To write data to the Google BigQuery, create a data object write operation based on the Google BigQuery data object. Configure the write operation properties to determine how the Data Integration Service must write data to the Google BigQuery. Add the write operation as a Write transformation in a mapping.

You can use a Google BigQuery data object read operation to look up data in a Google BigQuery table. You can add the data object read operation to a mapping as a lookup transformation. You can look up data from a Google BigQuery table in a mapping based on a lookup condition. You can configure a cached lookup operation to cache the lookup table on the Spark engine and an uncached lookup operation in the native environment.

You can create read-only views in the native environment in Google BigQuery. Views in Google BigQuery are virtual tables generated from a stored query. When you query a view table, you can view the data and fields specified in the query of the view.

Use Google BigQuery to create one of the following types of views:

Legacy
Standard

Legacy view uses Legacy SQL dialect in BigQuery. Standard SQL uses GoogleSQL that offers more functionalities than Legacy SQL.

For a Google BigQuery source, you can create views to import the view of the object. Use views to preview the source data of the view. Use views with custom query, parameter, and key-range partitioning. You can preview table with advanced properties, such as SQL override, cached or uncached lookup, or a key-range partitioned source.