[pull] master from cube-js:master

docs-mintlify/admin/account-billing/distribution.mdx

@@ -124,4 +124,4 @@ open http://localhost:3000
 [ref-infrastructure]: /admin/deployment/infrastructure
 [ref-workspace]: /admin/workspace
 [ref-deployment]: /admin/deployment
-[ref-update-channels]: /admin/deployment/deployments#update-channels
+[ref-update-channels]: /admin/deployment/index#update-channels

docs-mintlify/admin/connect-to-data/data-sources/ksqldb.mdx

@@ -349,6 +349,19 @@ cubes:
               - CUBE.user_id
               - CUBE.status
         stream_offset: latest
+        output_column_types:
+          - member: CUBE.order_id
+            type: text
+          - member: CUBE.user_id
+            type: text
+          - member: CUBE.status
+            type: text
+          - member: CUBE.count
+            type: int
+          - member: CUBE.total_amount
+            type: decimal
+          - member: CUBE.failed_count
+            type: int
 ```
 
 ```javascript title="JavaScript"
@@ -514,6 +527,14 @@ cube("order_events_stream", {
         },
       },
       stream_offset: `latest`,
+      output_column_types: [
+        { member: CUBE.order_id, type: `text` },
+        { member: CUBE.user_id, type: `text` },
+        { member: CUBE.status, type: `text` },
+        { member: CUBE.count, type: `int` },
+        { member: CUBE.total_amount, type: `decimal` },
+        { member: CUBE.failed_count, type: `int` },
+      ],
     },
   },
 });
@@ -533,6 +554,9 @@ Key properties for the streaming pre-aggregation:
   from the last processed offset regardless of this setting.
 - `unique_key_columns` — columns that uniquely identify a record, used
   for deduplication (see [below](#unique-key-columns-and-deduplication)).
+- `output_column_types` — declares the output column types for the Cube
+  Store table, required for Kafka streams mode (see
+  [below](#output-column-types)).
 
 #### Primary key and ungrouped queries
 
@@ -557,6 +581,35 @@ or table. Cube discovers its schema automatically. With Kafka streams
 mode enabled, the streaming pre-aggregation reads the backing Kafka topic
 directly — no objects are created in ksqlDB.
 
+#### Topic name matching {#topic-name-matching}
+
+In Kafka streams mode, Cube Store parses the `select_statement`
+(generated from the cube's `sql` property) and matches the `FROM` table
+name against the actual Kafka topic name. On managed platforms like
+Confluent Cloud, the Kafka topic name often differs from the ksqlDB
+stream or table name — for example, a ksqlDB stream called
+`ORDER_EVENTS_STREAM` might be backed by a Kafka topic named
+`pksqlc-abc123ORDER_EVENTS_STREAM`.
+
+The cube's `sql` property must reference the **ksqlDB stream or table
+name** (not the Kafka topic), because Cube uses ksqlDB `DESCRIBE` to
+discover the schema and resolve the backing topic. However, Cube does
+not currently rewrite the `FROM` clause in the generated
+`select_statement` to use the resolved Kafka topic name. If the ksqlDB
+object name differs from the Kafka topic name, Cube Store will fail
+with:
+
+> Topic table ORDER_EVENTS_STREAM is not found
+
+<Warning>
+
+This is a known limitation of Kafka streams mode. It does not occur
+when the ksqlDB object name and the Kafka topic name are the same,
+which is the default behavior when ksqlDB creates a stream or table
+with the default topic naming strategy.
+
+</Warning>
+
 ### Unique key columns and deduplication
 
 When `unique_key_columns` is set, Cube Store appends an internal
@@ -579,6 +632,135 @@ falls back to the Kafka message key: for a single unique key column, the
 raw key value is used; for composite keys, the key is expected to be a
 JSON object with matching field names.
 
+### Output column types
+
+In Kafka streams mode, Cube Store creates its internal pre-aggregation
+table based on column type information. By default, column types are
+inferred from the source ksqlDB stream using `DESCRIBE`. However, the
+pre-aggregation's `select_statement` (generated from the rollup
+definition) renames and transforms columns — for example, a source
+column `CREATED_AT` becomes `order_events_stream__created_at_second` in
+the output.
+
+When this renaming happens, the raw source column types no longer match
+the output column names, causing errors like:
+
+> Key column `order_events_stream__id` not found among column definitions
+
+To fix this, define `output_column_types` on the streaming
+pre-aggregation. This tells Cube the exact output column types to use
+for the Cube Store table, and separately passes the source schema so
+Cube Store can deserialize the raw Kafka messages correctly.
+
+<CodeGroup>
+
+```yaml title="YAML"
+pre_aggregations:
+  - name: stream
+    type: rollup
+    read_only: true
+    measures:
+      - CUBE.count
+      - CUBE.total_amount
+      - CUBE.failed_count
+    dimensions:
+      - CUBE.order_id
+      - CUBE.user_id
+      - CUBE.status
+    unique_key_columns:
+      - order_id
+    time_dimension: CUBE.created_at
+    granularity: second
+    partition_granularity: day
+    build_range_start:
+      sql: "SELECT date_trunc('day', DATE_SUB(NOW(), INTERVAL '5 hour'))"
+    build_range_end:
+      sql: "SELECT DATE_ADD(NOW(), INTERVAL '15 minute')"
+    refresh_key:
+      every: 1 minute
+      update_window: 1 hour
+      incremental: true
+    stream_offset: latest
+    output_column_types:
+      - member: CUBE.order_id
+        type: text
+      - member: CUBE.user_id
+        type: text
+      - member: CUBE.status
+        type: text
+      - member: CUBE.count
+        type: int
+      - member: CUBE.total_amount
+        type: decimal
+      - member: CUBE.failed_count
+        type: int
+```
+
+```javascript title="JavaScript"
+pre_aggregations: {
+  stream: {
+    type: `rollup`,
+    read_only: true,
+    measures: [CUBE.count, CUBE.total_amount, CUBE.failed_count],
+    dimensions: [CUBE.order_id, CUBE.user_id, CUBE.status],
+    unique_key_columns: [`order_id`],
+    time_dimension: CUBE.created_at,
+    granularity: `second`,
+    partition_granularity: `day`,
+    build_range_start: {
+      sql: `SELECT date_trunc('day', DATE_SUB(NOW(), INTERVAL '5 hour'))`,
+    },
+    build_range_end: {
+      sql: `SELECT DATE_ADD(NOW(), INTERVAL '15 minute')`,
+    },
+    refresh_key: {
+      every: `1 minute`,
+      update_window: `1 hour`,
+      incremental: true,
+    },
+    stream_offset: `latest`,
+    output_column_types: [
+      { member: CUBE.order_id, type: `text` },
+      { member: CUBE.user_id, type: `text` },
+      { member: CUBE.status, type: `text` },
+      { member: CUBE.count, type: `int` },
+      { member: CUBE.total_amount, type: `decimal` },
+      { member: CUBE.failed_count, type: `int` },
+    ],
+  },
+},
+```
+
+</CodeGroup>
+
+Each entry in `output_column_types` has two properties:
+
+- `member` — a reference to a dimension or measure included in the
+  pre-aggregation.
+- `type` — the Cube Store column type. Common values: `text`, `int`,
+  `bigint`, `decimal`, `float`, `boolean`, `timestamp`.
+
+The time dimension used in `time_dimension` does not need an entry in
+`output_column_types` — its type is always `timestamp` and is set
+automatically.
+
+When `output_column_types` is defined, Cube uses the aliased column
+names (matching the `select_statement`) for the Cube Store table
+definition and passes the raw source schema separately via
+`source_table`, so Cube Store knows how to deserialize incoming Kafka
+messages. Without it, column names come from the raw ksqlDB `DESCRIBE`
+output and will not match the aliased names in the `select_statement`
+or `unique_key_columns`.
+
+<Warning>
+
+`output_column_types` is required for Kafka streams mode when the
+pre-aggregation uses `unique_key_columns`. Without it, the unique key
+column names will not match the table column definitions, causing the
+pre-aggregation build to fail.
+
+</Warning>
+
 ### Stream format
 
 Cube Store expects Kafka messages to have a **JSON object** as their

docs-mintlify/admin/deployment/auto-suspension.mdx

@@ -124,4 +124,4 @@ response times to be significantly longer than usual.
 [self-effects]: #effects-on-experience
 [ref-refresh-worker]: /cube-core/architecture#refresh-worker
 [ref-sls]: /docs/integrations/semantic-layer-sync#on-schedule
-[ref-cube-version]: /admin/deployment/deployments#cube-version
+[ref-cube-version]: /admin/deployment/index#cube-version

docs-mintlify/admin/deployment/environments.mdx

@@ -9,12 +9,6 @@ Every Cube Cloud deployment provides a number of environments:
 - Multiple [staging environments](#staging-environments).
 - Per-user [development environments](#development-environments).
 
-<Note>
-
-Available on [all plans](https://cube.dev/pricing).
-
-</Note>
-
 ## Production environment
 
 This is the main environment. It runs the data model from the _main branch_.
@@ -120,5 +114,5 @@ credentials**][ref-credentials].
 [ref-suspend]: /docs/deployment/cloud/auto-suspension
 [ref-overview]: /docs/workspace/integrations#review-integrations
 [ref-credentials]: /docs/workspace/integrations#view-api-credentials
-[ref-version]: /docs/deployment/cloud/deployments#cube-version
-[ref-version-channel]: /docs/deployment/cloud/deployments#update-channels
+[ref-version]: /admin/deployment/index#cube-version
+[ref-version-channel]: /admin/deployment/index#update-channels

docs-mintlify/admin/deployment/index.mdx

@@ -147,7 +147,7 @@ You can view or change the update channel by navigating to **Settings →
 General → Cube version**:
 
 <Frame>
-  <img src="https://ucarecdn.com/3ef5fa36-4b27-437c-aa70-dbc0aa01255d/" />
+  <img src="https://ucarecdn.com/3ef5fa36-4b27-437c-aa70-dbc0aa01255d/-/format/auto/" />
 </Frame>
 
 You can select a specific version in the drop-down. Only versions that have been used by

docs-mintlify/admin/deployment/infrastructure.mdx

@@ -26,12 +26,6 @@ scaling, and monitoring your Cube Deployments, as well as managing Cube Store
 and persisting pre-aggregated data. This option requires the least effort to
 set up.
 
-<Note>
-
-Available on [all plans](https://cube.dev/pricing).
-
-</Note>
-
 Please note that some Enterprise features, such as VPC peering or PrivateLink are
 not available on the multi-tenant infrastructure. There's also a possibility of
 resource contention ("noisy neighbor") problem.

docs-mintlify/admin/monitoring/pre-aggregations.mdx

@@ -9,12 +9,6 @@ can see which pre-aggregations are accelerating queries, if they are [being
 refreshed][ref-caching-using-preaggs-refresh], along with the last 24 hours of
 build history.
 
-<Note>
-
-Available on [all plans](https://cube.dev/pricing).
-
-</Note>
-
 <Frame>
   <img src="https://ucarecdn.com/eb10de99-4ff6-4a9f-abd5-736971497583/" />
 </Frame>

docs-mintlify/admin/monitoring/query-history.mdx

@@ -10,8 +10,8 @@ failed.
 
 <Note>
 
-Available on [all plans](https://cube.dev/pricing).
-You can also choose a [Query History tier](/admin/account-billing/pricing#query-history-tiers).
+You can choose a [Query History tier](/admin/account-billing/pricing#query-history-tiers)
+to fit your retention and throughput needs.
 
 </Note>
 

docs-mintlify/docs.json

@@ -175,7 +175,8 @@
                 "pages": [
                   "docs/data-modeling/visual-modeler",
                   "docs/data-modeling/data-model-ide",
-                  "docs/data-modeling/dev-mode"
+                  "docs/data-modeling/dev-mode",
+                  "docs/data-modeling/access-policies-viewer"
                 ]
               }
             ]

docs-mintlify/docs/data-modeling/access-control/context.mdx

@@ -300,12 +300,6 @@ enrich the security context with additional attributes.
 When using Cube Cloud, you can enrich the security context with information about
 an authenticated user, obtained during their authentication.
 
-<Note>
-
-Available on [all plans](https://cube.dev/pricing).
-
-</Note>
-
 You can enable the authentication integration by navigating to the **Settings → Configuration**
 of your Cube Cloud deployment and using the **Enable Cloud Auth Integration** toggle.