jerryshao commented on code in PR #13842:
URL: https://github.com/apache/gravitino/pull/13842#discussion_r4290163411
##########
docs/semantic-models.md:
##########
@@ -0,0 +1,102 @@
+---
+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`. |
+| `metrics` | Named expressions such as `SUM(orders.order_amount)`, with
optional data types and descriptions. |
+| `aiContext` | Context for consumers, represented as text or a structured
object. |
+| `customExtensions` | Vendor-specific information preserved with the
definition. |
+
+Expressions contain one or more dialect-specific representations. The Java and
Python SDKs provide
+`Dialects` constants for `ANSI_SQL`, `SNOWFLAKE`, `MDX`, `TABLEAU`,
`DATABRICKS`, `MAQL`, and `BIGQUERY`.
+Other non-empty dialect identifiers are also accepted and preserved. Choose
identifiers supported
+by the application consuming the model. Gravitino validates the definition's
structure but does
+not parse or execute the expression text.
+
+### Sources and Validation
+
+Dataset sources use `catalog.schema.object` within the model's metalake. They
may reference another
+catalog or schema in that metalake. Each source must resolve to an existing
table or a logical view
+supported by its catalog. Cross-metalake references are not supported.
+
+The `from` and `to` endpoints of a relationship name datasets within the model.
+Primary-key, unique-key, and relationship columns refer to columns of the
source table or view,
+rather than field aliases in the model. Gravitino checks that these columns
exist; it does not
+check whether the data satisfies the declared keys or relationships.
+
+Creating, importing, or replacing a definition checks source existence and
these columns, even
+when authorization is disabled. With authorization enabled, source lookups
also require the
+caller's access to the source metadata.
+
+Loading or exporting a model, renaming it, and changing only its comment or
properties do not
+revalidate source metadata. Review definitions when their source schemas
change: a stored model
+can become stale after a source column is changed or removed.
+
+### Exchanging Definitions
+
+The native REST API and standalone Apache Ossie documents represent the same
definition in
+different forms:
+
+| Aspect | Native REST API | Ossie document |
+|--------|-----------------|----------------|
+| Definition location | Nested under `definition` in the model object |
Datasets and metrics at the document root |
+| Field names | `primaryKey`, `datatype` | `primary_key`, `datatype` |
Review Comment:
[Nit] The format-mapping table no longer covers the fields the examples use.
This commit put `relationships` at the Ossie document root and
`uniqueKeys`/`fromColumns`/`toColumns` into every create example, but this
table still says "Datasets and metrics at the document root" and maps only
`primaryKey`, `datatype`. `relationships` is a root property of the document
(OssieDocumentConverter.java:56-65), and the snake_case names a reader now
needs are `unique_keys` (:71, :332), `from_columns` and `to_columns` (:87,
:426). The same omission is in the guide's Ossie intro sentence,
docs/manage-semantic-model-metadata-using-gravitino.md:385-386 ("root-level
datasets and metrics").
Adding `relationships` to the "Definition location" row and
`uniqueKeys`/`fromColumns`/`toColumns` to the "Field names" row - and the word
to that guide sentence - keeps the mapping complete for the new examples.
Verified by: reading `ROOT_PROPERTIES`, `DATASET_PROPERTIES` and
`RELATIONSHIP_PROPERTIES` in OssieDocumentConverter and the
`readDataset`/`readRelationship` key reads, then grepping both new pages for
where the snake_case mapping is stated.
##########
docs/manage-semantic-model-metadata-using-gravitino.md:
##########
@@ -0,0 +1,612 @@
+---
+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`, `customer_id`,
and `order_amount` columns.
+* An existing source table `sales.mart.customers` with `customer_id` and
`customer_code` columns.
+
+See [Manage Relational
Metadata](./manage-relational-metadata-using-gravitino.md) to create the
+source tables. 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.Dialects;
+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.Relationship;
+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.dialects import Dialects
+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.relationship import Relationship
+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 revenue
+metric over orders and links orders to customers by `customer_id`. The native
REST API nests the
+definition under `definition`. Its field names include `primaryKey` and
`datatype`.
+
+The relationship's `from` and `to` name datasets in the model. Its column
lists and the datasets'
+keys use source table column names, even when those columns are not listed in
`fields`. Each array
+inside `uniqueKeys` defines one unique key.
+
+<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"
+ }
+ ]
+ },
+ {
+ "name": "customers",
+ "source": {"namespace": ["sales", "mart"], "name": "customers"},
+ "primaryKey": ["customer_id"],
+ "uniqueKeys": [["customer_code"]],
+ "fields": []
+ }
+ ],
+ "relationships": [
+ {
+ "name": "orders_to_customers",
+ "from": "orders",
+ "to": "customers",
+ "fromColumns": ["customer_id"],
+ "toColumns": ["customer_id"]
+ }
+ ],
+ "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(Dialects.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();
+Dataset customers = Dataset.builder().withName("customers")
+ .withSource(NameIdentifier.of("sales", "mart", "customers"))
+ .withPrimaryKey(new String[] {"customer_id"})
+ .withUniqueKeys(new String[][] {{"customer_code"}})
+ .withFields(new Field[0]).build();
+Relationship ordersToCustomers =
Relationship.builder().withName("orders_to_customers")
+ .withFrom("orders").withTo("customers")
+ .withFromColumns(new String[] {"customer_id"})
+ .withToColumns(new String[] {"customer_id"}).build();
+
+Expression revenueExpression = Expression.builder()
+ .withDialects(new DialectExpression[] {
+ DialectExpression.builder().withDialect(Dialects.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, customers})
+ .withRelationships(new Relationship[] {ordersToCustomers})
+ .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(Dialects.ANSI_SQL, "order_amount")]),
+ datatype=DataType.DECIMAL)
+orders = Dataset(
+ "orders",
+ NameIdentifier.of("sales", "mart", "orders"),
+ primary_key=["order_id"],
+ fields=[amount])
+customers = Dataset(
+ "customers",
+ NameIdentifier.of("sales", "mart", "customers"),
+ primary_key=["customer_id"],
+ unique_keys=[["customer_code"]],
+ fields=[])
+orders_to_customers = Relationship(
+ "orders_to_customers",
+ from_dataset="orders",
+ to_dataset="customers",
+ from_columns=["customer_id"],
+ to_columns=["customer_id"])
+revenue = Metric(
+ "total_revenue",
+ Expression([DialectExpression(Dialects.ANSI_SQL,
"SUM(orders.order_amount)")]),
+ datatype=DataType.DECIMAL)
+definition = SemanticModelDefinition(
+ datasets=[orders, customers],
+ relationships=[orders_to_customers],
+ 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
+ - name: customers
+ source: sales.mart.customers
+ primary_key: [customer_id]
+ unique_keys: [[customer_code]]
+ fields: []
+relationships:
+ - name: orders_to_customers
+ from: orders
+ to: customers
+ from_columns: [customer_id]
+ to_columns: [customer_id]
+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.
+
+<Tabs groupId='language' queryString>
+<TabItem value="shell" label="REST">
+
+```shell
+curl -X DELETE -H "Accept: application/vnd.gravitino.v1+json" \
+
http://localhost:8090/api/metalakes/example/catalogs/sales/schemas/mart/semantic-models/sales_model
+curl -X DELETE -H "Accept: application/vnd.gravitino.v1+json" \
+
http://localhost:8090/api/metalakes/example/catalogs/sales/schemas/mart/semantic-models/imported_sales_model
+```
+
+</TabItem>
+<TabItem value="java" label="Java">
+
+```java
+boolean dropped = models.dropSemanticModel(ident);
+boolean importedDropped = models.dropSemanticModel(
+ NameIdentifier.of("mart", "imported_sales_model"));
+```
+
+</TabItem>
+<TabItem value="python" label="Python">
+
+```python
+dropped = models.drop_semantic_model(ident)
+imported_dropped = models.drop_semantic_model(
+ NameIdentifier.of("mart", "imported_sales_model"))
+```
+
+</TabItem>
+</Tabs>
+
+REST returns `{"code":0,"dropped":true}` when the model is dropped, while the
SDKs return a boolean.
+An authorized request for an absent model returns `false` (`dropped: false` in
REST).
+
+## Other Interfaces
+
+The [Gravitino MCP server](./gravitino-mcp-server.md#semantic-models) provides
+`list_of_semantic_models`, `load_semantic_model`, `create_semantic_model`,
`alter_semantic_model`,
+and `drop_semantic_model`. Enable the `semantic_model` tool tag when filtering
tools.
+Create and alter use the native REST definition format. Use REST or the SDKs
for Ossie import and
+export. The current Web UI does not provide Semantic Model workflows.
+
+## Troubleshooting
+
+| HTTP status | What to check |
+|-------------|---------------|
+| `400` | Definition or document syntax, source identifiers, missing sources,
key or relationship columns, and supported export formats. |
Review Comment:
[Nit] The 400 row misses the one new failure mode the relationship example
introduces.
A relationship whose `from` or `to` does not name a dataset in the same
definition fails with "Unknown dataset %s in relationship", which is a distinct
400 from the column checks: `checkColumns` throws it when the dataset-name
lookup returns null (SemanticModelSourceValidator.java:215-218, reached from
:137-146). Now that every create example carries a relationship, a mistyped
dataset name is the likeliest 400 a reader will hit, and "key or relationship
columns" does not point at it.
Suggest extending the row, for example: "... missing sources, unknown
relationship dataset names, key or relationship columns, and supported export
formats."
Verified by: reading `SemanticModelSourceValidator.validate` and
`checkColumns` and confirming `IllegalSemanticModelException` maps to 400 in
`ExceptionHandlers`.
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