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【Doris】-工具SQLConverter

ops 2025/8/16 10:39:51

Doris SQL Converter

介绍

Doris 可以支持多种 SQL 方言，如 Presto、Trino、Hive、PostgreSQL、Spark、Clickhouse 等等。通过这个功能，用户可以直接使用对应的 SQL 方言查询 Doris 中的数据，方便用户将原先的业务平滑的迁移到 Doris 中。
建表语句、查询、更新等语句在线转化成Doris语言。

安装

下载地址：https://enterprise-doris-releases.oss-accelerate.aliyuncs.com/sql-converter/sql-converter-1.0.7-bin-x64.tar.gz
在任意 FE 节点，通过以下命令启动服务：

# 配置服务端口
vim apiserver/conf/config.conf# 启动 SQL Converter for Apache Doris 转换服务
sh apiserver/bin/start.sh# 如需前端界面，可在 webserver 中配置相应的端口并启动，不需要前端则可以忽略以下操作
vim webserver/conf/config.conf# 启动前端界面
sh webserver/bin/start.sh

提示
该服务是一个无状态的服务，可随时启停
在 apiserver/conf/config.conf 中配置 port 来指定任意一个可用端口，配置 workers 来指定启动的线程数量。在并发场景中，可以根据需要调整，默认为 1
建议在每个 FE 节点都单独启动一个服务

如需启动前端界面，可以在 webserver/conf/config.conf 中配置 SQL Converter for Apache Doris 转换服务地址，默认是 API_HOST=http://127.0.0.1:5001

通过以下命令，在 Doris 中设置 SQL 方言转换服务的 URL：

set global sql_converter_service_url = "http://127.0.0.1:5001/api/v1/convert,"http://127.0.0.2:5001/api/v1/convert""

127.0.0.1:5001 是 SQL 方言转换服务的部署节点 ip 和端口。
Web server started on http://127.0.0.1:3001/ with api_host: http://127.0.0.1:5001.

web访问地址

http://127.0.0.1:3001/

示例

CREATE TABLE  test_sqlconvert (id INT,start_time DATETIME,value STRING,arr_int ARRAY<INT>,arr_str ARRAY<STRING>
) ENGINE=OLAP
DUPLICATE KEY(`id`)
COMMENT 'OLAP'
DISTRIBUTED BY HASH(`id`) BUCKETS 1
PROPERTIES ("replication_allocation" = "tag.location.default: 1"
);INSERT INTO test_sqlconvert VALUES(1, '2024-05-20 13:14:52', '2024-01-14',[1, 2, 3, 3], ['Hello', 'World']);SET sql_dialect = presto;SELECT CAST(start_time AS varchar(20)) AS col1,array_distinct(arr_int) AS col2,FILTER(arr_str, x -> x LIKE '%World%') AS col3,to_date(value,'%Y-%m-%d') AS col4,YEAR(start_time) AS col5,date_add('month', 1, start_time) AS col6,REGEXP_EXTRACT_ALL(value, '-.') AS col7,JSON_EXTRACT('{"id": "33"}', '$.id')AS col8,element_at(arr_int, 1) AS col9,date_trunc('day',start_time) AS col10FROM test_sqlconvertWHERE date_trunc('day',start_time) = DATE '2024-05-20'     
ORDER BY id;
+---------------------+-----------+-----------+------------+------+---------------------+-------------+------+------+---------------------+
| col1                | col2      | col3      | col4       | col5 | col6                | col7        | col8 | col9 | col10               |
+---------------------+-----------+-----------+------------+------+---------------------+-------------+------+------+---------------------+
| 2024-05-20 13:14:52 | [1, 2, 3] | ["World"] | 2024-01-14 | 2024 | 2024-06-20 13:14:52 | ['-0','-1'] | "33" |    1 | 2024-05-20 00:00:00 |
+---------------------+-----------+-----------+------------+------+---------------------+-------------+------+------+---------------------+SET sql_dialect = clickhouse;SELECT toString(start_time) AS col1,arrayCompact(arr_int) AS col2,arrayFilter(x -> x LIKE '%World%',arr_str) AS col3,toDate(value) AS col4,toYear(start_time) AS col5,addMonths(start_time, 1) AS col6,extractAll(value, '-.') AS col7,JSONExtractString('{"id": "33"}' , 'id') AS col8,arrayElement(arr_int, 1) AS col9,date_trunc('day',start_time) AS col10FROM test_sqlconvertWHERE date_trunc('day',start_time)= '2024-05-20 00:00:00'     
ORDER BY id;
+---------------------+-----------+-----------+------------+------+---------------------+-------------+------+------+---------------------+
| col1                | col2      | col3      | col4       | col5 | col6                | col7        | col8 | col9 | col10               |
+---------------------+-----------+-----------+------------+------+---------------------+-------------+------+------+---------------------+
| 2024-05-20 13:14:52 | [1, 2, 3] | ["World"] | 2024-01-14 | 2024 | 2024-06-20 13:14:52 | ['-0','-1'] | "33" |    1 | 2024-05-20 00:00:00 |
+---------------------+-----------+-----------+------------+------+---------------------+-------------+------+------+---------------------+

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