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Feature Availability: This feature may not be available in all product editions. For more information on available features, see Compare Editions.

BigQuery is a scalable cloud data warehouse integrated with the Google Cloud Platform for storage of a wide range of datasets. In some use cases, your transformation jobs can be executed completely in BigQuery. If all of your source datasets and outputs are in BigQuery locations, then transferring the execution steps from the Trifacta node to BigQuery yields the following benefits:

  • A minimum of data (recipe steps and associated metadata) is transferred between systems. Everything else remains in BigQuery.
  • Recipe steps are converted into SQL that is understandable and native to BigQuery. Execution times are much faster.
  • Depending on your environment, total cost of executing the job may be lower in BigQuery.

In this scenario, the recipe steps are converted to SQL, which is sequentially executed on the Datasets and Tables of your source data into temporary tables, from which the results that you have defined for your output are written.

Tip: When running a job in BigQuery, your data never leaves BigQuery.

Tip: For jobs that are executed in BigQuery, you can optionally enable the execution of the visual profile in BigQuery, too. This option is enabled for individual flows. For more information, see Flow Optimization Settings Dialog.

Requirements

  • This feature must be enabled by the project owner. See Configure Running Environments.
  • The permission to execute jobs in BigQuery must be enabled. In most environments, it is enabled by default. For more information, see Required Dataprep User Permissions.
  • In your flow, you must enable all general and BigQuery-specific flow optimizations. When all of these optimizations are enabled, the job can be pushed down to BigQuery for execution. For more information, see Flow Optimization Settings Dialog.

If the requirements and limitations are met, the  Dataprep by Trifacta application  automatically executes the job in BigQuery.

Limitations

BigQuery as a running environment requires that pushdowns be enabled for the project and for the specific flow for which the job is executed. If the flow and the project are properly configured, the job is automatically executed in BigQuery.

NOTE: BigQuery is not a running environment that you explicitly select or specify as part of a job. If all of the requirements are met, then the job is executed in BigQuery when you select Dataflow.


  • All datasources and all outputs specified in a job must be located within BigQuery.
  • Dataflow must be selected as running environment.
  • All recipe steps, including all  Wrangle  functions in the recipe, must be translatable to SQL. 

    NOTE: When attempting to execute a job in BigQuery, Dataprep by Trifacta application executes each recipe in BigQuery, until it reaches a step that cannot be executed there. At that point, data is transferred to 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,  Dataprep by Trifacta falls back to submitting the job through 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.
  • In BigQuery, escaped whitespace characters (\s) match a broader set of Unicode space characters than 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.

Base Storage File Support

Feature Availability: This feature may not be available in all product editions. For more information on available features, see Compare Editions.

In addition to BigQuery sources, you can execute jobs in BigQuery on source files from  Base Storage . 

Tip: The BigQuery running environment also supports hybrid sources, so you can use as sources Base Storage files and BigQuery tables in the same flow.

Requirements:

  • Publishing actions must be defined to be a target in BigQuery. 
  • External views must be enabled in BigQuery. External views are used to query GCS files.  For more information, see Required Dataprep User Permissions.
  • In the  Dataprep by Trifacta application , the following flow optimization settings must be enabled at the flow level. 
    • BigQuery optimization
    • Full execution for GCS file
  • In the Run Job page, the Dataflow + BigQuery running environment must be selected. For more information, see Run Job Page.

Supported file formats from  Base Storage:

  • CSV. CSV files that fail to meet the following requirements may cause job failures when executed in BigQuery, even though they can be imported into Dataprep by Trifacta. Requirements:

    • For job execution of CSV files in BigQuery, source CSV files must be well-formatted.

    • Newlines must be inserted. 

    • Fields must be demarcated with quotes and commas.

      • Quotes in field value must be escaped with quotes when needed ("").

    • Each row must have the same number of columns.
    • For more information, see  https://cloud.google.com/bigquery/docs/loading-data-cloud-storage-csv .

  • TSV
  • JSON (newline-delimited)
  • TXT
  • LOG
  • Compressed Files (gz and bz)

Supported file encodings:

  • UTF-8
  • ISO-8859-1

Supported delimiters:

  • Comma
  • Tab
  • Pipe

Supported quote characters:

  • No quotes
  • double quotes

Unsupported  Wrangle  for BigQuery Execution

The following transformations and functions are not currently supported for execution in BigQuery. 

NOTE: If your recipe contains any of the following transformations or functions, full job execution in BigQuery is not possible at this time. These transformations are expected to be supported and removed from this list in future releases.

General limitations

  • Regex patterns used must be valid RE2. Operations on non-RE2 regex patterns are not pushed down.
  • For more information on limitations on specific push-downs, see Flow Optimization Settings Dialog.

Unsupported transformations

None.

Unsupported functions

The following  Wrangle  functions are not currently supported for execution in BigQuery.

Aggregate functions

KTHLARGEST
KTHLARGESTIF
KTHLARGESTUNIQUE
KTHLARGESTUNIQUEIF
MODE
MODEIF
QUARTILE
APPROXIMATEMEDIAN
APPROXIMATEPERCENTILE
APPROXIMATEQUARTILE

For more information, see Aggregate Functions.


Math functions

LCM
NUMVALUE

Partially supported:

NUMFORMAT: Only supported when used for rounding.

For more information, see Math Functions.

Date functions

NETWORKDAYS
NETWORKDAYSINTL
MODEDATE
WORKDAY
WORKDAYINTL
MODEDATEIF
KTHLARGESTDATE
KTHLARGESTUNIQUEDATE
KTHLARGESTUNIQUEDATEIF
KTHLARGESTDATEIF
EOMONTH
SERIALNUMBER

String functions

RIGHTFIND
EXACT
STRINGGREATERTHAN
STRINGGREATERTHANEQUAL
STRINGLESSTHAN
STRINGLESSTHANEQUAL
DOUBLEMETAPHONEEQUALS
TRANSLITERATE

For more information, see String Functions.

Window functions

SESSION

For more information, see Window Functions.

Verify Execution

To verify execution in BigQuery, please do the following:

Steps:

  1. In the left nav bar, click the Jobs link. 
  2. In the Jobs page, select the job that you executed. 
  3. In the Overview tab, the value for Environment under the Execution summary should be: BigQuery.

For more information, see Job Details Page.

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