_partkey = p_partkey
and l_shipdate >= date '1995-09-01'
and l_shipdate < date '1995-09-01' + interval '1' month;
--Q15
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=8, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=false, enable_cost_based_join_reorder=true, enable_projection=true) */
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;
--Q16
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=8, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=false, enable_cost_based_join_reorder=true, enable_projection=true) */
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;
--Q17
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=1, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=false, enable_cost_based_join_reorder=true, enable_projection=true) */
sum(l_extendedprice) / 7.0 as avg_yearly
from
lineitem join [broadcast]
part p1 on p1.p_partkey = l_partkey
where
p1.p_brand = 'Brand#23'
and p1.p_container = 'MED BOX'
and l_quantity < (
select
0.2 * avg(l_quantity)
from
lineitem join [broadcast]
part p2 on p2.p_partkey = l_partkey
where
l_partkey = p1.p_partkey
and p2.p_brand = 'Brand#23'
and p2.p_container = 'MED BOX'
);
--Q18
select /*+SET_VAR(exec_mem_limit=45899345920, parallel_fragment_exec_instance_num=4, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=true, enable_cost_based_join_reorder=true, enable_projection=true) */
c_name,
c_custkey,
t3.o_orderkey,
t3.o_orderdate,
t3.o_totalprice,
sum(t3.l_quantity)
from
customer join
(
select * from
lineitem join
(
select * from
orders left semi join
(
select
l_orderkey
from
lineitem
group by
l_orderkey having sum(l_quantity) > 300
) t1
on o_orderkey = t1.l_orderkey
) t2
on t2.o_orderkey = l_orderkey
) t3
on c_custkey = t3.o_custkey
group by
c_name,
c_custkey,
t3.o_orderkey,
t3.o_orderdate,
t3.o_totalprice
order by
t3.o_totalprice desc,
t3.o_orderdate
limit 100;
--Q19
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=2, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=false, enable_cost_based_join_reorder=false, enable_projection=true) */
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'
);
--Q20
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=2, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=true, enable_cost_based_join_reorder=true, enable_projection=true, runtime_bloom_filter_size=551943) */
s_name, s_address from
supplier left semi join
(
select * from
(
select l_partkey,l_suppkey, 0.5 * sum(l_quantity) as l_q
from lineitem
where l_shipdate >= date '1994-01-01'
and l_shipdate < date '1994-01-01' + interval '1' year
group by l_partkey,l_suppkey
) t2 join
(
select ps_partkey, ps_suppkey, ps_availqty
from partsupp left semi join part
on ps_partkey = p_partkey and p_name like 'forest%'
) t1
on t2.l_partkey = t1.ps_partkey and t2.l_suppkey = t1.ps_suppkey
and t1.ps_availqty > t2.l_q
) t3
on s_suppkey = t3.ps_suppkey
join nation
where s_nationkey = n_nationkey
and n_name = 'CANADA'
order by s_name;
--Q21
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=4, enable_vectorized_engine=true, batch_size=4096, disable_join_reorder=true, enable_cost_based_join_reorder=true, enable_projection=true) */
s_name, count(*) as numwait
from
lineitem l2 right semi join
(
select * from
lineitem l3 right anti join
(
select * from
orders join lineitem l1 on l1.l_orderkey = o_orderkey and o_orderstatus = 'F'
join
(
select * from
supplier join nation
where s_nationkey = n_nationkey
and n_name = 'SAUDI ARABIA'
) t1
where t1.s_suppkey = l1.l_suppkey and l1.l_receiptdate > l1.l_commitdate
) t2
on l3.l_orderkey = t2.l_orderkey and l3.l_suppkey <> t2.l_suppkey and l3.l_receiptdate > l3.l_commitdate
) t3
on l2.l_orderkey = t3.l_orderkey and l2.l_suppkey <> t3.l_suppkey
group by
t3.s_name
order by
numwait desc,
t3.s_name
limit 100;
--Q22
with tmp as (select
avg(c_acctbal) as av
from
customer
where
c_acctbal > 0.00
and substring(c_phone, 1, 2) in
('13', '31', '23', '29', '30', '18', '17'))
select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=4,runtime_bloom_filter_size=4194304) */
cntrycode,
count(*) as numcust,
sum(c_acctbal) as totacctbal
from
(
select
substring(c_phone, 1, 2) as cntrycode,
c_acctbal
from
orders right anti join customer c on o_custkey = c.c_custkey join tmp on c.c_acctbal > tmp.av
where
substring(c_phone, 1, 2) in
('13', '31', '23', '29', '30', '18', '17')
) as custsale
group by
cntrycode
order by
cntrycode;