///

## Mehrere Worker { #multiple-workers }

Sie können mehrere Worker mit der `--workers`-Befehlszeilenoption starten:

//// tab | `fastapi`

Wenn Sie den `fastapi`-Befehl verwenden:

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:solid">main.py</u>

比较特别的是，在 **Kubernetes** 环境中运行时，您通常**不需要**使用多个工作进程，而是**每个容器运行一个 Uvicorn 进程**。不过，我会在本章节的后续部分详细介绍这一点。

///

## 多个工作进程

您可以使用 `--workers` 命令行选项来启动多个工作进程：

//// tab | `fastapi`

如果您使用 `fastapi` 命令：

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:solid">main.py</u>

In particular, when running on **Kubernetes** you will probably **not** want to use workers and instead run **a single Uvicorn process per container**, but I'll tell you about it later in that chapter.

///

## Multiple Workers { #multiple-workers }

You can start multiple workers with the `--workers` command line option:

//// tab | `fastapi`

If you use the `fastapi` command:

<div class="termy">

///

## Несколько воркеров { #multiple-workers }

Можно запустить несколько воркеров с помощью опции командной строки `--workers`:

//// tab | `fastapi`

Если вы используете команду `fastapi`:

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:solid">main.py</u>

Gunicornを以下のように起動させることができます:

<div class="termy">

```console
$ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80

[19499] [INFO] Starting gunicorn 20.1.0
[19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
[19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
[19511] [INFO] Booting worker with pid: 19511
[19513] [INFO] Booting worker with pid: 19513

## 구니콘을 유비콘 워커와 함께 실행하기

설치 후 구니콘 실행하기:

<div class="termy">

```console
$ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80

[19499] [INFO] Starting gunicorn 20.1.0
[19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
[19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
[19511] [INFO] Booting worker with pid: 19511
[19513] [INFO] Booting worker with pid: 19513

///

## Vários trabalhadores { #multiple-workers }

Você pode iniciar vários trabalhadores com a opção de linha de comando `--workers`:

//// tab | `fastapi`

Se você usar o comando `fastapi`:

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:solid">main.py</u>

				},
			},
			"SELECT * FROM `users` ORDER BY `users`.`id` DESC,`name`", nil,
		},
		{
			[]clause.Interface{
				clause.Select{}, clause.From{}, clause.OrderBy{
					Columns: []clause.OrderByColumn{{Column: clause.PrimaryColumn, Desc: true}},
				}, clause.OrderBy{
					Columns: []clause.OrderByColumn{{Column: clause.Column{Name: "name"}, Reorder: true}},
				},
			},
			"SELECT * FROM `users` ORDER BY `name`", nil,
		},
		{

        `"LOCAL"` (case insensitive). If `"AUTO"`, tf.data service runtime
        decides which workers to read from. If `"ANY"`, TF workers read from any
        tf.data service workers. If `"LOCAL"`, TF workers will only read from
        local in-processs tf.data service workers. `"AUTO"` works well for most
        cases, while users can specify other targets. For example, `"LOCAL"`

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