Google bigquery 气流的bigqueryoperator不使用udf

Google bigquery 气流的bigqueryoperator不使用udf,google-bigquery,airflow,google-cloud-composer,Google Bigquery,Airflow,Google Cloud Composer,我正在尝试使用Google的Composer任务在Airflow中运行一个基本的bigquery操作符,该任务使用用户定义的函数UDF 该示例来自BigQuery,并在BigQuery中完美运行 然而,当我上传到composer时,我找不到函数:multiplyInputs。。。请参见下面的python脚本 BigQueryOperator的udf_config字段需要一个列表,因此我将我的udf定义为一个包含一个字符串的列表-不确定这是否正确,因为它显然没有注册为udf 任何帮助都将不胜感激

我正在尝试使用Google的Composer任务在Airflow中运行一个基本的bigquery操作符,该任务使用用户定义的函数UDF

该示例来自BigQuery,并在BigQuery中完美运行

然而,当我上传到composer时,我找不到函数:multiplyInputs。。。请参见下面的python脚本

BigQueryOperator的udf_config字段需要一个列表,因此我将我的udf定义为一个包含一个字符串的列表-不确定这是否正确,因为它显然没有注册为udf

任何帮助都将不胜感激

import datetime
from airflow import models
from airflow.contrib.operators import bigquery_operator

yesterday = datetime.datetime.combine(datetime.datetime.today() -             
datetime.timedelta(1),
                                  datetime.datetime.min.time())
default_dag_args = {
                # Setting start date as yesterday starts the DAG 
immediately when it is
                # detected in the Cloud Storage bucket.
                'start_date': yesterday,
                # To email on failure or retry set 'email' arg to your 
email and enable
                # emailing here.
                'email_on_failure': False,
                'email_on_retry': False,
                # If a task fails, retry it once after waiting at least 
5 minutes
                'retries': 1,
                'retry_delay': datetime.timedelta(minutes=5),
                'project_id': 'vital-platform-791'
}

with models.DAG('udf_example',
                schedule_interval=datetime.timedelta(days=1),
                default_args=default_dag_args) as dag:

    table = 'udf_table'

    # flatten fe table
    task_id = table + '_fe'

    udf_config = ["""CREATE TEMPORARY FUNCTION multiplyInputs(x 
                  FLOAT64, y FLOAT64)
                  RETURNS FLOAT64
                  LANGUAGE js AS \"""
                  return x*y;
                  \""";
                  """]

    print udf_config

    query = """WITH numbers AS
              (SELECT 1 AS x, 5 as y
              UNION ALL
              SELECT 2 AS x, 10 as y
              UNION ALL
              SELECT 3 as x, 15 as y)
            SELECT x, y, multiplyInputs(x, y) as product
            FROM numbers"""

    print query

    query = query
    destination_table = 'vital-platform-791.alpha_factors. 
                          {table}_fe'.format(table=table)

    t_fe = bigquery_operator.BigQueryOperator(task_id=task_id,
                                          bql=query,                                         
                     destination_dataset_table=destination_table,
                                          use_legacy_sql=False,                                              
                     write_disposition='WRITE_TRUNCATE',
                                          udf_config=udf_config)

我对这个例子有点困惑。看起来您只需要合并udf_配置和查询:


将您的UDF函数上传到Google云存储中,并将其传递给UDF_配置参数

例如:

您的UDF函数位于gs://testbucket/testfolder/UDF.js中

然后在dag中使用:

udf_gcs_path=gs://testbucket/testfolder/udf.js BigQueryOperator.BigQueryOperator任务id=任务id, bql=查询, 目的地\数据集\表格=目的地\表格, 使用\u legacy\u sql=False, write_disposition='write_TRUNCATE', udf_config=[{resourceUri:udf_gcs_path}] 参考资料:


谢谢,这个很好用。BigQueryOperator的显式udf_config字段在某种程度上误导了我,因为我认为在使用udf时必须填充它。我认为问题是针对标准SQL的,因此应该接受这个答案,而不是我的答案。干得好@ElliottbrossardThank,看看文档,这似乎是传统sql的方法,而不是标准sql?
query = ""CREATE TEMPORARY FUNCTION multiplyInputs(x 
              FLOAT64, y FLOAT64)
              RETURNS FLOAT64
              LANGUAGE js AS \"""
              return x*y;
              \""";
              WITH numbers AS
          (SELECT 1 AS x, 5 as y
          UNION ALL
          SELECT 2 AS x, 10 as y
          UNION ALL
          SELECT 3 as x, 15 as y)
        SELECT x, y, multiplyInputs(x, y) as product
        FROM numbers;"""