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S3

S3

Name

s3

description

S3 表函数(table-valued-function,tvf),可以让用户像访问关系表格式数据一样,读取并访问 S3 兼容的对象存储上的文件内容。目前支持csv/csv_with_names/csv_with_names_and_types/json/parquet/orc文件格式。

语法

s3(
"uri" = "..",
"s3.access_key" = "...",
"s3.secret_key" = "...",
"s3.region" = "...",
"format" = "csv",
"keyn" = "valuen",
...
);

参数说明

S3 TVF 中的每一个参数都是一个 "key"="value" 对。 访问 S3 相关参数:

  • uri: (必填) 访问 S3 的 URI,S3 表函数会根据 use_path_style 参数来决定是否使用 Path Style 访问方式,默认为 Virtual-hosted Style 方式
  • s3.access_key: (必填)
  • s3.secret_key: (必填)
  • s3.region: (选填)。如果 Minio 服务设置了其他的 Region,那么必填,否则默认使用us-east-1
  • s3.session_token: (选填)
  • use_path_style:(选填) 默认为false 。S3 SDK 默认使用 Virtual-hosted Syle 方式。但某些对象存储系统可能没开启或没支持 Virtual-hosted Style 方式的访问,此时我们可以添加 use_path_style 参数来强制使用 Path Style 方式。比如 minio 默认情况下只允许 path style 访问方式,所以在访问 MinIO 时要加上 use_path_style=true
  • force_parsing_by_standard_uri:(选填)默认 false 。我们可以添加 force_parsing_by_standard_uri 参数来强制将非标准的 URI 解析为标准 URI。

对于 AWS S3,标准 uri styles 有以下几种:

  1. AWS Client Style(Hadoop S3 Style): s3://my-bucket/path/to/file?versionId=abc123&partNumber=77&partNumber=88
  2. Virtual Host Style:https://my-bucket.s3.us-west-1.amazonaws.com/resources/doc.txt?versionId=abc123&partNumber=77&partNumber=88
  3. Path Style:https://s3.us-west-1.amazonaws.com/my-bucket/resources/doc.txt?versionId=abc123&partNumber=77&partNumber=88

除了支持以上三个标准常见的 URI Styles, 还支持其他一些 URI Styles(也许不常见,但也有可能有):

  1. Virtual Host AWS Client (Hadoop S3) Mixed Style: s3://my-bucket.s3.us-west-1.amazonaws.com/resources/doc.txt?versionId=abc123&partNumber=77&partNumber=88
  2. Path AWS Client (Hadoop S3) Mixed Style: s3://s3.us-west-1.amazonaws.com/my-bucket/resources/doc.txt?versionId=abc123&partNumber=77&partNumber=88

详细使用案例可以参考最下方 Best Practice。

文件格式参数:

  • format:(必填) 目前支持 csv/csv_with_names/csv_with_names_and_types/json/parquet/orc
  • column_separator:(选填) 列分割符,默认为\t
  • line_delimiter:(选填) 行分割符,默认为\n
  • compress_type: (选填) 目前支持 UNKNOWN/PLAIN/GZ/LZO/BZ2/LZ4FRAME/DEFLATE/SNAPPYBLOCK。默认值为 UNKNOWN, 将会根据 uri 的后缀自动推断类型。

下面 6 个参数是用于 JSON 格式的导入,具体使用方法可以参照:Json Load

  • read_json_by_line: (选填) 默认为 "true"
  • strip_outer_array: (选填) 默认为 "false"
  • json_root: (选填) 默认为空
  • jsonpaths: (选填) 默认为空
  • num_as_string: (选填) 默认为 false
  • fuzzy_parse: (选填) 默认为 false

下面 2 个参数是用于 CSV 格式的导入

  • trim_double_quotes:布尔类型,选填,默认值为 false,为 true 时表示裁剪掉 CSV 文件每个字段最外层的双引号
  • skip_lines:整数类型,选填,默认值为 0,含义为跳过 CSV 文件的前几行。当设置 format 设置为 csv_with_namescsv_with_names_and_types 时,该参数会失效

其他参数:

  • path_partition_keys:(选填)指定文件路径中携带的分区列名,例如 /path/to/city=beijing/date="2023-07-09", 则填写 path_partition_keys="city,date",将会自动从路径中读取相应列名和列值进行导入。
  • resource:(选填)指定 Resource 名,S3 TVF 可以利用已有的 S3 Resource 来直接访问 S3。创建 S3 Resource 的方法可以参照 CREATE-RESOURCE。该功能自 2.1.4 版本开始支持。
注意

直接查询 TVF 或基于该 TVF 创建 View ,需要拥有该 Resource 的 USAGE 权限,查询基于 TVF 创建的 View ,只需要该 View 的 SELECT 权限。

Example

读取并访问 S3 兼容的对象存储上的 CSV 格式文件

select * from s3("uri" = "http://127.0.0.1:9312/test2/student1.csv",
"s3.access_key"= "minioadmin",
"s3.secret_key" = "minioadmin",
"format" = "csv",
"use_path_style" = "true") order by c1;

可以配合 desc function 使用

MySQL [(none)]> Desc function s3("uri" = "http://127.0.0.1:9312/test2/student1.csv",
"s3.access_key"= "minioadmin",
"s3.secret_key" = "minioadmin",
"format" = "csv",
"use_path_style" = "true");

Keywords

S3, table-valued-function, TVF

Best Practice

不同 url schema 的写法 http:// 、https:// 使用示例:

// 注意URI Bucket写法以及`use_path_style`参数设置,HTTP 同理。
// 由于设置了 `"use_path_style"="true"`, 所以将采用 Path Style 的方式访问 S3。
select * from s3(
"uri" = "https://endpoint/bucket/file/student.csv",
"s3.access_key"= "ak",
"s3.secret_key" = "sk",
"format" = "csv",
"use_path_style"="true");

// 注意 URI Bucket写法以及use_path_style参数设置,http同理。
// 由于设置了 `"use_path_style"="false"`, 所以将采用 Virtual-hosted Style 方式访问 S3。
select * from s3(
"uri" = "https://bucket.endpoint/bucket/file/student.csv",
"s3.access_key"= "ak",
"s3.secret_key" = "sk",
"format" = "csv",
"use_path_style"="false");

// 阿里云 OSS 和腾讯云 COS 采用 Virtual-hosted Style 方式访问 S3。
// OSS
select * from s3(
"uri" = "http://example-bucket.oss-cn-beijing.aliyuncs.com/your-folder/file.parquet",
"s3.access_key"= "ak",
"s3.secret_key" = "sk",
"s3.region" = "oss-cn-beijing",
"format" = "parquet",
"use_path_style" = "false");
// COS
select * from s3(
"uri" = "https://example-bucket.cos.ap-hongkong.myqcloud.com/your-folder/file.parquet",
"s3.access_key"= "ak",
"s3.secret_key" = "sk",
"s3.region" = "ap-hongkong",
"format" = "parquet",
"use_path_style" = "false");

// MinIO
select * from s3(
"uri" = "s3://bucket/file.csv",
"s3.endpoint" = "http://172.21.0.101:9000",
"s3.access_key"= "ak",
"s3.secret_key" = "sk",
"s3.region" = "us-east-1",
"format" = "csv"
);

// 百度云 BOS 采用兼容 S3 协议的 Virtual-hosted Style 方式访问 S3。
// BOS
select * from s3(
"uri" = "https://example-bucket.s3.bj.bcebos.com/your-folder/file.parquet",
"s3.access_key"= "ak",
"s3.secret_key" = "sk",
"s3.region" = "bj",
"format" = "parquet",
"use_path_style" = "false");

s3:// 使用示例:

// 注意 URI Bucket 写法, 无需设置 `use_path_style` 参数。
// 将采用 Virtual-hosted Style 方式访问 S3。
select * from s3(
"uri" = "s3://bucket/file/student.csv",
"s3.endpoint"= "endpont",
"s3.region"= "region",
"s3.access_key"= "ak",
"s3.secret_key" = "sk",
"format" = "csv");

其它支持的 URI 风格示例:

// Virtual Host AWS Client (Hadoop S3) Mixed Style。通过设置 `use_path_style = false` 以及 `force_parsing_by_standard_uri = true` 来使用。
select * from s3(
"URI" = "s3://my-bucket.s3.us-west-1.amazonaws.com/resources/doc.txt?versionId=abc123&partNumber=77&partNumber=88",
"s3.access_key"= "ak",
"s3.secret_key" = "sk",
"format" = "csv",
"use_path_style"="false",
"force_parsing_by_standard_uri"="true");

// Path AWS Client (Hadoop S3) Mixed Style。通过设置 `use_path_style = true` 以及 `force_parsing_by_standard_uri = true` 来使用。
select * from s3(
"URI" = "s3://s3.us-west-1.amazonaws.com/my-bucket/resources/doc.txt?versionId=abc123&partNumber=77&partNumber=88",
"s3.access_key"= "ak",
"s3.secret_key" = "sk",
"format" = "csv",
"use_path_style"="true",
"force_parsing_by_standard_uri"="true");

CSV format 由于 S3 table-valued-function 事先并不知道 Table Schema,所以会先读一遍文件来解析出 Table Schema。

csv 格式:S3 table-valued-function 读取 S3 上的文件并当作 CSV 文件来处理,读取文件中的第一行用于解析 Table Schema。文件第一行的列个数 n 将作为 Table Schema 的列个数,Table Schema 的列名则自动取名为 c1, c2, ..., cn ,列类型都设置为 String, 举例:

student1.csv 文件内容为:

1,ftw,12
2,zs,18
3,ww,20

使用 S3 TVF

MySQL [(none)]> select * from s3("uri" = "http://127.0.0.1:9312/test2/student1.csv",
-> "s3.access_key"= "minioadmin",
-> "s3.secret_key" = "minioadmin",
-> "format" = "csv",
-> "use_path_style" = "true") order by c1;
+------+------+------+
| c1 | c2 | c3 |
+------+------+------+
| 1 | ftw | 12 |
| 2 | zs | 18 |
| 3 | ww | 20 |
+------+------+------+

可以配合 desc function S3() 来查看 Table Schema

MySQL [(none)]> Desc function s3("uri" = "http://127.0.0.1:9312/test2/student1.csv",
-> "s3.access_key"= "minioadmin",
-> "s3.secret_key" = "minioadmin",
-> "format" = "csv",
-> "use_path_style" = "true");
+-------+------+------+-------+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------+------+------+-------+---------+-------+
| c1 | TEXT | Yes | false | NULL | NONE |
| c2 | TEXT | Yes | false | NULL | NONE |
| c3 | TEXT | Yes | false | NULL | NONE |
+-------+------+------+-------+---------+-------+

csv_with_names format csv_with_names 格式:解析文件的第一行作为 Table Schema 的列个数和列名,列类型则都设置为 String, 举例:

student_with_names.csv 文件内容为

id,name,age
1,ftw,12
2,zs,18
3,ww,20

使用 S3 tvf

MySQL [(none)]> select * from s3("uri" = "http://127.0.0.1:9312/test2/student_with_names.csv",
-> "s3.access_key"= "minioadmin",
-> "s3.secret_key" = "minioadmin",
-> "format" = "csv_with_names",
-> "use_path_style" = "true") order by id;
+------+------+------+
| id | name | age |
+------+------+------+
| 1 | ftw | 12 |
| 2 | zs | 18 |
| 3 | ww | 20 |
+------+------+------+

同样配合 desc function S3() 可查看 Table Schema

MySQL [(none)]> Desc function s3("uri" = "http://127.0.0.1:9312/test2/student_with_names.csv",
-> "s3.access_key"= "minioadmin",
-> "s3.secret_key" = "minioadmin",
-> "format" = "csv_with_names",
-> "use_path_style" = "true");
+-------+------+------+-------+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------+------+------+-------+---------+-------+
| id | TEXT | Yes | false | NULL | NONE |
| name | TEXT | Yes | false | NULL | NONE |
| age | TEXT | Yes | false | NULL | NONE |
+-------+------+------+-------+---------+-------+

csv_with_names_and_types foramt

csv_with_names_and_types 格式:目前暂不支持从 CSV 文件中解析出 Column Type。使用该 Format 时,S3 TVF 会解析文件的第一行作为 Table Schema 的列个数和列名,列类型则都设置为 String,同时将忽略该文件的第二行。

student_with_names_and_types.csv 文件内容为

id,name,age
INT,STRING,INT
1,ftw,12
2,zs,18
3,ww,20

使用 S3 TVF

MySQL [(none)]> select * from s3("uri" = "http://127.0.0.1:9312/test2/student_with_names_and_types.csv",
-> "s3.access_key"= "minioadmin",
-> "s3.secret_key" = "minioadmin",
-> "format" = "csv_with_names_and_types",
-> "use_path_style" = "true") order by id;
+------+------+------+
| id | name | age |
+------+------+------+
| 1 | ftw | 12 |
| 2 | zs | 18 |
| 3 | ww | 20 |
+------+------+------+

同样配合 desc function S3() 可查看 Table Schema

MySQL [(none)]> Desc function s3("uri" = "http://127.0.0.1:9312/test2/student_with_names_and_types.csv",
-> "s3.access_key"= "minioadmin",
-> "s3.secret_key" = "minioadmin",
-> "format" = "csv_with_names_and_types",
-> "use_path_style" = "true");
+-------+------+------+-------+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------+------+------+-------+---------+-------+
| id | TEXT | Yes | false | NULL | NONE |
| name | TEXT | Yes | false | NULL | NONE |
| age | TEXT | Yes | false | NULL | NONE |
+-------+------+------+-------+---------+-------+

JSON format

json 格式:JSON 格式涉及到较多的可选参数,各个参数的意义可以参考:Json Load。S3 TVF 查询 JSON 格式文件时根据 json_rootjsonpaths 参数定位到一个 JSON 对象,将该对象的中的 key 作为 Table Schema 的列名,列类型都设置为 String。举例:

data.json 文件

[{"id":1, "name":"ftw", "age":18}]
[{"id":2, "name":"xxx", "age":17}]
[{"id":3, "name":"yyy", "age":19}]

使用 S3 TVF 查询

MySQL [(none)]> select * from s3(
"uri" = "http://127.0.0.1:9312/test2/data.json",
"s3.access_key"= "minioadmin",
"s3.secret_key" = "minioadmin",
"format" = "json",
"strip_outer_array" = "true",
"read_json_by_line" = "true",
"use_path_style"="true");
+------+------+------+
| id | name | age |
+------+------+------+
| 1 | ftw | 18 |
| 2 | xxx | 17 |
| 3 | yyy | 19 |
+------+------+------+

MySQL [(none)]> select * from s3(
"uri" = "http://127.0.0.1:9312/test2/data.json",
"s3.access_key"= "minioadmin",
"s3.secret_key" = "minioadmin",
"format" = "json",
"strip_outer_array" = "true",
"jsonpaths" = "[\"$.id\", \"$.age\"]",
"use_path_style"="true");
+------+------+
| id | age |
+------+------+
| 1 | 18 |
| 2 | 17 |
| 3 | 19 |
+------+------+

Parquet format

parquet 格式:S3 TVF 支持从 Parquet 文件中解析出 Table Schema 的列名、列类型。举例:

MySQL [(none)]> select * from s3(
"uri" = "http://127.0.0.1:9312/test2/test.snappy.parquet",
"s3.access_key"= "minioadmin",
"s3.secret_key" = "minioadmin",
"format" = "parquet",
"use_path_style"="true") limit 5;
+-----------+------------------------------------------+----------------+----------+-------------------------+--------+-------------+---------------+---------------------+
| p_partkey | p_name | p_mfgr | p_brand | p_type | p_size | p_container | p_retailprice | p_comment |
+-----------+------------------------------------------+----------------+----------+-------------------------+--------+-------------+---------------+---------------------+
| 1 | goldenrod lavender spring chocolate lace | Manufacturer#1 | Brand#13 | PROMO BURNISHED COPPER | 7 | JUMBO PKG | 901 | ly. slyly ironi |
| 2 | blush thistle blue yellow saddle | Manufacturer#1 | Brand#13 | LARGE BRUSHED BRASS | 1 | LG CASE | 902 | lar accounts amo |
| 3 | spring green yellow purple cornsilk | Manufacturer#4 | Brand#42 | STANDARD POLISHED BRASS | 21 | WRAP CASE | 903 | egular deposits hag |
| 4 | cornflower chocolate smoke green pink | Manufacturer#3 | Brand#34 | SMALL PLATED BRASS | 14 | MED DRUM | 904 | p furiously r |
| 5 | forest brown coral puff cream | Manufacturer#3 | Brand#32 | STANDARD POLISHED TIN | 15 | SM PKG | 905 | wake carefully |
+-----------+------------------------------------------+----------------+----------+-------------------------+--------+-------------+---------------+---------------------+
MySQL [(none)]> desc function s3(
"uri" = "http://127.0.0.1:9312/test2/test.snappy.parquet",
"s3.access_key"= "minioadmin",
"s3.secret_key" = "minioadmin",
"format" = "parquet",
"use_path_style"="true");
+---------------+--------------+------+-------+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+---------------+--------------+------+-------+---------+-------+
| p_partkey | INT | Yes | false | NULL | NONE |
| p_name | TEXT | Yes | false | NULL | NONE |
| p_mfgr | TEXT | Yes | false | NULL | NONE |
| p_brand | TEXT | Yes | false | NULL | NONE |
| p_type | TEXT | Yes | false | NULL | NONE |
| p_size | INT | Yes | false | NULL | NONE |
| p_container | TEXT | Yes | false | NULL | NONE |
| p_retailprice | DECIMAL(9,0) | Yes | false | NULL | NONE |
| p_comment | TEXT | Yes | false | NULL | NONE |
+---------------+--------------+------+-------+---------+-------+

orc format

orc 格式:和 parquet format 使用方法一致,将 format 参数设置为 orc

MySQL [(none)]> select * from s3(
"uri" = "http://127.0.0.1:9312/test2/test.snappy.orc",
"s3.access_key"= "minioadmin",
"s3.secret_key" = "minioadmin",
"format" = "orc",
"use_path_style"="true") limit 5;
+-----------+------------------------------------------+----------------+----------+-------------------------+--------+-------------+---------------+---------------------+
| p_partkey | p_name | p_mfgr | p_brand | p_type | p_size | p_container | p_retailprice | p_comment |
+-----------+------------------------------------------+----------------+----------+-------------------------+--------+-------------+---------------+---------------------+
| 1 | goldenrod lavender spring chocolate lace | Manufacturer#1 | Brand#13 | PROMO BURNISHED COPPER | 7 | JUMBO PKG | 901 | ly. slyly ironi |
| 2 | blush thistle blue yellow saddle | Manufacturer#1 | Brand#13 | LARGE BRUSHED BRASS | 1 | LG CASE | 902 | lar accounts amo |
| 3 | spring green yellow purple cornsilk | Manufacturer#4 | Brand#42 | STANDARD POLISHED BRASS | 21 | WRAP CASE | 903 | egular deposits hag |
| 4 | cornflower chocolate smoke green pink | Manufacturer#3 | Brand#34 | SMALL PLATED BRASS | 14 | MED DRUM | 904 | p furiously r |
| 5 | forest brown coral puff cream | Manufacturer#3 | Brand#32 | STANDARD POLISHED TIN | 15 | SM PKG | 905 | wake carefully |
+-----------+------------------------------------------+----------------+----------+-------------------------+--------+-------------+---------------+---------------------+

avro format

avro 格式:S3 TVF 支持从 avro 文件中解析出 Table Schema 的列名、列类型。举例:

select * from s3(
"uri" = "http://127.0.0.1:9312/test2/person.avro",
"ACCESS_KEY" = "ak",
"SECRET_KEY" = "sk",
"FORMAT" = "avro");
+--------+--------------+-------------+-----------------+
| name | boolean_type | double_type | long_type |
+--------+--------------+-------------+-----------------+
| Alyssa | 1 | 10.0012 | 100000000221133 |
| Ben | 0 | 5555.999 | 4009990000 |
| lisi | 0 | 5992225.999 | 9099933330 |
+--------+--------------+-------------+-----------------+

URI 包含通配符

URI 可以使用通配符来读取多个文件。注意:如果使用通配符要保证各个文件的格式是一致的 (尤其是 csv/csv_with_names/csv_with_names_and_types 算做不同的格式),S3 TVF 用第一个文件来解析出 Table Schema。 如下两个 CSV 文件:

// file1.csv
1,aaa,18
2,qqq,20
3,qwe,19

// file2.csv
5,cyx,19
6,ftw,21

可以在 URI 上使用通配符来导入。

MySQL [(none)]> select * from s3(
"uri" = "http://127.0.0.1:9312/test2/file*.csv",
"s3.access_key"= "minioadmin",
"s3.secret_key" = "minioadmin",
"format" = "csv",
"use_path_style"="true");
+------+------+------+
| c1 | c2 | c3 |
+------+------+------+
| 1 | aaa | 18 |
| 2 | qqq | 20 |
| 3 | qwe | 19 |
| 5 | cyx | 19 |
| 6 | ftw | 21 |
+------+------+------+

配合 insert intocast 使用 S3 TVF

// 创建 Doris 内部表
CREATE TABLE IF NOT EXISTS ${testTable}
(
id int,
name varchar(50),
age int
)
COMMENT "my first table"
DISTRIBUTED BY HASH(id) BUCKETS 32
PROPERTIES("replication_num" = "1");

// 使用 S3 插入数据
insert into ${testTable} (id,name,age)
select cast (id as INT) as id, name, cast (age as INT) as age
from s3(
"uri" = "${uri}",
"s3.access_key"= "${ak}",
"s3.secret_key" = "${sk}",
"format" = "${format}",
"strip_outer_array" = "true",
"read_json_by_line" = "true",
"use_path_style" = "true");