# Terms ## Why Would You Use Terms on Datasets? The Business Glossary(Term) feature in DataHub helps you use a shared vocabulary within the orgarnization, by providing a framework for defining a standardized set of data concepts and then associating them with the physical assets that exist within your data ecosystem. For more information about terms, refer to [About DataHub Business Glossary](/docs/glossary/business-glossary.md). ### Goal Of This Guide This guide will show you how to - Create: create a term. - Read : read terms attached to a dataset. - Add: add a term to a column of a dataset or a dataset itself. - Remove: remove a term from a dataset. ## Prerequisites For this tutorial, you need to deploy DataHub Quickstart and ingest sample data. For detailed information, please refer to [DataHub Quickstart Guide](/docs/quickstart.md). :::note Before modifying terms, you need to ensure the target dataset is already present in your DataHub instance. If you attempt to manipulate entities that do not exist, your operation will fail. In this guide, we will be using data from sample ingestion. ::: For more information on how to set up for GraphQL, please refer to [How To Set Up GraphQL](/docs/api/graphql/how-to-set-up-graphql.md). ## Create Terms The following code creates a term `Rate of Return`. #### GraphQL ```json mutation createGlossaryTerm { createGlossaryTerm(input: { name: "Rate of Return", id: "rateofreturn", description: "A rate of return (RoR) is the net gain or loss of an investment over a specified time period." }, ) } ``` If you see the following response, the operation was successful: ```python { "data": { "createGlossaryTerm": "urn:li:glossaryTerm:rateofreturn" }, "extensions": {} } ``` #### Curl ```shell curl --location --request POST 'http://localhost:8080/api/graphql' \ --header 'Authorization: Bearer ' \ --header 'Content-Type: application/json' \ --data-raw '{ "query": "mutation createGlossaryTerm { createGlossaryTerm(input: { name: \"Rate of Return\", id:\"rateofreturn\", description: \"A rate of return (RoR) is the net gain or loss of an investment over a specified time period.\" }) }", "variables":{}}' ``` Expected Response: ```json { "data": { "createGlossaryTerm": "urn:li:glossaryTerm:rateofreturn" }, "extensions": {} } ``` #### Python ```python # Inlined from /metadata-ingestion/examples/library/glossary_term_create_simple.py from datahub.sdk import DataHubClient from datahub.sdk.glossary_term import GlossaryTerm client = DataHubClient.from_env() term = GlossaryTerm( id="e5f67890", display_name="Rate of Return", definition="A rate of return (RoR) is the net gain or loss of an investment over a specified time period.", ) client.entities.upsert(term) ``` ### Expected Outcome of Creating Terms You can now see the new term `Rate of Return` has been created.

We can also verify this operation by programmatically searching `Rate of Return` term after running this code using the `datahub` cli. ```shell datahub get --urn "urn:li:glossaryTerm:rateofreturn" --aspect glossaryTermInfo { "glossaryTermInfo": { "definition": "A rate of return (RoR) is the net gain or loss of an investment over a specified time period.", "name": "Rate of Return", "termSource": "INTERNAL" } } ``` ## Read Terms #### GraphQL ```json query { dataset(urn: "urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)") { glossaryTerms { terms { term { urn glossaryTermInfo { name description } } } } } } ``` If you see the following response, the operation was successful: ```python { "data": { "dataset": { "glossaryTerms": { "terms": [ { "term": { "urn": "urn:li:glossaryTerm:CustomerAccount", "glossaryTermInfo": { "name": "CustomerAccount", "description": "account that represents an identified, named collection of balances and cumulative totals used to summarize customer transaction-related activity over a designated period of time" } } } ] } } }, "extensions": {} } ``` #### Curl ```shell curl --location --request POST 'http://localhost:8080/api/graphql' \ --header 'Authorization: Bearer ' \ --header 'Content-Type: application/json' \ --data-raw '{ "query": "{dataset(urn: \"urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)\") {glossaryTerms {terms {term {urn glossaryTermInfo { name description } } } } } }", "variables":{}}' ``` Expected Response: ````json {"data":{"dataset":{"glossaryTerms":{"terms":[{"term":{"urn":"urn:li:glossaryTerm:CustomerAccount","glossaryTermInfo":{"name":"CustomerAccount","description":"account that represents an identified, named collection of balances and cumulative totals used to summarize customer transaction-related activity over a designated period of time"}}}]}}},"extensions":{}}``` ```` #### Python ```python # Inlined from /metadata-ingestion/examples/library/dataset_query_terms.py from datahub.sdk import DataHubClient, DatasetUrn client = DataHubClient.from_env() dataset = client.entities.get( DatasetUrn(platform="hive", name="realestate_db.sales", env="PROD") ) print(dataset.terms) ``` ## Add Terms ### Add Terms to a dataset The following code shows you how can add terms to a dataset. In the following code, we add a term `Rate of Return` to a dataset named `fct_users_created`. #### GraphQL ```json mutation addTerms { addTerms( input: { termUrns: ["urn:li:glossaryTerm:rateofreturn"], resourceUrn: "urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)", } ) } ``` If you see the following response, the operation was successful: ```python { "data": { "addTerms": true }, "extensions": {} } ``` #### Curl ```shell curl --location --request POST 'http://localhost:8080/api/graphql' \ --header 'Authorization: Bearer ' \ --header 'Content-Type: application/json' \ --data-raw '{ "query": "mutation addTerm { addTerms(input: { termUrns: [\"urn:li:glossaryTerm:rateofreturn\"], resourceUrn: \"urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)\" }) }", "variables":{}}' ``` Expected Response: ```json { "data": { "addTerms": true }, "extensions": {} } ``` #### Python ```python # Inlined from /metadata-ingestion/examples/library/dataset_add_term.py from typing import List, Union from datahub.sdk import DataHubClient, DatasetUrn, GlossaryTermUrn def add_terms_to_dataset( client: DataHubClient, dataset_urn: DatasetUrn, term_urns: List[Union[GlossaryTermUrn, str]], ) -> None: """ Add glossary terms to a dataset. Args: client: DataHub client to use dataset_urn: URN of the dataset to update term_urns: List of term URNs or term names to add """ dataset = client.entities.get(dataset_urn) for term in term_urns: if isinstance(term, str): resolved_term_urn = client.resolve.term(name=term) dataset.add_term(resolved_term_urn) else: dataset.add_term(term) client.entities.update(dataset) def main() -> None: """ Main function to add terms to dataset example. """ client = DataHubClient.from_env() dataset_urn = DatasetUrn(platform="hive", name="realestate_db.sales", env="PROD") # Add terms using both URN and name resolution add_terms_to_dataset( client=client, dataset_urn=dataset_urn, term_urns=[ GlossaryTermUrn("Classification.HighlyConfidential"), "PII", # Will be resolved by name ], ) if __name__ == "__main__": main() ``` ### Add Terms to a Column of a Dataset #### GraphQL ```json mutation addTerms { addTerms( input: { termUrns: ["urn:li:glossaryTerm:rateofreturn"], resourceUrn: "urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)", subResourceType:DATASET_FIELD, subResource:"user_name"}) } ``` #### Curl ```shell curl --location --request POST 'http://localhost:8080/api/graphql' \ --header 'Authorization: Bearer ' \ --header 'Content-Type: application/json' \ --data-raw '{ "query": "mutation addTerms { addTerms(input: { termUrns: [\"urn:li:glossaryTerm:rateofreturn\"], resourceUrn: \"urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)\", subResourceType: DATASET_FIELD, subResource: \"user_name\" }) }", "variables":{}}' ``` Expected Response: ```json { "data": { "addTerms": true }, "extensions": {} } ``` #### Python ```python # Inlined from /metadata-ingestion/examples/library/dataset_add_column_term.py from datahub.sdk import DataHubClient, DatasetUrn, GlossaryTermUrn client = DataHubClient.from_env() dataset = client.entities.get( DatasetUrn(platform="hive", name="realestate_db.sales", env="PROD") ) dataset["address.zipcode"].add_term(GlossaryTermUrn("Classification.Location")) client.entities.update(dataset) ``` ### Expected Outcome of Adding Terms You can now see `Rate of Return` term has been added to `user_name` column.

## Remove Terms The following code remove a term from a dataset. After running this code, `Rate of Return` term will be removed from a `user_name` column. #### GraphQL ```json mutation removeTerm { removeTerm( input: { termUrn: "urn:li:glossaryTerm:rateofreturn", resourceUrn: "urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)", subResourceType:DATASET_FIELD, subResource:"user_name"}) } ``` Note that you can also remove a term from a dataset if you don't specify `subResourceType` and `subResource`. ```json mutation removeTerm { removeTerm( input: { termUrn: "urn:li:glossaryTerm:rateofreturn", resourceUrn: "urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)", }) } ``` Also note that you can remove terms from multiple entities or subresource using `batchRemoveTerms`. ```json mutation batchRemoveTerms { batchRemoveTerms( input: { termUrns: ["urn:li:glossaryTerm:rateofreturn"], resources: [ { resourceUrn:"urn:li:dataset:(urn:li:dataPlatform:hdfs,SampleHdfsDataset,PROD)"} , { resourceUrn:"urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)"} ,] } ) } ``` #### Curl ```shell curl --location --request POST 'http://localhost:8080/api/graphql' \ --header 'Authorization: Bearer ' \ --header 'Content-Type: application/json' \ --data-raw '{ "query": "mutation removeTerm { removeTerm(input: { termUrn: \"urn:li:glossaryTerm:rateofreturn\", resourceUrn: \"urn:li:dataset:(urn:li:dataPlatform:hdfs,SampleHdfsDataset,PROD)\" }) }", "variables":{}}' ``` #### Python ```python # Inlined from /metadata-ingestion/examples/library/dataset_remove_term_execute_graphql.py # read-modify-write requires access to the DataHubGraph (RestEmitter is not enough) from datahub.ingestion.graph.client import DatahubClientConfig, DataHubGraph gms_endpoint = "http://localhost:8080" graph = DataHubGraph(DatahubClientConfig(server=gms_endpoint)) # Query multiple aspects from entity query = """ mutation batchRemoveTerms { batchRemoveTerms( input: { termUrns: ["urn:li:glossaryTerm:rateofreturn"], resources: [ { resourceUrn:"urn:li:dataset:(urn:li:dataPlatform:hdfs,SampleHdfsDataset,PROD)"} , { resourceUrn:"urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)"} ,] } ) } """ result = graph.execute_graphql(query=query) print(result) ``` ### Expected Outcome of Removing Terms You can now see `Rate of Return` term has been removed to `user_name` column.