mchades commented on code in PR #13842: URL: https://github.com/apache/gravitino/pull/13842#discussion_r4284326465
########## docs/manage-semantic-model-metadata-using-gravitino.md: ########## @@ -0,0 +1,551 @@ +--- +title: "Manage Semantic Model Metadata" +slug: "/manage-semantic-model-metadata-using-gravitino" +keyword: "semantic model management, semantic metadata, Ossie, Gravitino" +license: "This software is licensed under the Apache License version 2." +--- + +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +## Introduction + +This page covers the Gravitino API for Semantic Models. For what a model contains, how its sources +are validated, and how it relates to tables and views, see [Semantic Models](./semantic-models.md). +For creating the catalog and schema a model lives in, see +[Manage Catalogs and Schemas](./manage-catalogs-and-schemas.md). + +## Before You Start + +The examples use the `2.0.0-SNAPSHOT` server and clients. They assume: + +* A server at `http://localhost:8090` and an existing metalake named `example`. +* A relational catalog named `sales`, with a schema named `mart`. +* An existing source table `sales.mart.orders` with `order_id` and `order_amount` columns. + +See [Manage Relational Metadata](./manage-relational-metadata-using-gravitino.md) to create the +source table. Add the credentials required by your deployment as described in +[Authentication](./security/how-to-authenticate.md). With authorization enabled, the caller also +needs the [model and source privileges](#ownership-and-privileges). + +Choose one language tab and follow its examples. Each language manages the same model names, so +running create or import again in another language reports that the model already exists. +Run the [drop examples](#drop-a-semantic-model) when you have finished. + +Java and Python model identifiers are relative to the loaded catalog (`schema.model`). Dataset +sources use `catalog.schema.object` within the same metalake. For SDK configuration, see +[Client Setup](./how-to-use-gravitino-client.md) and [Python Client](./how-to-use-python-client.md). + +<details> +<summary>Java and Python client setup and imports</summary> + +Place the operation snippets inside the client block below. The block closes the client when +finished; Java file operations also require the calling method to handle or declare `IOException`. + +<Tabs groupId='language' queryString> +<TabItem value="java" label="Java"> + +```java +import java.nio.file.Files; +import java.nio.file.Path; +import java.util.Map; +import org.apache.gravitino.NameIdentifier; +import org.apache.gravitino.Namespace; +import org.apache.gravitino.client.GravitinoClient; +import org.apache.gravitino.semantic.DataType; +import org.apache.gravitino.semantic.Dataset; +import org.apache.gravitino.semantic.DialectExpression; +import org.apache.gravitino.semantic.Expression; +import org.apache.gravitino.semantic.Field; +import org.apache.gravitino.semantic.Metric; +import org.apache.gravitino.semantic.OssieDocument; +import org.apache.gravitino.semantic.OssieFormat; +import org.apache.gravitino.semantic.SemanticModel; +import org.apache.gravitino.semantic.SemanticModelCatalog; +import org.apache.gravitino.semantic.SemanticModelChange; +import org.apache.gravitino.semantic.SemanticModelDefinition; + +try (GravitinoClient client = GravitinoClient.builder("http://localhost:8090";) + .withMetalake("example").build()) { + SemanticModelCatalog models = client.loadCatalog("sales").asSemanticModelCatalog(); + NameIdentifier ident = NameIdentifier.of("mart", "sales_model"); + + // Run the Java operation examples here. +} +``` + +</TabItem> +<TabItem value="python" label="Python"> + +```python +from pathlib import Path + +from gravitino import GravitinoClient, NameIdentifier +from gravitino.api.semantic.data_type import DataType +from gravitino.api.semantic.dataset import Dataset +from gravitino.api.semantic.dialect_expression import DialectExpression +from gravitino.api.semantic.expression import Expression +from gravitino.api.semantic.field import Field +from gravitino.api.semantic.metric import Metric +from gravitino.api.semantic.semantic_model_change import SemanticModelChange +from gravitino.api.semantic.semantic_model_definition import SemanticModelDefinition +from gravitino.namespace import Namespace + +client = GravitinoClient(uri="http://localhost:8090";, metalake_name="example") +try: + models = client.load_catalog("sales").as_semantic_model_catalog() + ident = NameIdentifier.of("mart", "sales_model") + + # Run the Python operation examples here. +finally: + client.close() +``` + +</TabItem> +</Tabs> + +</details> + +## Semantic Model Operations + +### Create a Semantic Model + +A model needs a name and a definition with at least one dataset. This example defines a field and +a revenue metric over the existing orders table. The native REST API nests the definition under +`definition`. Its field names include `primaryKey` and `datatype`. + +<Tabs groupId='language' queryString> +<TabItem value="shell" label="REST"> + +```shell +curl -X POST -H "Accept: application/vnd.gravitino.v1+json" \ + -H "Content-Type: application/json" -d '{ + "name": "sales_model", + "comment": "Governed sales definitions", + "properties": {"domain": "sales"}, + "definition": { + "datasets": [ + { + "name": "orders", + "source": {"namespace": ["sales", "mart"], "name": "orders"}, + "primaryKey": ["order_id"], + "fields": [ + { + "name": "order_amount", + "expression": { + "dialects": [{"dialect": "ANSI_SQL", "expression": "order_amount"}] + }, + "datatype": "Decimal" + } + ] + } + ], + "metrics": [ + { + "name": "total_revenue", + "expression": { + "dialects": [{"dialect": "ANSI_SQL", "expression": "SUM(orders.order_amount)"}] + }, + "datatype": "Decimal" + } + ] + } +}' http://localhost:8090/api/metalakes/example/catalogs/sales/schemas/mart/semantic-models +``` + +</TabItem> +<TabItem value="java" label="Java"> + +```java +Expression amountExpression = Expression.builder() + .withDialects(new DialectExpression[] { + DialectExpression.builder().withDialect("ANSI_SQL") + .withExpression("order_amount").build() + }).build(); +Field amount = Field.builder().withName("order_amount") + .withExpression(amountExpression).withDatatype(DataType.DECIMAL).build(); +Dataset orders = Dataset.builder().withName("orders") + .withSource(NameIdentifier.of("sales", "mart", "orders")) + .withPrimaryKey(new String[] {"order_id"}) + .withFields(new Field[] {amount}).build(); + +Expression revenueExpression = Expression.builder() + .withDialects(new DialectExpression[] { + DialectExpression.builder().withDialect("ANSI_SQL") + .withExpression("SUM(orders.order_amount)").build() + }).build(); +Metric revenue = Metric.builder().withName("total_revenue") + .withExpression(revenueExpression).withDatatype(DataType.DECIMAL).build(); +SemanticModelDefinition definition = SemanticModelDefinition.builder() + .withDatasets(new Dataset[] {orders}) + .withMetrics(new Metric[] {revenue}).build(); + +SemanticModel created = models.createSemanticModel( + ident, "Governed sales definitions", definition, Map.of("domain", "sales")); +``` + +</TabItem> +<TabItem value="python" label="Python"> + +```python +amount = Field( + "order_amount", + Expression([DialectExpression("ANSI_SQL", "order_amount")]), + datatype=DataType.DECIMAL) +orders = Dataset( + "orders", + NameIdentifier.of("sales", "mart", "orders"), + primary_key=["order_id"], + fields=[amount]) +revenue = Metric( + "total_revenue", + Expression([DialectExpression("ANSI_SQL", "SUM(orders.order_amount)")]), + datatype=DataType.DECIMAL) +definition = SemanticModelDefinition(datasets=[orders], metrics=[revenue]) + +created = models.create_semantic_model( + ident, "Governed sales definitions", definition, {"domain": "sales"}) +``` + +</TabItem> +</Tabs> + +The REST response contains `code: 0` and a `semanticModel` object with `name`, `comment`, +`properties`, `definition`, and `audit`. The SDKs return a `SemanticModel` directly. Creating a name +that already exists reports a conflict without overwriting the model. + +### List Semantic Models + +Listing returns identifiers rather than complete definitions. With authorization enabled, it +includes only models visible to the caller. + +<Tabs groupId='language' queryString> +<TabItem value="shell" label="REST"> + +```shell +curl -X GET -H "Accept: application/vnd.gravitino.v1+json" \ + http://localhost:8090/api/metalakes/example/catalogs/sales/schemas/mart/semantic-models +``` + +</TabItem> +<TabItem value="java" label="Java"> + +```java +NameIdentifier[] identifiers = models.listSemanticModels(Namespace.of("mart")); +``` + +</TabItem> +<TabItem value="python" label="Python"> + +```python +identifiers = models.list_semantic_models(Namespace.of("mart")) +``` + +</TabItem> +</Tabs> + +REST identifiers include the namespace `["example", "sales", "mart"]`. SDK identifiers are relative +to the loaded catalog, such as `mart.sales_model`. + +### Load a Semantic Model + +Load returns the stored definition, properties, comment, and audit information. + +<Tabs groupId='language' queryString> +<TabItem value="shell" label="REST"> + +```shell +curl -X GET -H "Accept: application/vnd.gravitino.v1+json" \ + http://localhost:8090/api/metalakes/example/catalogs/sales/schemas/mart/semantic-models/sales_model +``` + +</TabItem> +<TabItem value="java" label="Java"> + +```java +SemanticModel loaded = models.loadSemanticModel(ident); +``` + +</TabItem> +<TabItem value="python" label="Python"> + +```python +loaded = models.load_semantic_model(ident) +``` + +</TabItem> +</Tabs> + +### Alter a Semantic Model + +Changes are applied in order in one request. If any change or the resulting model is invalid, none +of the changes is persisted. + +| Change | REST update | +|--------|-------------| +| Rename within the schema | `{"@type":"rename","newName":"renamed_model"}` | +| Update or clear the comment | `{"@type":"updateComment","newComment":"Reviewed sales definitions"}`; use `null` to clear it. | +| Set a property | `{"@type":"setProperty","property":"domain","value":"finance"}` | +| Remove a property | `{"@type":"removeProperty","property":"domain"}` | +| Replace the definition | Set `@type` to `replaceDefinition` and supply the complete native definition in `definition`. | + +<Tabs groupId='language' queryString> +<TabItem value="shell" label="REST"> + +```shell +curl -X PUT -H "Accept: application/vnd.gravitino.v1+json" \ + -H "Content-Type: application/json" -d '{ + "updates": [ + {"@type": "updateComment", "newComment": "Reviewed sales definitions"}, + {"@type": "setProperty", "property": "domain", "value": "finance"} + ] +}' http://localhost:8090/api/metalakes/example/catalogs/sales/schemas/mart/semantic-models/sales_model +``` + +</TabItem> +<TabItem value="java" label="Java"> + +```java +SemanticModel altered = models.alterSemanticModel( + ident, + SemanticModelChange.updateComment("Reviewed sales definitions"), + SemanticModelChange.setProperty("domain", "finance")); +``` + +</TabItem> +<TabItem value="python" label="Python"> + +```python +altered = models.alter_semantic_model( + ident, + SemanticModelChange.update_comment("Reviewed sales definitions"), + SemanticModelChange.set_property("domain", "finance")) +``` + +</TabItem> +</Tabs> + +Definition replacement replaces all datasets, relationships, and metrics. Include everything you +want to retain. In Java, use `SemanticModelChange.replaceDefinition(definition)`; in Python, use +`SemanticModelChange.replace_definition(definition)`. Each replacement revalidates the complete +definition and its source access. Comment and property changes do not revalidate sources. + +## Apache Ossie Import and Export + +An Ossie document uses snake_case names, string source identifiers, and root-level datasets and +metrics. See [Exchanging Definitions](./semantic-models.md#exchanging-definitions) for the mapping +from the native REST format. + +### Import a Document + +Save the following as `sales.ossie.yaml`. It uses a different model name so it can be imported +alongside the model created above: + +```yaml +version: 0.2.0.dev0 +name: imported_sales_model +description: Imported sales definitions +datasets: + - name: orders + source: sales.mart.orders + primary_key: [order_id] + fields: + - name: order_amount + expression: + dialects: + - dialect: ANSI_SQL + expression: order_amount + datatype: Decimal +metrics: + - name: total_revenue + expression: + dialects: + - dialect: ANSI_SQL + expression: SUM(orders.order_amount) + datatype: Decimal +custom_extensions: + - vendor_name: GRAVITINO_PROPERTIES + data: '{"domain":"sales"}' +``` + +<Tabs groupId='language' queryString> +<TabItem value="shell" label="REST"> + +```shell +curl -X POST -H "Accept: application/vnd.gravitino.v1+json" \ + -H "Content-Type: application/yaml" --data-binary @sales.ossie.yaml \ + http://localhost:8090/api/metalakes/example/catalogs/sales/schemas/mart/semantic-models/ossie +``` + +</TabItem> +<TabItem value="java" label="Java"> + +```java +SemanticModel importedModel = models.importOssieDocument( + Namespace.of("mart"), OssieDocument.yaml(Files.readString(Path.of("sales.ossie.yaml")))); +``` + +</TabItem> +<TabItem value="python" label="Python"> + +```python +imported_model = models.import_ossie_document( + Namespace.of("mart"), Path("sales.ossie.yaml").read_text(encoding="utf-8")) +``` + +</TabItem> +</Tabs> + +Import creates a new model using the name in the document and applies the same validation as +native creation. An existing name reports a conflict. REST returns the native `semanticModel` +response; the SDKs return a `SemanticModel`. + +Send the raw document text. For JSON, use `Content-Type: application/json` in REST, +`OssieDocument.json(...)` in Java, or `document_format="json"` in Python. YAML requests use +`application/yaml`; `application/x-yaml` and `text/yaml` are also accepted. An omitted content type +defaults to YAML, while an unsupported content type returns `415`. Use an explicit content type +with curl, since its data options otherwise send a form content type. + +### Export a Document + +Export the native model as an Ossie JSON document: + +<Tabs groupId='language' queryString> +<TabItem value="shell" label="REST"> + +```shell +curl 'http://localhost:8090/api/metalakes/example/catalogs/sales/schemas/mart/semantic-models/sales_model/ossie?format=json' \ + -o exported-sales.ossie.json +``` + +</TabItem> +<TabItem value="java" label="Java"> + +```java +OssieDocument exported = models.exportOssieDocument(ident, OssieFormat.JSON); +Files.writeString(Path.of("exported-sales.ossie.json"), exported.content()); +``` + +</TabItem> +<TabItem value="python" label="Python"> + +```python +exported = models.export_ossie_document(ident, document_format="json") +Path("exported-sales.ossie.json").write_text(exported, encoding="utf-8") +``` + +</TabItem> +</Tabs> + +For YAML, use `format=yaml` in REST, `OssieFormat.YAML` in Java, or `document_format="yaml"` in +Python. REST and Python default to YAML when the format is omitted. REST returns the document +text without the native response wrapper, and Python returns that text unchanged. + +The `ossie-version` model property supplies the document's `version`. Native creation records the +server's default when the property is omitted; import records the document version. Other model +properties are exchanged through the root `GRAVITINO_PROPERTIES` custom extension, whose `data` +is a JSON object encoded as a string. Its values must be strings. Use `properties` when creating a +model through the native API; the reserved extension is for Ossie exchange. + +## Ownership and Privileges + +When authorization is enabled, a model's creator becomes its owner. For callers using explicit +privilege grants, access also requires `USE_CATALOG` and `USE_SCHEMA` on the parent objects: + +| Operation | Required model privilege or ownership | +|-----------|---------------------------------------| +| Create or import | `CREATE_SEMANTIC_MODEL` on the containing schema or an ancestor. | +| Discover, load, or export | `USE_SEMANTIC_MODEL`, `MODIFY_SEMANTIC_MODEL`, or ownership. | +| Alter or rename | `MODIFY_SEMANTIC_MODEL` or ownership. | +| Drop | Ownership; `MODIFY_SEMANTIC_MODEL` alone is insufficient. | + +Parent owners can also operate on contained models under the +[access-control rules](./security/access-control.md#required-privileges). A schema owner still +needs access to the catalog. Create, import, and definition replacement additionally check the +caller's access to every source table or view. Permission to load a Semantic Model does not itself +grant permission to read its source data. + +Ownership and role grants use metadata object type `SEMANTIC_MODEL` and a name such as +`sales.mart.sales_model` within the selected metalake. See +[Ownership](./security/access-control.md#ownership) and the +[access-control walkthrough](./security/access-control.md#walkthrough) to manage owners and roles. +Setting a string property named `owner` does not transfer ownership. + +### Tags and Policies + +Create a tag in the metalake before attaching it to a Semantic Model. For an existing tag named +`certified`, use the `semantic_model` object type in the REST path: + +```shell +curl -X POST -H "Accept: application/vnd.gravitino.v1+json" \ + -H "Content-Type: application/json" -d '{"tagsToAdd": ["certified"]}' \ + http://localhost:8090/api/metalakes/example/objects/semantic_model/sales.mart.sales_model/tags +``` + +Tag operations have their own authorization requirements. See +[Manage Tags](./manage-tags-in-gravitino.md#object-operations) for creating, attaching, listing, and +removing tags. Policies are selected through tags; see +[Policy-to-Tag Associations](./manage-policies-in-gravitino.md#policy-to-tag-associations). + +## Drop a Semantic Model + +Drop the models after trying the examples. Dropping removes the semantic metadata and its +governance associations without deleting source tables, views, or data. Review Comment: The sentence describes user-visible deletion. Dropped models are excluded from tag associations and role grants, and owner lookup no longer resolves them. The remaining relation rows are reclaimed by GC. I replaced the TODO with a comment pointing to the existing cleanup service. ########## docs/semantic-models.md: ########## @@ -0,0 +1,99 @@ +--- +title: "Semantic Models" +slug: "/semantic-models" +keyword: "semantic model, semantic metadata, Ossie, metrics, Gravitino" +license: "This software is licensed under the Apache License version 2." +--- + +## Introduction + +A Semantic Model describes the business meaning of data: the datasets to use, their fields and +relationships, and the metrics calculated from them. A sales model, for example, can give +analytical applications and AI tools a shared definition of revenue. + +Semantic Models live in schemas of relational catalogs. Gravitino stores their definitions and +manages their lifecycle, ownership, privileges, and tags, even when the underlying catalog system +has no semantic-model feature. They are separate from [SQL views](./tables-and-views.md) and the +AI/ML artifacts managed by a [model catalog](./model-catalog.md). + +Gravitino manages the definitions. Query compilation, execution, materialization, and publishing +engine-specific semantic objects are responsibilities of the applications that consume them. + +## Quick Start + +**1. Choose the source data.** Connect a relational catalog and identify the tables or logical views +the model will describe. See [Catalogs and Schemas](./catalogs-and-schemas.md). + +**2. Create or import a model.** Define datasets and metrics through REST or a client SDK, or import +an Apache Ossie YAML or JSON document. The source objects must already exist. + +**3. Govern and share the definition.** Assign access through roles, attach tags, and let consumers +load the model or export it as an Ossie document. Permission to read a definition does not itself +grant access to the source data. + +Worked examples are in [Manage Semantic Model Metadata](./manage-semantic-model-metadata-using-gravitino.md). + +## The Semantic Model + +A model has a name, an optional comment, string-valued Gravitino properties, a structured +definition, and audit information. The definition uses these components: + +| Component | Purpose | +|-----------|---------| +| `datasets` | A required, non-empty list of named sources. Each dataset can define fields, a primary key, and unique keys. | +| `fields` | Named expressions within a dataset, with optional data types, labels, descriptions, and dimension information. | +| `relationships` | Links between datasets in the same model, using source column names in `fromColumns` and `toColumns`. | Review Comment: Added a `customers` dataset with a unique key and an `orders_to_customers` relationship across the REST, Java, Python, and Ossie examples. The prerequisites and text now distinguish dataset names from source column names. ########## docs/manage-semantic-model-metadata-using-gravitino.md: ########## @@ -0,0 +1,551 @@ +--- +title: "Manage Semantic Model Metadata" +slug: "/manage-semantic-model-metadata-using-gravitino" +keyword: "semantic model management, semantic metadata, Ossie, Gravitino" +license: "This software is licensed under the Apache License version 2." +--- + +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +## Introduction + +This page covers the Gravitino API for Semantic Models. For what a model contains, how its sources +are validated, and how it relates to tables and views, see [Semantic Models](./semantic-models.md). +For creating the catalog and schema a model lives in, see +[Manage Catalogs and Schemas](./manage-catalogs-and-schemas.md). + +## Before You Start + +The examples use the `2.0.0-SNAPSHOT` server and clients. They assume: + +* A server at `http://localhost:8090` and an existing metalake named `example`. +* A relational catalog named `sales`, with a schema named `mart`. +* An existing source table `sales.mart.orders` with `order_id` and `order_amount` columns. + +See [Manage Relational Metadata](./manage-relational-metadata-using-gravitino.md) to create the +source table. Add the credentials required by your deployment as described in +[Authentication](./security/how-to-authenticate.md). With authorization enabled, the caller also +needs the [model and source privileges](#ownership-and-privileges). + +Choose one language tab and follow its examples. Each language manages the same model names, so +running create or import again in another language reports that the model already exists. +Run the [drop examples](#drop-a-semantic-model) when you have finished. + +Java and Python model identifiers are relative to the loaded catalog (`schema.model`). Dataset +sources use `catalog.schema.object` within the same metalake. For SDK configuration, see +[Client Setup](./how-to-use-gravitino-client.md) and [Python Client](./how-to-use-python-client.md). + +<details> +<summary>Java and Python client setup and imports</summary> + +Place the operation snippets inside the client block below. The block closes the client when +finished; Java file operations also require the calling method to handle or declare `IOException`. + +<Tabs groupId='language' queryString> +<TabItem value="java" label="Java"> + +```java +import java.nio.file.Files; +import java.nio.file.Path; +import java.util.Map; +import org.apache.gravitino.NameIdentifier; +import org.apache.gravitino.Namespace; +import org.apache.gravitino.client.GravitinoClient; +import org.apache.gravitino.semantic.DataType; +import org.apache.gravitino.semantic.Dataset; +import org.apache.gravitino.semantic.DialectExpression; +import org.apache.gravitino.semantic.Expression; +import org.apache.gravitino.semantic.Field; +import org.apache.gravitino.semantic.Metric; +import org.apache.gravitino.semantic.OssieDocument; +import org.apache.gravitino.semantic.OssieFormat; +import org.apache.gravitino.semantic.SemanticModel; +import org.apache.gravitino.semantic.SemanticModelCatalog; +import org.apache.gravitino.semantic.SemanticModelChange; +import org.apache.gravitino.semantic.SemanticModelDefinition; + +try (GravitinoClient client = GravitinoClient.builder("http://localhost:8090";) + .withMetalake("example").build()) { + SemanticModelCatalog models = client.loadCatalog("sales").asSemanticModelCatalog(); + NameIdentifier ident = NameIdentifier.of("mart", "sales_model"); + + // Run the Java operation examples here. +} +``` + +</TabItem> +<TabItem value="python" label="Python"> + +```python +from pathlib import Path + +from gravitino import GravitinoClient, NameIdentifier +from gravitino.api.semantic.data_type import DataType +from gravitino.api.semantic.dataset import Dataset +from gravitino.api.semantic.dialect_expression import DialectExpression +from gravitino.api.semantic.expression import Expression +from gravitino.api.semantic.field import Field +from gravitino.api.semantic.metric import Metric +from gravitino.api.semantic.semantic_model_change import SemanticModelChange +from gravitino.api.semantic.semantic_model_definition import SemanticModelDefinition +from gravitino.namespace import Namespace + +client = GravitinoClient(uri="http://localhost:8090";, metalake_name="example") +try: + models = client.load_catalog("sales").as_semantic_model_catalog() + ident = NameIdentifier.of("mart", "sales_model") + + # Run the Python operation examples here. +finally: + client.close() +``` + +</TabItem> +</Tabs> + +</details> + +## Semantic Model Operations + +### Create a Semantic Model + +A model needs a name and a definition with at least one dataset. This example defines a field and +a revenue metric over the existing orders table. The native REST API nests the definition under +`definition`. Its field names include `primaryKey` and `datatype`. + +<Tabs groupId='language' queryString> +<TabItem value="shell" label="REST"> + +```shell +curl -X POST -H "Accept: application/vnd.gravitino.v1+json" \ + -H "Content-Type: application/json" -d '{ + "name": "sales_model", + "comment": "Governed sales definitions", + "properties": {"domain": "sales"}, + "definition": { + "datasets": [ + { + "name": "orders", + "source": {"namespace": ["sales", "mart"], "name": "orders"}, + "primaryKey": ["order_id"], + "fields": [ + { + "name": "order_amount", + "expression": { + "dialects": [{"dialect": "ANSI_SQL", "expression": "order_amount"}] + }, + "datatype": "Decimal" + } + ] + } + ], + "metrics": [ + { + "name": "total_revenue", + "expression": { + "dialects": [{"dialect": "ANSI_SQL", "expression": "SUM(orders.order_amount)"}] + }, + "datatype": "Decimal" + } + ] + } +}' http://localhost:8090/api/metalakes/example/catalogs/sales/schemas/mart/semantic-models +``` + +</TabItem> +<TabItem value="java" label="Java"> + +```java +Expression amountExpression = Expression.builder() + .withDialects(new DialectExpression[] { + DialectExpression.builder().withDialect("ANSI_SQL") Review Comment: Updated both SDK examples to use `Dialects.ANSI_SQL` and listed the predefined constants. The text also explains that other non-empty dialect identifiers are accepted and preserved, with support determined by consumers. ########## docs/open-api/semantic-models.yaml: ########## @@ -53,8 +53,9 @@ paths: summary: Create a Semantic Model description: >- Creates a schema-scoped Semantic Model in a relational catalog. The complete definition is - validated before the model is stored, including source identifier shape. Source existence, - source columns, and source authorization checks are not yet implemented. + validated before the model is stored, including source identifier shape, source existence, + and primary-key, unique-key, and relationship columns. When authorization is enabled, Review Comment: Added the source and column validation requirements to the import description, including source-access permissions. The existing `400` and `403` responses already cover these failures. -- This is an automated message from the Apache Git Service. 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