Apache Iceberg™ 表的元数据与保留¶

创建¶

Snowflake 定期为 Apache Iceberg 规范第 2 版生成元数据，并将元数据写入外部卷的文件。每个新的元数据文件都包含自上次创建 Snowflake 生成的元数据文件以来所有的 DML 或者 DDL 变更。

您还可以使用 SYSTEM$GET_ICEBERG_TABLE_INFORMATION 函数按需创建元数据。有关说明，请参阅 生成 DML 变更的快照。

有关查找元数据文件的信息，请参阅 数据和元数据目录。

查看元数据创建历史记录¶

要访问元数据生成尝试的完整历史记录，请查看账户的查询历史记录并过滤结果。在 SQL 文本中搜索 SYSTEM$GET_ICEBERG_TABLE_INFORMATION 函数名称。

Snowflake 内部使用相同的 SYSTEM$GET_ICEBERG_TABLE_INFORMATION 函数生成表元数据。在查询历史记录中，Snowflake 所做的尝试出现在名为 SYSTEM 的用户名下。查询历史记录中的 STATUS 列指示元数据是否成功生成。

有关查看选项，请参阅 使用 Query History 监控查询活动。

删除¶

当发生以下事件时，Snowflake 会从您的外部云存储中删除 Iceberg 元数据：

• 删除表之后。

• Iceberg 元数据引用已过期的快照或表数据。

数据保留期到期后并不会立即删除。因此，元数据存储可能会导致您的云存储提供商产生比数据表生命周期更长的费用。

基于 Delta 的表¶

对于从 Delta 表文件创建的 Iceberg 表，如果您为外部卷配置写入权限，Snowflake 会自动将 Iceberg 元数据写入外部存储（请参阅 ALLOW_WRITES）。有关写入位置的更多信息，请参阅 数据和元数据目录。

为防止 Snowflake 写入 Iceberg 元数据，只要没有 Snowflake 管理的 Iceberg 表使用相同的外部卷，您就可以在外部卷上将 ALLOW_WRITES 参数设置为 FALSE。

Partitioning support matrix¶

The following table shows which features and actions are supported for each type of partitioned Iceberg table, and indicates compliance with version 2 of the Apache Iceberg specification.

Partitioning considerations¶

Consider the following before you use partitioned writes for Iceberg tables:

• If you use an external engine to add, drop, or replace a partition field in an externally managed table, Snowflake writes data according to the latest partition specification.

• The GET_DDL function doesn't include the PARTITION BY clause in its output.

• The sum of the sizes of the outputs for all partition transforms can't exceed 1024 bytes for a single row.

• Because partition evolution isn't supported for Snowflake-managed tables, you must drop the table and create a new one with partitioning.

• The DAY(), MONTH(), YEAR() partition transform parameters, which you specify within the PARTITION BY clause under table properties, are part of the Iceberg specification. For multiple days, months, or years, the partition expression parameter returns a partition for each calendar day, month, or year. For example, when the DAY() transform is used on a timestamp column that has 2 months of data, 61 partitions are created.

  In contrast, the DAY(), MONTH(), YEAR() functions in Snowflake are part of the SQL standard. For multiple days, months, or years, these functions extract the corresponding day, month, or year part from a date or timestamp. For example, when the DAY() function is used on a timestamp column that has multiple months of data, this function returns a day of the month ranging from 1 to 31.