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We are ingesting data into Snowflake via the kafka connector. To increase the data read performance / scan less partitions we decided to add a clustering key to a a key / combination of keys stored in the RECORD_CONTENT variant field.

The data in the RECORD_CONTENT field looks like this:

{
  "jsonSrc": {
    "Integerfield": 1,
    "SourceDateTime": "2020-06-30 05:33:08:345",
    *REST_OF_THE_KEY_VALUE_PAIRS*
}

Now, the issue is that clustering on a datetime col like SourceDateTime does NOT work:

CLUSTER BY (to_date(RECORD_CONTENT:jsonSrc:loadDts::datetime))

...while clustering on a field like Integerfield DOES work:

CLUSTER BY (RECORD_CONTENT:jsonSrc:Integerfield::int )

Not working means: when using a filter on RECORD_CONTENT:jsonSrc:loadDts::datetime, it has no effect on the partitions scanned, while filtering on RECORD_CONTENT:jsonSrc:Integerfield::int does perform partition pruning.

What is wrong here? Is this a bug?

Note that:

  • There is enough data to do meaningful clustering on RECORD_CONTENT:jsonSrc:loadDts::datetime
  • I validated clustering on RECORD_CONTENT:jsonSrc:loadDts::datetime working by making a copy of the raw table, with RECORD_CONTENT:jsonSrc:loadDts::datetime in a seperate column loadDtsCol and then adding a similar clustering key on that column: to_date(loadDtsCol).
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1 回答 1

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为了更好地修剪和减少存储消耗，如果您的半结构化数据包括：日期和时间戳，尤其是非 ISO 8601 日期和时间戳，我们建议将您的对象和关键数据扁平化到单独的关系列中，作为字符串值

字符串中的数字

数组

日期和时间戳等非本机值在加载到 VARIANT 列时存储为字符串，因此与存储在具有相应数据类型的关系列中相比，对这些值的操作可能会更慢并且消耗更多空间。

请参阅此链接： https ://docs.snowflake.com/en/user-guide/semistructured-considerations.html#storing-semi-structured-data-in-a-variant-column-vs-flattening-the-nested-结构体

于 2020-07-01T14:11:18.490 回答