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ドキュメントTencent Cloud TCHouse-DPerformance TestingTPC-H Performance TestingTest Scheme Introduction

Test Scheme Introduction

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最終更新日: 2025-01-07 11:19:57
This document will introduce how to use TPC-H (Business Intelligence Computing Test) to perform performance testing on Tencent Cloud TCHouse-D. Taking the TPC-H query performance of a 16-core cluster under a 100 GB data set as an example, a reference test scheme is given.

About TPC-H Performance Test

TPC-H is a decision support benchmark that consists of a set of business-oriented ad hoc queries and concurrent data modifications. The data it queries and populates in the database is extensively industry-related. This benchmark test demonstrates the ability of a decision support system to examine large amounts of data, perform highly complex queries, and answer critical business questions. The performance metric reported by TPC-H is called TPC-H Composite Query-per-Hour Performance Metric (QphH@Size), which reflects the system's ability to process multiple queries.
Note:
TPC-H simulates a data warehouse of a sales system. The benchmark test includes 22 queries in total, and the main evaluation metric is the response time of each query, that is, the time required from submitting the query to returning the result. TPC-H test results can comprehensively reflect the system's ability to process queries.

Test Scheme Introduction

Test Environment Preparation

Hardware Environment

In the reference scheme given in this document, the tested cluster includes 1 FE and 3 BEs. The FE/BE node processes are deployed separately. The specific specifications are as follows. It should be noted that in actual testing, such a large amount of hardware resources will not be consumed.
Node Type
Node Specifications
1 FE, standard
CPU:4 cores
Memory: 16 GB
Hard disk: Enhanced SSD Cloud Disk 200 GB
3 BEs, standard
CPU:16 cores
Memory: 64 GB
Hard disk: Enhanced SSD Cloud Disk 1000 GB

Software Version

Tencent Cloud TChouse-D 1.2.7

Test Script Preparation

Download the TPC-H toolkit from Toolkit Address and compile it.

TPC-H 100 G Data Test

Generating a 100 G Data Set

sh gen-tpch-data.sh -s 100 -c 10
The data generated is shown in the following table:
TPC-H Table Name
Number of rows
Remarks
REGION
5
Region Table
NATION
25
Country Table
SUPPLIER
1 million
Supplier Table
PART
20 million
Parts List
PARTSUPP
80 million
Parts Supply List
CUSTOMER
15 million
Customer Table
ORDERS
150 million
Order Table
LINEITEM
600 million
Order Details Table

Creating a Table

Modify the doris-cluster.conf configuration file.
Modify configuration: FE_HOST, PASSWORD, DB.
# cat doris-cluster.conf

# 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='tpch_100g_decimalv3'
# The scale of testing data
export SCALE='100g' # only support '100g' or '1t'
Create a table.
sh create-tpch-tables.sh

Importing the Data

sh load-tpch-data.sh


MySQL [tpch100g]> show data;
+-----------+-------------+--------------+
| TableName | Size        | ReplicaCount |
+-----------+-------------+--------------+
| customer  | 1.317 GB    | 24           |
| lineitem  | 20.880 GB   | 96           |
| nation    | 2.571 KB    | 1            |
| orders    | 6.302 GB    | 96           |
| part      | 752.470 MB  | 24           |
| partsupp  | 4.375 GB    | 24           |
| region    | 1.090 KB    | 1            |
| supplier  | 85.528 MB   | 12           |
| Total     | 33.693 GB   | 278          |
| Quota     | 1024.000 TB | 1073741824   |
| Left      | 1023.967 TB | 1073741546   |
+-----------+-------------+--------------+
11 rows in set (0.00 sec)

Querying

[root@9 tpch-tools]# sh bin/run-tpch-queries.sh 
q1: 2103
q2: 305
q3: 792
q4: 516
q5: 1036
q6: 60
q7: 493
q8: 954
q9: 4411
q10: 870
q11: 183
q12: 1847
q13: 2886
q14: 165
q15: 255
q16: 398
q17: 520
q18: 1665
q19: 468
q20: 347
q21: 1741
q22: 412
total time: 22427 ms
Till then, TCP-H data generation, table creation, import, and query under the 100 GB data set scene is completed.
前の記事へ: Accessing TCHouse-D via JDBC over the Public Network次の記事へ: Test Results for Reference

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