TPCDS
使用须知
TPCDS Catalog 通过 Trino Connector 兼容框架，使用 TPCDS Connector 来快速构建 TPCDS 测试集。
提示
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 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 |
+--------------------+
11 rows in set (0.00 sec)
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 |
+------------------------+
25 rows in set (0.00 sec)
通过 SELECT 语句可以直接查询这些表。
提示
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。
最佳实践
快速构建 TPCDS 测试数据集
可以通过 CTAS 语句快速构建一个 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 ;
提示
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。
