GoodData-BigQuery Integration Details

When setting up direct data distribution from your BigQuery data warehouse, pay attention to the best practices concerning the following:

  • Output Stage prefixes
  • User access rights
  • Data types
  • Limitations

This article is applicable to all use cases of GoodData and BigQuery integration:

Contents:

Output Stage Prefixes

BigQuery does not support primary key constraints for tables. After generating the Output Stage, manually rename the a__ prefix to either cp__ (connection point) or r__ (reference) for the generated views.

User Access Rights

For the minimum sufficient level of access, your BigQuery service account must have the bigquery.dataViewer and bigquery.jobUser roles assigned (for more information, see https://cloud.google.com/iam/docs/service-accounts and https://cloud.google.com/bigquery/docs/access-control).

Specifically, your BigQuery service account must have the following permissions:

  • bigquery.jobs.create
  • bigquery.tables.get
  • bigquery.tables.getData
  • bigquery.tables.list

Data Types

The BigQuery data warehouse provides a wide range of data types. During mapping the BigQuery schema and the GoodData logical data model (LDM), data types are automatically converted from a BigQuery data type to a GoodData LDM data type. Some columns may be ignored because their data type is not supported within GoodData or their type may lead to performance issues. If you want to prevent automatic changes, update the schema manually.

BigQuery Data TypeGoodData LDM Data Type
ARRAYNot supported
BOOLVARCHAR (128)
BYTESNot supported
DATEDATE
DATETIMEDATE
FLOAT64DECIMAL (12, 2)
GEOGRAPYNot supported
INT64BIGINT
NUMERICDECIMAL (12, 2)
STRINGVARCHAR (128)
STRUCTNot supported
TIMENot supported
TIMESTAMPDATE

Limitations

Powered by Atlassian Confluence and Scroll Viewport.