在 Hive/Iceberg 上构建 TPC-DS 数据集
Doris 支持通过 Trino Connector (opens in a new tab) 兼容框架，使用 TPCDS Connector (opens in a new tab) 来快速构建 TPCDS 测试集。
结合 Hive/Iceberg 表的数据写回功能，您可以快速通过 Doris 构建 Doris、Hive、Iceberg 表的 TPCDS 测试数据集。
本文档主要介绍如何部署和使用 TPCDS Connector 构建测试数据集。
:::tip 该功能自 Doris 3.0.0 版本开始支持。 :::
编译 TPCDS Connector
需要 JDK 17 版本。
git clone https://github.com/trinodb/trino.git
git checkout 435
cd trino/plugin/trino-tpcds
mvn clean install -DskipTest完成编译后，会在 trino/plugin/trino-tpcds/target/ 下得到 trino-tpcds-435/ 目录。
也可以直接下载预编译的 trino-tpcds-435.tar.gz (opens in a new tab) 并解压。
部署 TPCDS Connector
将 trino-tpcds-435/ 目录放到所有 FE 和 BE 部署路径的 connectors/ 目录下。（如果没有，可以手动创建）。
├── bin
├── conf
├── connectors
│ ├── trino-tpcds-435
...部署完成后，建议重启 FE、BE 节点以确保 Connector 可以被正确加载。
创建 TPCDS Catalog
CREATE CATALOG `tpcds` PROPERTIES (
"type" = "trino-connector",
"trino.connector.name" = "tpcds",
"trino.tpcds.split-count" = "32"
);其中 tpcds.split-count 为并发数，建议设置为 BE 单机核数的 2 倍，可以获得最优的并发度。提升数据生成效率。
使用 TPCDS Catalog
TPCDS Catalog 中预制了不同 Scale Factor 的 TPCDS 数据集，可以通过 SHOW DATABASES 和 SHOW TABLES 命令查看。
mysql> SWITCH tpcds;
Query OK, 0 rows affected (0.00 sec)
mysql> SHOW DATABASES;
+--------------------+
| Database |
+--------------------+
| information_schema |
| mysql |
| sf1 |
| sf100 |
| sf1000 |
| sf10000 |
| sf100000 |
| sf300 |
| sf3000 |
| sf30000 |
| tiny |
+--------------------+
mysql> USE sf1;
mysql> SHOW TABLES;
+------------------------+
| Tables_in_sf1 |
+------------------------+
| call_center |
| catalog_page |
| catalog_returns |
| catalog_sales |
| customer |
| customer_address |
| customer_demographics |
| date_dim |
| dbgen_version |
| household_demographics |
| income_band |
| inventory |
| item |
| promotion |
| reason |
| ship_mode |
| store |
| store_returns |
| store_sales |
| time_dim |
| warehouse |
| web_page |
| web_returns |
| web_sales |
| web_site |
+------------------------+通过 SELECT 语句可以直接查询这些表。
:::tip
这些预制数据集的数据，并没有实际存储，而是在查询时实时生成的。所以这些预制数据集不适合用来直接进行 Benchmark 测试。适用于通过 INSERT INTO SELECT 将数据集写入到其他目的表（如 Doris 内表、Hive、Iceberg 等所有 Doris 支持写入的数据源）后，对目的表进行性能测试。
:::
构建 TPCDS 测试数据集
以下示例通过 CTAS 语句快速构建一个 Hive 上的 TPCDS 测试数据集：
CREATE TABLE hive.tpcds100.call_center PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.call_center ;
CREATE TABLE hive.tpcds100.catalog_page PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.catalog_page ;
CREATE TABLE hive.tpcds100.catalog_returns PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.catalog_returns ;
CREATE TABLE hive.tpcds100.catalog_sales PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.catalog_sales ;
CREATE TABLE hive.tpcds100.customer PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.customer ;
CREATE TABLE hive.tpcds100.customer_address PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.customer_address ;
CREATE TABLE hive.tpcds100.customer_demographics PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.customer_demographics ;
CREATE TABLE hive.tpcds100.date_dim PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.date_dim ;
CREATE TABLE hive.tpcds100.dbgen_version PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.dbgen_version ;
CREATE TABLE hive.tpcds100.household_demographics PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.household_demographics;
CREATE TABLE hive.tpcds100.income_band PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.income_band ;
CREATE TABLE hive.tpcds100.inventory PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.inventory ;
CREATE TABLE hive.tpcds100.item PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.item ;
CREATE TABLE hive.tpcds100.promotion PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.promotion ;
CREATE TABLE hive.tpcds100.reason PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.reason ;
CREATE TABLE hive.tpcds100.ship_mode PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.ship_mode ;
CREATE TABLE hive.tpcds100.store PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.store ;
CREATE TABLE hive.tpcds100.store_returns PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.store_returns ;
CREATE TABLE hive.tpcds100.store_sales PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.store_sales ;
CREATE TABLE hive.tpcds100.time_dim PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.time_dim ;
CREATE TABLE hive.tpcds100.warehouse PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.warehouse ;
CREATE TABLE hive.tpcds100.web_page PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.web_page ;
CREATE TABLE hive.tpcds100.web_returns PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.web_returns ;
CREATE TABLE hive.tpcds100.web_sales PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.web_sales ;
CREATE TABLE hive.tpcds100.web_site PROPERTIES("file_format" = "parquet") AS SELECT * FROM tpcds.sf100.web_site ;:::tip 在包含 3 个 16C BE 节点的 Doris 集群上，创建一个 TPCDS 1000 的 Hive 数据集，大约需要 3 到 4 个小时。 :::