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

HardwareConfiguration Instructions
Number of mMachines4 Tencent Cloud Virtual Machine(1FE,3BEs)
CPUIntel Xeon(Cascade Lake) Platinum 8269CY 16C (2.5 GHz/3.2 GHz)
Memory64G
Network5Gbps
DiskESSD 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 NameRowsSize after ImportAnnotation
REGION5400KBRegion
NATION257.714 KBNation
SUPPLIER1,000,00085.528 MBSupplier
PART20,000,000752.330 MBParts
PARTSUPP20,000,0004.375 GBParts Supply
CUSTOMER15,000,0001.317 GBCustomer
ORDERS1,50,000,0006.301 GBOrders
LINEITEM6,00,000,00020.882 GBOrder 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. 1. enable_vectorized_engine=true,
  2. 2. batch_size=4096,
  3. 3. disable_join_reorder=false
  4. 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:

QueryApache Doris 1.2.0-rc01 (ms)Apache Doris 1.1.3 (ms)Apache Doris 0.15.0 RC04 (ms)
Q12.123.7528.63
Q20.204.227.88
Q30.622.649.39
Q40.611.59.3
Q51.052.154.11
Q60.080.190.43
Q70.581.041.61
Q80.721.7550.35
Q93.617.9416.34
Q101.261.415.21
Q110.150.351.72
Q120.210.575.39
Q132.628.1520.88
Q140.160.3
Q150.300.661.86
Q160.380.791.32
Q170.651.5126.67
Q182.283.36411.77
Q190.200.8291.71
Q200.212.775.2
Q211.174.4710.34
Q220.460.93.22
Total19.6451.253223.33

image-20220614114351241

  • 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.

  1. 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:

  1. 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:

  1. # Any of FE host
  2. export FE_HOST='127.0.0.1'
  3. # http_port in fe.conf
  4. export FE_HTTP_PORT=8030
  5. # query_port in fe.conf
  6. export FE_QUERY_PORT=9030
  7. # Doris username
  8. export USER='root'
  9. # Doris password
  10. export PASSWORD=''
  11. # The database where TPC-H tables located
  12. export DB='tpch1'

Execute the Following Script to Generate and Create TPC-H Table

  1. 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:

  1. 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.

  1. select count(*) from lineitem;
  2. select count(*) from orders;
  3. select count(*) from partsupp;
  4. select count(*) from part;
  5. select count(*) from customer;
  6. select count(*) from supplier;
  7. select count(*) from nation;
  8. select count(*) from region;
  9. select count(*) from revenue0;

7.6 Query Test

7.6.1 Executing Query Scripts

Execute the above test SQL or execute the following command

  1. ./run-tpch-queries.sh

Notice:

  1. 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

  2. Doris’ new query optimizer will be released in future versions

  3. Set set mem_exec_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.

  1. --Q1
  2. 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) */
  3. l_returnflag,
  4. l_linestatus,
  5. sum(l_quantity) as sum_qty,
  6. sum(l_extendedprice) as sum_base_price,
  7. sum(l_extendedprice * (1 - l_discount)) as sum_disc_price,
  8. sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)) as sum_charge,
  9. avg(l_quantity) as avg_qty,
  10. avg(l_extendedprice) as avg_price,
  11. avg(l_discount) as avg_disc,
  12. count(*) as count_order
  13. from
  14. lineitem
  15. where
  16. l_shipdate <= date '1998-12-01' - interval '90' day
  17. group by
  18. l_returnflag,
  19. l_linestatus
  20. order by
  21. l_returnflag,
  22. l_linestatus;
  23. --Q2
  24. 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) */
  25. s_acctbal,
  26. s_name,
  27. n_name,
  28. p_partkey,
  29. p_mfgr,
  30. s_address,
  31. s_phone,
  32. s_comment
  33. from
  34. partsupp join
  35. (
  36. select
  37. ps_partkey as a_partkey,
  38. min(ps_supplycost) as a_min
  39. from
  40. partsupp,
  41. part,
  42. supplier,
  43. nation,
  44. region
  45. where
  46. p_partkey = ps_partkey
  47. and s_suppkey = ps_suppkey
  48. and s_nationkey = n_nationkey
  49. and n_regionkey = r_regionkey
  50. and r_name = 'EUROPE'
  51. and p_size = 15
  52. and p_type like '%BRASS'
  53. group by a_partkey
  54. ) A on ps_partkey = a_partkey and ps_supplycost=a_min ,
  55. part,
  56. supplier,
  57. nation,
  58. region
  59. where
  60. p_partkey = ps_partkey
  61. and s_suppkey = ps_suppkey
  62. and p_size = 15
  63. and p_type like '%BRASS'
  64. and s_nationkey = n_nationkey
  65. and n_regionkey = r_regionkey
  66. and r_name = 'EUROPE'
  67. order by
  68. s_acctbal desc,
  69. n_name,
  70. s_name,
  71. p_partkey
  72. limit 100;
  73. --Q3
  74. 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) */
  75. l_orderkey,
  76. sum(l_extendedprice * (1 - l_discount)) as revenue,
  77. o_orderdate,
  78. o_shippriority
  79. from
  80. (
  81. select l_orderkey, l_extendedprice, l_discount, o_orderdate, o_shippriority, o_custkey from
  82. lineitem join orders
  83. where l_orderkey = o_orderkey
  84. and o_orderdate < date '1995-03-15'
  85. and l_shipdate > date '1995-03-15'
  86. ) t1 join customer c
  87. on c.c_custkey = t1.o_custkey
  88. where c_mktsegment = 'BUILDING'
  89. group by
  90. l_orderkey,
  91. o_orderdate,
  92. o_shippriority
  93. order by
  94. revenue desc,
  95. o_orderdate
  96. limit 10;
  97. --Q4
  98. 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) */
  99. o_orderpriority,
  100. count(*) as order_count
  101. from
  102. (
  103. select
  104. *
  105. from
  106. lineitem
  107. where l_commitdate < l_receiptdate
  108. ) t1
  109. right semi join orders
  110. on t1.l_orderkey = o_orderkey
  111. where
  112. o_orderdate >= date '1993-07-01'
  113. and o_orderdate < date '1993-07-01' + interval '3' month
  114. group by
  115. o_orderpriority
  116. order by
  117. o_orderpriority;
  118. --Q5
  119. 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) */
  120. n_name,
  121. sum(l_extendedprice * (1 - l_discount)) as revenue
  122. from
  123. customer,
  124. orders,
  125. lineitem,
  126. supplier,
  127. nation,
  128. region
  129. where
  130. c_custkey = o_custkey
  131. and l_orderkey = o_orderkey
  132. and l_suppkey = s_suppkey
  133. and c_nationkey = s_nationkey
  134. and s_nationkey = n_nationkey
  135. and n_regionkey = r_regionkey
  136. and r_name = 'ASIA'
  137. and o_orderdate >= date '1994-01-01'
  138. and o_orderdate < date '1994-01-01' + interval '1' year
  139. group by
  140. n_name
  141. order by
  142. revenue desc;
  143. --Q6
  144. 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) */
  145. sum(l_extendedprice * l_discount) as revenue
  146. from
  147. lineitem
  148. where
  149. l_shipdate >= date '1994-01-01'
  150. and l_shipdate < date '1994-01-01' + interval '1' year
  151. and l_discount between .06 - 0.01 and .06 + 0.01
  152. and l_quantity < 24;
  153. --Q7
  154. 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) */
  155. supp_nation,
  156. cust_nation,
  157. l_year,
  158. sum(volume) as revenue
  159. from
  160. (
  161. select
  162. n1.n_name as supp_nation,
  163. n2.n_name as cust_nation,
  164. extract(year from l_shipdate) as l_year,
  165. l_extendedprice * (1 - l_discount) as volume
  166. from
  167. supplier,
  168. lineitem,
  169. orders,
  170. customer,
  171. nation n1,
  172. nation n2
  173. where
  174. s_suppkey = l_suppkey
  175. and o_orderkey = l_orderkey
  176. and c_custkey = o_custkey
  177. and s_nationkey = n1.n_nationkey
  178. and c_nationkey = n2.n_nationkey
  179. and (
  180. (n1.n_name = 'FRANCE' and n2.n_name = 'GERMANY')
  181. or (n1.n_name = 'GERMANY' and n2.n_name = 'FRANCE')
  182. )
  183. and l_shipdate between date '1995-01-01' and date '1996-12-31'
  184. ) as shipping
  185. group by
  186. supp_nation,
  187. cust_nation,
  188. l_year
  189. order by
  190. supp_nation,
  191. cust_nation,
  192. l_year;
  193. --Q8
  194. 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) */
  195. o_year,
  196. sum(case
  197. when nation = 'BRAZIL' then volume
  198. else 0
  199. end) / sum(volume) as mkt_share
  200. from
  201. (
  202. select
  203. extract(year from o_orderdate) as o_year,
  204. l_extendedprice * (1 - l_discount) as volume,
  205. n2.n_name as nation
  206. from
  207. lineitem,
  208. orders,
  209. customer,
  210. supplier,
  211. part,
  212. nation n1,
  213. nation n2,
  214. region
  215. where
  216. p_partkey = l_partkey
  217. and s_suppkey = l_suppkey
  218. and l_orderkey = o_orderkey
  219. and o_custkey = c_custkey
  220. and c_nationkey = n1.n_nationkey
  221. and n1.n_regionkey = r_regionkey
  222. and r_name = 'AMERICA'
  223. and s_nationkey = n2.n_nationkey
  224. and o_orderdate between date '1995-01-01' and date '1996-12-31'
  225. and p_type = 'ECONOMY ANODIZED STEEL'
  226. ) as all_nations
  227. group by
  228. o_year
  229. order by
  230. o_year;
  231. --Q9
  232. 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) */
  233. nation,
  234. o_year,
  235. sum(amount) as sum_profit
  236. from
  237. (
  238. select
  239. n_name as nation,
  240. extract(year from o_orderdate) as o_year,
  241. l_extendedprice * (1 - l_discount) - ps_supplycost * l_quantity as amount
  242. from
  243. lineitem join orders on o_orderkey = l_orderkey
  244. join[shuffle] part on p_partkey = l_partkey
  245. join[shuffle] partsupp on ps_partkey = l_partkey
  246. join[shuffle] supplier on s_suppkey = l_suppkey
  247. join[broadcast] nation on s_nationkey = n_nationkey
  248. where
  249. ps_suppkey = l_suppkey and
  250. p_name like '%green%'
  251. ) as profit
  252. group by
  253. nation,
  254. o_year
  255. order by
  256. nation,
  257. o_year desc;
  258. --Q10
  259. 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) */
  260. c_custkey,
  261. c_name,
  262. sum(t1.l_extendedprice * (1 - t1.l_discount)) as revenue,
  263. c_acctbal,
  264. n_name,
  265. c_address,
  266. c_phone,
  267. c_comment
  268. from
  269. customer,
  270. (
  271. select o_custkey,l_extendedprice,l_discount from lineitem, orders
  272. where l_orderkey = o_orderkey
  273. and o_orderdate >= date '1993-10-01'
  274. and o_orderdate < date '1993-10-01' + interval '3' month
  275. and l_returnflag = 'R'
  276. ) t1,
  277. nation
  278. where
  279. c_custkey = t1.o_custkey
  280. and c_nationkey = n_nationkey
  281. group by
  282. c_custkey,
  283. c_name,
  284. c_acctbal,
  285. c_phone,
  286. n_name,
  287. c_address,
  288. c_comment
  289. order by
  290. revenue desc
  291. limit 20;
  292. --Q11
  293. 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) */
  294. ps_partkey,
  295. sum(ps_supplycost * ps_availqty) as value
  296. from
  297. partsupp,
  298. (
  299. select s_suppkey
  300. from supplier, nation
  301. where s_nationkey = n_nationkey and n_name = 'GERMANY'
  302. ) B
  303. where
  304. ps_suppkey = B.s_suppkey
  305. group by
  306. ps_partkey having
  307. sum(ps_supplycost * ps_availqty) > (
  308. select
  309. sum(ps_supplycost * ps_availqty) * 0.000002
  310. from
  311. partsupp,
  312. (select s_suppkey
  313. from supplier, nation
  314. where s_nationkey = n_nationkey and n_name = 'GERMANY'
  315. ) A
  316. where
  317. ps_suppkey = A.s_suppkey
  318. )
  319. order by
  320. value desc;
  321. --Q12
  322. 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) */
  323. l_shipmode,
  324. sum(case
  325. when o_orderpriority = '1-URGENT'
  326. or o_orderpriority = '2-HIGH'
  327. then 1
  328. else 0
  329. end) as high_line_count,
  330. sum(case
  331. when o_orderpriority <> '1-URGENT'
  332. and o_orderpriority <> '2-HIGH'
  333. then 1
  334. else 0
  335. end) as low_line_count
  336. from
  337. orders,
  338. lineitem
  339. where
  340. o_orderkey = l_orderkey
  341. and l_shipmode in ('MAIL', 'SHIP')
  342. and l_commitdate < l_receiptdate
  343. and l_shipdate < l_commitdate
  344. and l_receiptdate >= date '1994-01-01'
  345. and l_receiptdate < date '1994-01-01' + interval '1' year
  346. group by
  347. l_shipmode
  348. order by
  349. l_shipmode;
  350. --Q13
  351. 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) */
  352. c_count,
  353. count(*) as custdist
  354. from
  355. (
  356. select
  357. c_custkey,
  358. count(o_orderkey) as c_count
  359. from
  360. orders right outer join customer on
  361. c_custkey = o_custkey
  362. and o_comment not like '%special%requests%'
  363. group by
  364. c_custkey
  365. ) as c_orders
  366. group by
  367. c_count
  368. order by
  369. custdist desc,
  370. c_count desc;
  371. --Q14
  372. 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) */
  373. 100.00 * sum(case
  374. when p_type like 'PROMO%'
  375. then l_extendedprice * (1 - l_discount)
  376. else 0
  377. end) / sum(l_extendedprice * (1 - l_discount)) as promo_revenue
  378. from
  379. part,
  380. lineitem
  381. where
  382. l_partkey = p_partkey
  383. and l_shipdate >= date '1995-09-01'
  384. and l_shipdate < date '1995-09-01' + interval '1' month;
  385. --Q15
  386. 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) */
  387. s_suppkey,
  388. s_name,
  389. s_address,
  390. s_phone,
  391. total_revenue
  392. from
  393. supplier,
  394. revenue0
  395. where
  396. s_suppkey = supplier_no
  397. and total_revenue = (
  398. select
  399. max(total_revenue)
  400. from
  401. revenue0
  402. )
  403. order by
  404. s_suppkey;
  405. --Q16
  406. 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) */
  407. p_brand,
  408. p_type,
  409. p_size,
  410. count(distinct ps_suppkey) as supplier_cnt
  411. from
  412. partsupp,
  413. part
  414. where
  415. p_partkey = ps_partkey
  416. and p_brand <> 'Brand#45'
  417. and p_type not like 'MEDIUM POLISHED%'
  418. and p_size in (49, 14, 23, 45, 19, 3, 36, 9)
  419. and ps_suppkey not in (
  420. select
  421. s_suppkey
  422. from
  423. supplier
  424. where
  425. s_comment like '%Customer%Complaints%'
  426. )
  427. group by
  428. p_brand,
  429. p_type,
  430. p_size
  431. order by
  432. supplier_cnt desc,
  433. p_brand,
  434. p_type,
  435. p_size;
  436. --Q17
  437. 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) */
  438. sum(l_extendedprice) / 7.0 as avg_yearly
  439. from
  440. lineitem join [broadcast]
  441. part p1 on p1.p_partkey = l_partkey
  442. where
  443. p1.p_brand = 'Brand#23'
  444. and p1.p_container = 'MED BOX'
  445. and l_quantity < (
  446. select
  447. 0.2 * avg(l_quantity)
  448. from
  449. lineitem join [broadcast]
  450. part p2 on p2.p_partkey = l_partkey
  451. where
  452. l_partkey = p1.p_partkey
  453. and p2.p_brand = 'Brand#23'
  454. and p2.p_container = 'MED BOX'
  455. );
  456. --Q18
  457. 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) */
  458. c_name,
  459. c_custkey,
  460. t3.o_orderkey,
  461. t3.o_orderdate,
  462. t3.o_totalprice,
  463. sum(t3.l_quantity)
  464. from
  465. customer join
  466. (
  467. select * from
  468. lineitem join
  469. (
  470. select * from
  471. orders left semi join
  472. (
  473. select
  474. l_orderkey
  475. from
  476. lineitem
  477. group by
  478. l_orderkey having sum(l_quantity) > 300
  479. ) t1
  480. on o_orderkey = t1.l_orderkey
  481. ) t2
  482. on t2.o_orderkey = l_orderkey
  483. ) t3
  484. on c_custkey = t3.o_custkey
  485. group by
  486. c_name,
  487. c_custkey,
  488. t3.o_orderkey,
  489. t3.o_orderdate,
  490. t3.o_totalprice
  491. order by
  492. t3.o_totalprice desc,
  493. t3.o_orderdate
  494. limit 100;
  495. --Q19
  496. 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) */
  497. sum(l_extendedprice* (1 - l_discount)) as revenue
  498. from
  499. lineitem,
  500. part
  501. where
  502. (
  503. p_partkey = l_partkey
  504. and p_brand = 'Brand#12'
  505. and p_container in ('SM CASE', 'SM BOX', 'SM PACK', 'SM PKG')
  506. and l_quantity >= 1 and l_quantity <= 1 + 10
  507. and p_size between 1 and 5
  508. and l_shipmode in ('AIR', 'AIR REG')
  509. and l_shipinstruct = 'DELIVER IN PERSON'
  510. )
  511. or
  512. (
  513. p_partkey = l_partkey
  514. and p_brand = 'Brand#23'
  515. and p_container in ('MED BAG', 'MED BOX', 'MED PKG', 'MED PACK')
  516. and l_quantity >= 10 and l_quantity <= 10 + 10
  517. and p_size between 1 and 10
  518. and l_shipmode in ('AIR', 'AIR REG')
  519. and l_shipinstruct = 'DELIVER IN PERSON'
  520. )
  521. or
  522. (
  523. p_partkey = l_partkey
  524. and p_brand = 'Brand#34'
  525. and p_container in ('LG CASE', 'LG BOX', 'LG PACK', 'LG PKG')
  526. and l_quantity >= 20 and l_quantity <= 20 + 10
  527. and p_size between 1 and 15
  528. and l_shipmode in ('AIR', 'AIR REG')
  529. and l_shipinstruct = 'DELIVER IN PERSON'
  530. );
  531. --Q20
  532. 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) */
  533. s_name, s_address from
  534. supplier left semi join
  535. (
  536. select * from
  537. (
  538. select l_partkey,l_suppkey, 0.5 * sum(l_quantity) as l_q
  539. from lineitem
  540. where l_shipdate >= date '1994-01-01'
  541. and l_shipdate < date '1994-01-01' + interval '1' year
  542. group by l_partkey,l_suppkey
  543. ) t2 join
  544. (
  545. select ps_partkey, ps_suppkey, ps_availqty
  546. from partsupp left semi join part
  547. on ps_partkey = p_partkey and p_name like 'forest%'
  548. ) t1
  549. on t2.l_partkey = t1.ps_partkey and t2.l_suppkey = t1.ps_suppkey
  550. and t1.ps_availqty > t2.l_q
  551. ) t3
  552. on s_suppkey = t3.ps_suppkey
  553. join nation
  554. where s_nationkey = n_nationkey
  555. and n_name = 'CANADA'
  556. order by s_name;
  557. --Q21
  558. 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) */
  559. s_name, count(*) as numwait
  560. from
  561. lineitem l2 right semi join
  562. (
  563. select * from
  564. lineitem l3 right anti join
  565. (
  566. select * from
  567. orders join lineitem l1 on l1.l_orderkey = o_orderkey and o_orderstatus = 'F'
  568. join
  569. (
  570. select * from
  571. supplier join nation
  572. where s_nationkey = n_nationkey
  573. and n_name = 'SAUDI ARABIA'
  574. ) t1
  575. where t1.s_suppkey = l1.l_suppkey and l1.l_receiptdate > l1.l_commitdate
  576. ) t2
  577. on l3.l_orderkey = t2.l_orderkey and l3.l_suppkey <> t2.l_suppkey and l3.l_receiptdate > l3.l_commitdate
  578. ) t3
  579. on l2.l_orderkey = t3.l_orderkey and l2.l_suppkey <> t3.l_suppkey
  580. group by
  581. t3.s_name
  582. order by
  583. numwait desc,
  584. t3.s_name
  585. limit 100;
  586. --Q22
  587. with tmp as (select
  588. avg(c_acctbal) as av
  589. from
  590. customer
  591. where
  592. c_acctbal > 0.00
  593. and substring(c_phone, 1, 2) in
  594. ('13', '31', '23', '29', '30', '18', '17'))
  595. select /*+SET_VAR(exec_mem_limit=8589934592, parallel_fragment_exec_instance_num=4,runtime_bloom_filter_size=4194304) */
  596. cntrycode,
  597. count(*) as numcust,
  598. sum(c_acctbal) as totacctbal
  599. from
  600. (
  601. select
  602. substring(c_phone, 1, 2) as cntrycode,
  603. c_acctbal
  604. from
  605. orders right anti join customer c on o_custkey = c.c_custkey join tmp on c.c_acctbal > tmp.av
  606. where
  607. substring(c_phone, 1, 2) in
  608. ('13', '31', '23', '29', '30', '18', '17')
  609. ) as custsale
  610. group by
  611. cntrycode
  612. order by
  613. cntrycode;