4.7 KiB
toc_priority | toc_title |
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45 | s3 |
S3 Table Function
Provides table-like interface to select/insert files in Amazon S3. This table function is similar to hdfs, but provides S3-specific features.
Syntax
s3(path, [aws_access_key_id, aws_secret_access_key,] format, structure, [compression])
Arguments
path
— Bucket url with path to file. Supports following wildcards in readonly mode:*
,?
,{abc,def}
and{N..M}
whereN
,M
— numbers,'abc'
,'def'
— strings. For more information see here.format
— The format of the file.structure
— Structure of the table. Format'column1_name column1_type, column2_name column2_type, ...'
.compression
— Parameter is optional. Supported values:none
,gzip/gz
,brotli/br
,xz/LZMA
,zstd/zst
. By default, it will autodetect compression by file extension.
Returned value
A table with the specified structure for reading or writing data in the specified file.
Examples
Selecting the first two rows from the table from S3 file https://storage.yandexcloud.net/my-test-bucket-768/data.csv
:
SELECT *
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/data.csv', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32')
LIMIT 2;
┌─column1─┬─column2─┬─column3─┐
│ 1 │ 2 │ 3 │
│ 3 │ 2 │ 1 │
└─────────┴─────────┴─────────┘
The similar but from file with gzip
compression:
SELECT *
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/data.csv.gz', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32', 'gzip')
LIMIT 2;
┌─column1─┬─column2─┬─column3─┐
│ 1 │ 2 │ 3 │
│ 3 │ 2 │ 1 │
└─────────┴─────────┴─────────┘
Usage
Suppose that we have several files with following URIs on S3:
- 'https://storage.yandexcloud.net/my-test-bucket-768/some_prefix/some_file_1.csv'
- 'https://storage.yandexcloud.net/my-test-bucket-768/some_prefix/some_file_2.csv'
- 'https://storage.yandexcloud.net/my-test-bucket-768/some_prefix/some_file_3.csv'
- 'https://storage.yandexcloud.net/my-test-bucket-768/some_prefix/some_file_4.csv'
- 'https://storage.yandexcloud.net/my-test-bucket-768/another_prefix/some_file_1.csv'
- 'https://storage.yandexcloud.net/my-test-bucket-768/another_prefix/some_file_2.csv'
- 'https://storage.yandexcloud.net/my-test-bucket-768/another_prefix/some_file_3.csv'
- 'https://storage.yandexcloud.net/my-test-bucket-768/another_prefix/some_file_4.csv'
Count the amount of rows in files ending with numbers from 1 to 3:
SELECT count(*)
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/some_file_{1..3}.csv', 'CSV', 'name String, value UInt32')
┌─count()─┐
│ 18 │
└─────────┘
Count the total amount of rows in all files in these two directories:
SELECT count(*)
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/*', 'CSV', 'name String, value UInt32')
┌─count()─┐
│ 24 │
└─────────┘
!!! warning "Warning"
If your listing of files contains number ranges with leading zeros, use the construction with braces for each digit separately or use ?
.
Count the total amount of rows in files named file-000.csv
, file-001.csv
, … , file-999.csv
:
SELECT count(*)
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/big_prefix/file-{000..999}.csv', 'CSV', 'name String, value UInt32');
┌─count()─┐
│ 12 │
└─────────┘
Insert data into file test-data.csv.gz
:
INSERT INTO s3('https://storage.yandexcloud.net/my-test-bucket-768/test-data.csv.gz', 'CSV', 'name String, value UInt32', 'gzip')
VALUES ('test-data', 1), ('test-data-2', 2);
Insert data into file test-data.csv.gz
from existing table:
INSERT INTO s3('https://storage.yandexcloud.net/my-test-bucket-768/test-data.csv.gz', 'CSV', 'name String, value UInt32', 'gzip')
SELECT name, value FROM existing_table;
See Also