mchades commented on code in PR #13842: URL: https://github.com/apache/gravitino/pull/13842#discussion_r4291178870
########## 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: Updated the mapping table and Ossie introduction to include root-level `relationships`, and added the `uniqueKeys`, `fromColumns`, and `toColumns` field-name mappings. ########## 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: Removed the troubleshooting table to avoid duplicating the OpenAPI error responses. The create section already states that `from` and `to` name datasets in the model. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
