# Q

For google cloud platform big query

Best Practice always set a project wide query usage limit

One of the great things about big query is you pay for what you eat and in general thats a good thing. But big query also has a major down side badly written queries or programs that automate running queries can run up surprisingly large bills. big query by default has no upper quota. Navigate to IAM→Quuotas and filter by service "Big Query API" to see if it is set or not.


# ChatGPT 

Here’s your text cleaned up and clarified into a more concise, best-practice note:

---

## **Best Practice: Set a Project-Wide Query Usage Limit in BigQuery**
  

One of the advantages of **Google Cloud BigQuery** is its pay-as-you-go model — you pay only for the data you process. However, this also comes with a risk:

- **Badly written queries** or
    
- **Automated scripts** that repeatedly run queries
    

  

…can unexpectedly generate **very large bills**.

  

By default, **BigQuery has no upper quota** on query usage.

To protect your budget, you should set a **project-wide query usage limit**.

  

**How to check and set limits:**

1. In the Google Cloud Console, navigate to:
    
    **IAM & Admin → Quotas**
    
2. Filter by service:
    
    "BigQuery API"
    
3. Review and set limits for:
    
    - **Query usage (bytes processed per day)**
        
    - **Concurrent queries**
        
    
4. Adjust these limits to a safe threshold for your project.
    

---

If you want, I can also give you a **step-by-step CLI version** of setting these BigQuery quotas using gcloud so you can automate it. That would make it easier to apply limits across multiple projects.


# Dia 
Setting a project-wide query usage limit in BigQuery helps prevent unexpected high costs.

  

Here’s why and how to do it:

  

**Why Set a Project-Wide Query Usage Limit?**

- **Cost Control:** BigQuery charges based on the amount of data processed. A single poorly written query or an automated script can accidentally process terabytes of data, leading to unexpectedly high bills.
- **No Default Cap:** By default, Google Cloud Platform (GCP) does not set an upper quota for BigQuery usage, so there’s nothing to stop runaway costs unless you configure it.
- **Best Practice:** Setting a usage limit is a recommended best practice for all GCP projects using BigQuery, especially in shared or production environments.

  

**How to Set a Project-Wide Query Usage Limit**

1. **Go to the GCP Console:**  
    Visit the [Google Cloud Console](https://console.cloud.google.com/).
2. **Navigate to IAM & Admin → Quotas**:

- In the left sidebar, go to **IAM & Admin** > **Quotas**.

4. **Filter by Service:**

- In the filter bar, type **BigQuery API** to see all quotas related to BigQuery.

6. **Find Query Usage Quotas:**

- Look for quotas like “Query usage per day” or “Query usage per user per day.”

8. **Edit Quotas:**

- Select the quota you want to change and click **Edit Quotas**.
- Submit a request to lower the quota to your desired daily or monthly limit.

10. **Monitor Regularly:**

- Regularly review your quotas and usage to ensure they’re still appropriate for your needs.

  

**Additional Tips**

- **Set Alerts:** Use GCP’s billing alerts to notify you if spending approaches your budget.
- **Educate Your Team:** Make sure everyone understands the cost implications of running large queries.
- **Review Query Plans:** Use the BigQuery Query Validator to estimate costs before running queries.

  

By setting a project-wide query usage limit, you can avoid surprise bills and keep your BigQuery costs predictable and under control.


# Grok 
Yes, setting a project-wide query usage limit in Google Cloud Platform\\'s BigQuery is indeed a recommended best practice to mitigate the risk of unexpected high costs from inefficient or automated queries. BigQuery operates on a pay-as-you-go model based on bytes processed (often referred to as "pay for what you eat"), which is efficient for controlled usage but can lead to large bills if queries scan excessive data without oversight. By default, there is no upper quota on query bytes billed, allowing unlimited processing until you hit broader account or service limits, which emphasizes the need for custom controls.

To implement this:
- **Set custom quotas**: You can define limits like "Query usage per day" (in TiB) at the project level to cap aggregate usage across all users, or per-user limits for more granular control. These apply to on-demand pricing and reset daily at midnight Pacific Time. Exceeding the limit triggers a `usageQuotaExceeded` error, blocking further queries.
- **Navigation to check/set quotas**:
  1. Go to the Google Cloud console.
  2. Navigate to **IAM & Admin > Quotas & System Limits**.
  3. Filter by service: "BigQuery API" (note: it\'s "BigQuery API," not "Big Query API").
  4. Look for quotas like "Query usage per day." If it shows "Unlimited," no custom limit is set.
  5. To edit, select the quota, click **Edit**, deselect "Unlimited," enter your desired limit, and submit. You\'ll need the Quota Administrator role (or equivalent permissions) for this.
- **Why it\'s essential**: Poorly optimized queries (e.g., full table scans) or automated scripts can process terabytes unwittingly. Custom quotas act as a safety net, preventing bill shocks while encouraging query optimization.

For more details on setup and considerations, refer to the official documentation.

# 综合专家建议：设置 BigQuery 项目级查询用量限制

为 Google Cloud BigQuery 设置项目级的查询用量限制是一项至关重要的成本控制最佳实践。下面综合了核心要点、操作步骤和补充建议。

### 1. 为什么必须设置用量限制？

BigQuery 的“按使用付费”模型虽然灵活，但也隐藏着风险。由于默认没有设置任何费用上限，以下情况可能导致成本失控：

- **编写不佳的查询**: 例如，未使用 `WHERE` 子句的 `SELECT *` 会扫描整个表，产生巨额费用。
- **自动化的查询脚本**: 如果脚本中存在逻辑错误，可能会在短时间内触发大量查询。

设置配额相当于为您的项目预算建立一个“熔断机制”，防止意外的超支。

### 2. 如何检查与设置配额

您可以通过 GCP Console 或 `gcloud` 命令行工具进行设置。

#### **通过 GCP Console (UI)**

这是一个检查和设置配额的流程图：

```mermaid
graph TD
    A[登录 GCP Console] --> B{导航到 "IAM & Admin"};
    B --> C[选择 "Quotas"];
    C --> D{筛选服务};
    D -- "输入 'BigQuery API'" --> E[找到相关配额];
    E -- "例如: Query usage per day" --> F[点击 "EDIT QUOTAS"];
    F --> G[设置新的限制值];
    G --> H[提交请求];
    H --> I[完成];
```

**步骤分解:** 

1.  **导航**: 在 Google Cloud Console 中，前往 **IAM & Admin → Quotas**。
2.  **过滤**: 在“Filter”框中，选择“Service”并输入 `BigQuery API`。
3.  **选择配额**: 找到您想限制的配额。最重要的两个是：
    *   `Query usage per day`: 限制整个项目每天处理的总数据量（按需查询）。
    *   `Query usage per user per day`: 限制单个用户每天处理的数据量。
4.  **编辑**: 选中要修改的配额，点击 **EDIT QUOTAS**，输入您的上限值（例如 10 TiB），然后提交。

#### **通过 gcloud (CLI)**

对于自动化和跨项目管理，使用 `gcloud` 更为高效。

```bash
# 1. 查看当前的配额 (以 'query-usage-per-day' 为例)
# 将 YOUR_PROJECT_ID 替换为您的项目ID
gcloud alpha services quota list \
    --service=bigquery.googleapis.com \
    --consumer=projects/YOUR_PROJECT_ID \
    --filter="metric=bigquery.googleapis.com/quota/query/usage"

# 2. 更新配额 (需要 Quota Administrator 角色)
# 假设您想将每日用量限制设置为 1 TiB (1099511627776 字节)
# 注意：这里的 value 需要以字符串形式提供
gcloud alpha services quota update \
    --service=bigquery.googleapis.com \
    --consumer=projects/YOUR_PROJECT_ID \
    --metric="bigquery.googleapis.com/quota/query/usage" \
    --limit="per-day-per-project" \
    --value="1099511627776"
```

### 3. 关键配额推荐

| 配额名称 (Quota Name) | 描述 | 建议 | 
| :--- | :--- | :--- |
| **Query usage per day** | **项目级**每日查询处理的总字节数。这是最重要的成本控制配额。 | 根据您的项目预算和正常用量设置一个合理的上限，例如 `1 TiB` 或 `10 TiB`。 |
| **Query usage per user per day** | **用户级**每日查询处理的字节数。 | 用于更精细的控制，防止单个用户滥用。可以设置为比项目级更低的值。 |
| **Concurrent rate limit** | 项目中可以同时运行的按需查询的数量。 | 默认值为 100。通常不需要修改，除非有特定的高并发需求。 |

### 4. 补充的最佳实践

- **设置结算提醒 (Billing Alerts)**: 在 Cloud Billing 中设置预算提醒，当费用接近或超过阈值时，您会收到邮件通知。这是独立于配额的另一层保障。
- **使用查询前预估成本**: 在 BigQuery UI 中，运行查询前，查询验证器会显示将要处理的数据量。养成检查预估成本的习惯。
- **为团队提供培训**: 确保所有使用 BigQuery 的团队成员都了解成本模型和如何编写高效的查询。
- **使用分区和聚簇表 (Partitioning and Clustering)**: 对于大型表，使用分区和聚簇可以显著减少查询时扫描的数据量，从而降低成本。
