BigQuery

数据库

分析 PB 级数据、管理成本并运行 BigQuery 作业--Neotask 将 Neotask 带入 Google 的数据仓库。

通过简单英语描述数据问题来编写和执行 BigQuery SQL 进行分析和报告
在运行前估算并控制查询成本，并随时间分析槽位和字节消耗趋势
通过自然语言命令管理数据集、表、定时查询和 IAM 权限

你能做什么

无需编写 SQL 即可运行分析查询

询问 Neotask 您想要回答的业务问题 - “本月我们每天有多少日活跃用户（按平台细分）？” - 它会编写优化的 BigQuery SQL，预览扫描的估计字节数，并在您批准的情况下运行查询。

查询前估算和控制成本

BigQuery 按处理的字节数收费。 Neotask 在执行任何查询之前运行一次试运行，并告诉您以字节和美元为单位的估计成本。您可以决定是否继续、优化查询或使用分区筛选器来减少扫描大小。

管理表和数据集

创建分区和集群表、向现有架构添加列、复制或导出表以及管理数据集级访问控制--所有这些都通过对话进行。 Neotask 生成正确的 DDL 和 bq CLI 命令。

分析时段和预订使用情况

要求按项目、预留或工作类型细分槽位利用率。识别插槽争用窗口，查看哪些作业消耗最多的资源，并决定是否调整按需与保留插槽分配。

监控预定的查询和传输

检查计划查询的状态，查看是否有失败及其原因，并查看数据传输运行历史记录。要求 Neotask 重新运行失败的传输或更新计划查询的时间，而无需打开 BigQuery 控制台。

尝试询问

“上个月每个产品类别产生了多少收入？”
“这个查询会扫描多少字节以及它的成本是多少？” （粘贴查询）
“在分析数据集中为日常用户事件创建分区表”
“过去 24 小时内哪些计划查询失败了？错误是什么？”
“按计费字节数显示本周运行成本最高的 10 个作业”
“将 user_id 上的集群添加到事件表中”
“授予数据分析师组对报告数据集的读取权限”
“将第 4 季度销售表作为 Parquet 文件导出到 GCS”

专业提示

在运行大型查询之前，请务必要求进行试运行估算 - Neotask 将自动包含成本估算，并在扫描超出阈值时要求确认。
在提示中使用分区过滤器：“仅适用于 2026 年 1 月的日期” - Neotask 将在分区列上添加正确的 WHERE 子句以避免全表扫描。
按 WHERE 和 JOIN 条件中最常用的字段对表进行聚类 - 在决定聚类键顺序之前，请 Neotask 检查您的查询模式。
对于重复查询，请要求 Neotask 创建计划查询或物化视图，而不是每次都运行临时查询。
使用 INFORMATION_SCHEMA 视图获取元数据：Neotask 可以查询 JOBS_BY_PROJECT、TABLE_STORAGE 和 PARTITIONS 视图，无需手动控制台导航即可为您提供深入洞察。

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