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BigQuery Executor

BigQueryExecutor allows you to execute SQL code in BigQuery.

Install

Ensure that garf-executors library is installed with BigQuery support:

pip install garf-executors[bq]

Usage

After garf-executors is installed you can use garf utility to perform fetching.

echo "SELECT campaign_id FROM project.dataset.table" > query.sql

garf query.sql --source bq \
  --output csv \
  --source.project_id=MY_PROJECT
where

  • query- local or remote path(s) to files with queries.
  • output - output supported by garf-io library.
from garf.executors.bq_executor import BigQueryExecutor


query_executor = BigQueryExecutor(project_id=MY_PROJECT)

query_text = "SELECT campaign_id FROM project.dataset.table"

# execute query and get report back
report = query_executor.execute(query=query_text, title="campaign")

# execute query and save results to `campaign.csv`
query_executor.execute(
  query=query_text,
  title="campaign",
  context={'writer': 'csv'}
)

curl -X 'POST' \
  'http://127.0.0.1:8000/api/execute' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
  "source": "bq",
  "query": "SELECT campaign_id FROM project.dataset.table",
  "title": "campaign",
  "context": {
    "writer": "csv",
    "fetcher_parameters": {
      "project_id": "MY_PROJECT"
    }
  }
}'