diff --git a/website/docs/docs/dbt-cloud-apis/sl-graphql.md b/website/docs/docs/dbt-cloud-apis/sl-graphql.md index 3071d4ddf60..b2604c3e2ca 100644 --- a/website/docs/docs/dbt-cloud-apis/sl-graphql.md +++ b/website/docs/docs/dbt-cloud-apis/sl-graphql.md @@ -209,12 +209,12 @@ query( ```graphql Metric { - name: String! - description: String - type: MetricType! - typeParams: MetricTypeParams! - filter: WhereFilter - dimensions: [Dimension!]! + name: String! + description: String + type: MetricType! + typeParams: MetricTypeParams! + filter: WhereFilter + dimensions: [Dimension!]! queryableGranularities: [TimeGranularity!]! } ``` @@ -227,14 +227,14 @@ MetricType = [SIMPLE, RATIO, CUMULATIVE, DERIVED] ```graphql MetricTypeParams { - measure: MetricInputMeasure - inputMeasures: [MetricInputMeasure!]! - numerator: MetricInput - denominator: MetricInput - expr: String - window: MetricTimeWindow - grainToDate: TimeGranularity - metrics: [MetricInput!] + measure: MetricInputMeasure + inputMeasures: [MetricInputMeasure!]! + numerator: MetricInput + denominator: MetricInput + expr: String + window: MetricTimeWindow + grainToDate: TimeGranularity + metrics: [MetricInput!] } ``` @@ -243,12 +243,12 @@ MetricTypeParams { ```graphql Dimension { - name: String! - description: String - type: DimensionType! - typeParams: DimensionTypeParams - isPartition: Boolean! - expr: String + name: String! + description: String + type: DimensionType! + typeParams: DimensionTypeParams + isPartition: Boolean! + expr: String queryableGranularities: [TimeGranularity!]! } ``` @@ -352,7 +352,7 @@ mutation { environmentId: BigInt! metrics: [{name:"food_order_amount"}, {name: "order_gross_profit"}] groupBy: [{name:"metric_time, grain: "month"}, {name: "customer__customer_type"}] - limit: 10 + limit: 10 ) { queryId } @@ -400,3 +400,63 @@ The results default to the table but you can change it to any [pandas](https://p **Pagination** By default, we return 1024 rows per page. If your result set exceeds this, you need to increase the page number using the `pageNum` option. + +### Execute a Query through Python + +The `arrowResult` from the GraphQL query response isn't all that useful visually as it's a byte dump. You can utilize any language that supports Arrow to convert that byte into a Arrow table. Here is an example of querying and decoding the arrow result in Python. + +```python +import base64 +import pyarrow as pa + +headers = {"Authorization":"Bearer "} +query_result_request = """ +{ + query(environmentId: 70, queryId: "12345678") { + sql + status + error + arrowResult + } +} +""" + +gql_response = requests.post( + "http://localhost:8000/graphql", + json={"query": query_result_request}, + headers=headers, +) + +""" +gql_response.json() => +{ + "data": { + "query": { + "sql": "SELECT\n ordered_at AS metric_time__day\n , SUM(order_total) AS order_total\nFROM semantic_layer.orders orders_src_1\nGROUP BY\n ordered_at", + "status": "SUCCESSFUL", + "error": null, + "arrowResult": "arrow-byte-data" + } + } +} +""" + +def to_arrow_table(byte_string: str) -> pa.Table: + """Get a raw base64 string and convert to an Arrow Table.""" + with pa.ipc.open_stream(base64.b64decode(res)) as reader: + return pa.Table.from_batches(reader, reader.schema) + + +arrow_table = to_arrow_table(gql_response.json()["data"]["query"]["arrowResult"]) + +# Perform whatever functionality is available e.g., +# Convert to a pandas table +print(arrow_table.to_pandas()) +""" +order_total ordered_at + 3 2023-08-07 + 112 2023-08-08 + 12 2023-08-09 + 5123 2023-08-10 +""" +``` \ No newline at end of file