JulianJaffePinterest opened a new issue #9707: Add IS_MULTIVALUE and COMPLEX_TYPE columns to INFORMATION_SCHEMA.COLUMNS URL: https://github.com/apache/druid/issues/9707 ### Description Currently, the `INFORMATION_SCHEMA.COLUMNS` table in Druid does not have full information about the columns in a data source, specifically whether or not a column can contain multi-valued entries and detailed information about which complex serde a metric uses. This means that users attempting to interact with Druid metadata must either fall back to (potentially expensive) SegmentMetadataQueries to determine this information or implement complicated handling logic. ### Motivation It is currently difficult to obtain complete metadata about a Druid datasource. The only way to determine whether or not a column can contain multiple values or what complex serde was used to encode a metric is to use SegmentMetadataQueries. These queries can be expensive (if aggregating over a large number of segments) and can miss information if not all segments are queried (e.g. columns that don't appear in a given segment won't be returned by a SegmentMetadataQuery, and columns that don't have multiple values _in a queried segment_ will return `..."hasMultipleValues" : false,...`). This can be worked around to some degree via merging results, but this reintroduces the problem that SegmentMetadataQueries can be expensive when run over many segments. If the `INFORMATION_SCHEMA.COLUMNS` table were to be extended to include information about whether a column could contain multiple values and what serde was used for a complex metric, tools that interact with Druid metadata such as the [Calcite Druid adapter](https://calcite.apache.org/docs/druid_adapter.html), proposed Spark and Hive readers, and other third party integrations could issue simple SQL-based queries to determine data source metadata instead of needing to rely on SegmentMetadataQueries. This would also align with the Druid recommendation to use the `INFORMATION_SCHEMA` tables for metadata if you're using SQL.
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