mirror of
https://github.com/ClickHouse/ClickHouse.git
synced 2024-11-10 09:32:06 +00:00
revert some changes
This commit is contained in:
Anna
parent
c9cdde9983
commit
bb2061dd8f
@ -24,17 +24,17 @@ ENGINE = S3(path, [aws_access_key_id, aws_secret_access_key,] format, structure,
|
||||
**Example**
|
||||
|
||||
``` sql
|
||||
CREATE TABLE s3_engine_table (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/test-data.csv.gz', 'CSV', 'name String, value UInt32', 'gzip');
|
||||
INSERT INTO s3_engine_table VALUES ('one', 1), ('two', 2), ('three', 3);
|
||||
SELECT * FROM s3_engine_table LIMIT 2;
|
||||
CREATE TABLE s3_engine_table (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/test-data.csv.gz', 'CSV', 'name String, value UInt32', 'gzip');
|
||||
INSERT INTO s3_engine_table VALUES ('one', 1), ('two', 2), ('three', 3);
|
||||
SELECT * FROM s3_engine_table LIMIT 2;
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─name─┬─value─┐
|
||||
│ one │ 1 │
|
||||
│ two │ 2 │
|
||||
└──────┴───────┘
|
||||
┌─name─┬─value─┐
|
||||
│ one │ 1 │
|
||||
│ two │ 2 │
|
||||
└──────┴───────┘
|
||||
```
|
||||
## Virtual columns {#virtual-columns}
|
||||
|
||||
@ -85,7 +85,7 @@ The following settings can be specified in configuration file for given endpoint
|
||||
|
||||
**Example:**
|
||||
|
||||
```
|
||||
``` xml
|
||||
<s3>
|
||||
<endpoint-name>
|
||||
<endpoint>https://storage.yandexcloud.net/my-test-bucket-768/</endpoint>
|
||||
@ -112,22 +112,22 @@ Suppose we have several files in TSV format with the following URIs on HDFS:
|
||||
1. There are several ways to make a table consisting of all six files:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE table_with_range (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/some_file_{1..3}', 'CSV');
|
||||
CREATE TABLE table_with_range (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/some_file_{1..3}', 'CSV');
|
||||
```
|
||||
|
||||
2. Another way:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE table_with_question_mark (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/some_file_?', 'CSV');
|
||||
CREATE TABLE table_with_question_mark (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/some_file_?', 'CSV');
|
||||
```
|
||||
|
||||
3. Table consists of all the files in both directories (all files should satisfy format and schema described in query):
|
||||
|
||||
``` sql
|
||||
CREATE TABLE table_with_asterisk (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/*', 'CSV');
|
||||
CREATE TABLE table_with_asterisk (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/*', 'CSV');
|
||||
```
|
||||
|
||||
!!! warning "Warning"
|
||||
@ -136,8 +136,8 @@ Suppose we have several files in TSV format with the following URIs on HDFS:
|
||||
4. Create table with files named `file-000.csv`, `file-001.csv`, … , `file-999.csv`:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE big_table (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/big_prefix/file-{000..999}.csv', 'CSV');
|
||||
CREATE TABLE big_table (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/big_prefix/file-{000..999}.csv', 'CSV');
|
||||
```
|
||||
## See also
|
||||
|
||||
|
||||
@ -10,7 +10,7 @@ Provides table-like interface to select/insert files in [Amazon S3](https://aws.
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
s3(path, [aws_access_key_id, aws_secret_access_key,] format, structure, [compression])
|
||||
s3(path, [aws_access_key_id, aws_secret_access_key,] format, structure, [compression])
|
||||
```
|
||||
|
||||
**Arguments**
|
||||
@ -29,31 +29,31 @@ A table with the specified structure for reading or writing data in the specifie
|
||||
Table from S3 file `https://storage.yandexcloud.net/my-test-bucket-768/data.csv` and selection of the first two rows from it:
|
||||
|
||||
``` sql
|
||||
SELECT *
|
||||
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/data.csv', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32')
|
||||
LIMIT 2;
|
||||
SELECT *
|
||||
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/data.csv', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32')
|
||||
LIMIT 2;
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─column1─┬─column2─┬─column3─┐
|
||||
│ 1 │ 2 │ 3 │
|
||||
│ 3 │ 2 │ 1 │
|
||||
└─────────┴─────────┴─────────┘
|
||||
┌─column1─┬─column2─┬─column3─┐
|
||||
│ 1 │ 2 │ 3 │
|
||||
│ 3 │ 2 │ 1 │
|
||||
└─────────┴─────────┴─────────┘
|
||||
```
|
||||
|
||||
The similar but from file with `gzip` compression:
|
||||
|
||||
``` sql
|
||||
SELECT *
|
||||
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/data.csv.gz', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32', 'gzip')
|
||||
LIMIT 2;
|
||||
SELECT *
|
||||
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/data.csv.gz', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32', 'gzip')
|
||||
LIMIT 2;
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─column1─┬─column2─┬─column3─┐
|
||||
│ 1 │ 2 │ 3 │
|
||||
│ 3 │ 2 │ 1 │
|
||||
└─────────┴─────────┴─────────┘
|
||||
┌─column1─┬─column2─┬─column3─┐
|
||||
│ 1 │ 2 │ 3 │
|
||||
│ 3 │ 2 │ 1 │
|
||||
└─────────┴─────────┴─────────┘
|
||||
```
|
||||
|
||||
## Usage {#usage-examples}
|
||||
@ -72,27 +72,27 @@ Suppose that we have several files with following URIs on S3:
|
||||
1. Query the amount of rows in files end with number from 1 to 3:
|
||||
|
||||
``` sql
|
||||
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');
|
||||
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')
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─count()─┐
|
||||
│ 18 │
|
||||
└─────────┘
|
||||
┌─count()─┐
|
||||
│ 18 │
|
||||
└─────────┘
|
||||
```
|
||||
|
||||
2. Query the amount of rows in all files of these two directories:
|
||||
|
||||
``` sql
|
||||
SELECT count(*)
|
||||
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/*', 'CSV', 'name String, value UInt32');
|
||||
SELECT count(*)
|
||||
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/*', 'CSV', 'name String, value UInt32')
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─count()─┐
|
||||
│ 24 │
|
||||
└─────────┘
|
||||
┌─count()─┐
|
||||
│ 24 │
|
||||
└─────────┘
|
||||
```
|
||||
|
||||
!!! warning "Warning"
|
||||
@ -101,28 +101,28 @@ Suppose that we have several files with following URIs on S3:
|
||||
3. Query the data from files named `file-000.csv`, `file-001.csv`, … , `file-999.csv`:
|
||||
|
||||
``` sql
|
||||
SELECT count(*)
|
||||
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/big_prefix/file-{000..999}.csv', 'CSV', 'name String, value UInt32');
|
||||
SELECT count(*)
|
||||
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/big_prefix/file-{000..999}.csv', 'CSV', 'name String, value UInt32');
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─count()─┐
|
||||
│ 12 │
|
||||
└─────────┘
|
||||
┌─count()─┐
|
||||
│ 12 │
|
||||
└─────────┘
|
||||
```
|
||||
|
||||
4. Insert a data into file `test-data.csv.gz`:
|
||||
|
||||
``` sql
|
||||
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 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);
|
||||
```
|
||||
|
||||
5. Insert a data into file `test-data.csv.gz` from existing table:
|
||||
|
||||
``` sql
|
||||
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;
|
||||
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**
|
||||
|
||||
@ -24,17 +24,17 @@ ENGINE = S3(path, [aws_access_key_id, aws_secret_access_key,] format, structure,
|
||||
**Пример**
|
||||
|
||||
``` sql
|
||||
CREATE TABLE s3_engine_table (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/test-data.csv.gz', 'CSV', 'name String, value UInt32', 'gzip');
|
||||
INSERT INTO s3_engine_table VALUES ('one', 1), ('two', 2), ('three', 3);
|
||||
SELECT * FROM s3_engine_table LIMIT 2;
|
||||
CREATE TABLE s3_engine_table (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/test-data.csv.gz', 'CSV', 'name String, value UInt32', 'gzip');
|
||||
INSERT INTO s3_engine_table VALUES ('one', 1), ('two', 2), ('three', 3);
|
||||
SELECT * FROM s3_engine_table LIMIT 2;
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─name─┬─value─┐
|
||||
│ one │ 1 │
|
||||
│ two │ 2 │
|
||||
└──────┴───────┘
|
||||
┌─name─┬─value─┐
|
||||
│ one │ 1 │
|
||||
│ two │ 2 │
|
||||
└──────┴───────┘
|
||||
```
|
||||
## Виртуальные столбцы {#virtual-columns}
|
||||
|
||||
@ -88,7 +88,7 @@ ENGINE = S3(path, [aws_access_key_id, aws_secret_access_key,] format, structure,
|
||||
|
||||
**Пример**
|
||||
|
||||
```
|
||||
```xml
|
||||
<s3>
|
||||
<endpoint-name>
|
||||
<endpoint>https://storage.yandexcloud.net/my-test-bucket-768/</endpoint>
|
||||
@ -115,22 +115,22 @@ ENGINE = S3(path, [aws_access_key_id, aws_secret_access_key,] format, structure,
|
||||
1. Существует несколько способов создать таблицу, включающую в себя все шесть файлов:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE table_with_range (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/some_file_{1..3}', 'CSV');
|
||||
CREATE TABLE table_with_range (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/some_file_{1..3}', 'CSV');
|
||||
```
|
||||
|
||||
2. Другой способ:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE table_with_question_mark (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/some_file_?', 'CSV');
|
||||
CREATE TABLE table_with_question_mark (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/some_file_?', 'CSV');
|
||||
```
|
||||
|
||||
3. Таблица содержит все файлы в обоих директориях (все файлы должны соответствовать формату и схеме, описанным в запросе):
|
||||
|
||||
``` sql
|
||||
CREATE TABLE table_with_asterisk (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/*', 'CSV');
|
||||
CREATE TABLE table_with_asterisk (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/*', 'CSV');
|
||||
```
|
||||
|
||||
!!! warning "Warning"
|
||||
@ -139,8 +139,8 @@ ENGINE = S3(path, [aws_access_key_id, aws_secret_access_key,] format, structure,
|
||||
4. Создание таблицы из файлов с именами `file-000.csv`, `file-001.csv`, … , `file-999.csv`:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE big_table (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/big_prefix/file-{000..999}.csv', 'CSV');
|
||||
CREATE TABLE big_table (name String, value UInt32)
|
||||
ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/big_prefix/file-{000..999}.csv', 'CSV');
|
||||
```
|
||||
## Смотрите также
|
||||
|
||||
|
||||
@ -10,7 +10,7 @@ toc_title: s3
|
||||
**Синтаксис**
|
||||
|
||||
``` sql
|
||||
s3(path, [aws_access_key_id, aws_secret_access_key,] format, structure, [compression])
|
||||
s3(path, [aws_access_key_id, aws_secret_access_key,] format, structure, [compression])
|
||||
```
|
||||
|
||||
**Aргументы**
|
||||
@ -31,18 +31,18 @@ toc_title: s3
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
SELECT *
|
||||
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/data.csv', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32')
|
||||
LIMIT 2;
|
||||
SELECT *
|
||||
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/data.csv', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32')
|
||||
LIMIT 2;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─column1─┬─column2─┬─column3─┐
|
||||
│ 1 │ 2 │ 3 │
|
||||
│ 3 │ 2 │ 1 │
|
||||
└─────────┴─────────┴─────────┘
|
||||
┌─column1─┬─column2─┬─column3─┐
|
||||
│ 1 │ 2 │ 3 │
|
||||
│ 3 │ 2 │ 1 │
|
||||
└─────────┴─────────┴─────────┘
|
||||
```
|
||||
|
||||
То же самое, но файл со сжатием `gzip`:
|
||||
@ -50,18 +50,18 @@ Result:
|
||||
Запрос:
|
||||
|
||||
``` sql
|
||||
SELECT *
|
||||
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/data.csv.gz', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32', 'gzip')
|
||||
LIMIT 2;
|
||||
SELECT *
|
||||
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/data.csv.gz', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32', 'gzip')
|
||||
LIMIT 2;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
``` text
|
||||
┌─column1─┬─column2─┬─column3─┐
|
||||
│ 1 │ 2 │ 3 │
|
||||
│ 3 │ 2 │ 1 │
|
||||
└─────────┴─────────┴─────────┘
|
||||
┌─column1─┬─column2─┬─column3─┐
|
||||
│ 1 │ 2 │ 3 │
|
||||
│ 3 │ 2 │ 1 │
|
||||
└─────────┴─────────┴─────────┘
|
||||
```
|
||||
## Примеры использования {#usage-examples}
|
||||
|
||||
@ -79,27 +79,27 @@ Result:
|
||||
1. Запрос количества строк в файлах, заканчивающихся цифрами от 1 до 3:
|
||||
|
||||
``` sql
|
||||
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');
|
||||
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');
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─count()─┐
|
||||
│ 18 │
|
||||
└─────────┘
|
||||
┌─count()─┐
|
||||
│ 18 │
|
||||
└─────────┘
|
||||
```
|
||||
|
||||
2. Запрос количества строк во всех файлах этих двух каталогов:
|
||||
|
||||
``` sql
|
||||
SELECT count(*)
|
||||
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/*', 'CSV', 'name String, value UInt32');
|
||||
SELECT count(*)
|
||||
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/*', 'CSV', 'name String, value UInt32');
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─count()─┐
|
||||
│ 24 │
|
||||
└─────────┘
|
||||
┌─count()─┐
|
||||
│ 24 │
|
||||
└─────────┘
|
||||
```
|
||||
|
||||
!!! warning "Warning"
|
||||
@ -108,28 +108,28 @@ Result:
|
||||
3. Запрос данных из файлов с именами `file-000.csv`, `file-001.csv`, … , `file-999.csv`:
|
||||
|
||||
``` sql
|
||||
SELECT count(*)
|
||||
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/big_prefix/file-{000..999}.csv', 'CSV', 'name String, value UInt32');
|
||||
SELECT count(*)
|
||||
FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/big_prefix/file-{000..999}.csv', 'CSV', 'name String, value UInt32');
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─count()─┐
|
||||
│ 12 │
|
||||
└─────────┘
|
||||
┌─count()─┐
|
||||
│ 12 │
|
||||
└─────────┘
|
||||
```
|
||||
|
||||
4. Вставка данных в файл `test-data.csv.gz`:
|
||||
|
||||
``` sql
|
||||
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 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);
|
||||
```
|
||||
|
||||
5. Вставка данных в файл `test-data.csv.gz` из существующей таблицы:
|
||||
|
||||
``` sql
|
||||
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;
|
||||
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;
|
||||
```
|
||||
|
||||
## Смотрите также
|
||||
|
||||
Loading…
Reference in New Issue
Block a user