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Comment: Published by Scroll Versions from space DEV and version r0810


  • All datasources and all outputs specified in a job must be located within BigQuery.
  • D s dataflow
     must be selected as running environment.
  • All recipe steps, including all 

    D s lang
     functions in the recipe, must be translatable to SQL. 


    NOTE: When attempting to execute a job in BigQuery,

    D s webapp
    executes each recipe in BigQuery, until it reaches a step that cannot be executed there. At that point, data is transferred to
    D s dataflow
    , where the remainder of the job is executed.

  • BigQuery imposes a limit of 1 MB for all submitted SQL queries. If this limit is exceeded during job execution, 
    D s product
     falls back to submitting the job through 
    D s dataflow
  • Some transformations and functions are not currently supported for execution in BigQuery. See below.
  • Upserts, merges, and deletes are not supported for full execution in BigQuery.
  • Sampling jobs are not supported for execution in BigQuery.
  • If your recipe includes data quality rules, the job cannot be fully executed in BigQuery.
  • BigQuery does not permit partitioned tables to be replaced. As a result, the Drop and Load publishing action is not supported when writing to a partitioned table during BigQuery execution. For more information, see
  • In BigQuery, escaped whitespace characters (\s) match a broader set of Unicode space characters than 
    D s dataflow
    , due to differences in implementation of regular expressions between the two running environments. Depending on your dataset, this difference may result in mismatches between rows in your results when running the same job across different running environments.