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Posted to commits@druid.apache.org by "317brian (via GitHub)" <gi...@apache.org> on 2026/05/04 19:53:51 UTC
[PR] docs: add caution re: schema auto discovery (druid)
317brian opened a new pull request, #19403:
URL: https://github.com/apache/druid/pull/19403
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Re: [PR] docs: add caution re: schema auto discovery (druid)
Posted by "317brian (via GitHub)" <gi...@apache.org>.
317brian merged PR #19403:
URL: https://github.com/apache/druid/pull/19403
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Re: [PR] docs: add caution re: schema auto discovery (druid)
Posted by "writer-jill (via GitHub)" <gi...@apache.org>.
writer-jill commented on code in PR #19403:
URL: https://github.com/apache/druid/pull/19403#discussion_r3228533793
##########
docs/ingestion/schema-design.md:
##########
@@ -249,12 +249,13 @@ Druid can infer the schema for your data in one of two ways:
#### Type-aware schema discovery
-:::info
- Note that using type-aware schema discovery can impact downstream BI tools depending on how they handle ARRAY typed columns.
-:::
-
You can have Druid infer the schema and types for your data partially or fully by setting `dimensionsSpec.useSchemaDiscovery` to `true` and defining some or no dimensions in the dimensions list.
+Before you use type-aware schema discovery, keep the following in mind:
+
+- There maybe impact on downstream BI tools depending on how they handle ARRAY-typed columns.
Review Comment:
```suggestion
- There may be an impact on downstream BI tools depending on how they handle ARRAY-typed columns.
```
##########
docs/ingestion/ingestion-spec.md:
##########
@@ -188,9 +188,13 @@ Treat `__time` as a millisecond timestamp: the number of milliseconds since Jan
The `dimensionsSpec` is located in `dataSchema` → `dimensionsSpec` and is responsible for
configuring [dimensions](./schema-model.md#dimensions).
-You can either manually specify the dimensions or take advantage of schema auto-discovery where you allow Druid to infer all or some of the schema for your data. This means that you don't have to explicitly specify your dimensions and their type.
+You can either manually specify the dimensions or take advantage of type-aware schema auto-discovery where you allow Druid to infer all or some of the schema for your data. This means that you don't have to explicitly specify your dimensions and their type.
-To use schema auto-discovery, set `useSchemaDiscovery` to `true`.
+:::caution
+When using type-aware schema auto-discovery, Druid discovers the type for all dimensions unless you explicitly specify dimensions for Druid to ignore by using the `dimensionExclusions` field. This helps you control storage costs by preventing Druid from ingesting dimensions unintentionally.
Review Comment:
```suggestion
When using type-aware schema auto-discovery, Druid discovers the type for all dimensions unless you use the `dimensionExclusions` field to explicitly specify dimensions to ignore. This helps you control storage costs by preventing Druid from unintentionally ingesting dimensions.
```
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Re: [PR] docs: add caution re: schema auto discovery (druid)
Posted by "techdocsmith (via GitHub)" <gi...@apache.org>.
techdocsmith commented on code in PR #19403:
URL: https://github.com/apache/druid/pull/19403#discussion_r3237642540
##########
docs/ingestion/schema-design.md:
##########
@@ -249,12 +249,13 @@ Druid can infer the schema for your data in one of two ways:
#### Type-aware schema discovery
-:::info
- Note that using type-aware schema discovery can impact downstream BI tools depending on how they handle ARRAY typed columns.
-:::
-
You can have Druid infer the schema and types for your data partially or fully by setting `dimensionsSpec.useSchemaDiscovery` to `true` and defining some or no dimensions in the dimensions list.
+Before you use type-aware schema discovery, keep the following in mind:
+
+- There may be an impact on downstream BI tools depending on how they handle ARRAY-typed columns.
+- Be aware of all the potential dimensions. Druid discovers all the dimensions unless you specify an exclusion list. Without the list, you may ingest more columns than you intend. For example, if you use type-aware schema discovery and the Kafka input format, you'll ingest optional dimensions like the Kafka offset and partition unless you add them to the exclusion list.
Review Comment:
```suggestion
- Be aware of all the potential dimensions. Druid discovers all available dimensions unless you specify an exclusion list. Without an exclusion list, you may ingest more columns than you intend. For example, if you use type-aware schema discovery and the Kafka input format, Druid discovers dimensions like the Kafka offset and partition unless you add them to the exclusion list.
```
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