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WorksheetsSources & Sinks: BigQueryIO
Total questions: 7
Worksheet time: 4mins
What is the role of the BigQuery Storage API in Apache Beam?
To manage metadata and schema definitions for BigQuery tables.
To facilitate high-throughput consumption of data from BigQuery
To export BigQuery results to local storage before reading them
To transform BigQuery data into JSON format
When using BigQuery IO to read data, what is the process after Dataflow submits a SQL query to BigQuery?
BigQuery directly streams the results to the Dataflow pipeline.
BigQuery exports the results to a temporary staging location in Google Cloud Storage.
Dataflow performs the query and returns results directly without using BigQuery.
BigQuery stores the results in a local cache for subsequent retrieval
Which method can be used to write to multiple destinations in BigQuery with different schemas?
Using a static destination configuration in BigQuery IO.
Applying dynamic destinations to route writes to various tables.
Utilizing the file load method for batch writing.
Configuring BigQuery to handle data through the streaming write method only.
What is the default write method for streaming jobs in BigQuery IO?
File load method.
Batch method.
Streaming write method.
Dynamic destination method.
In BigQuery IO, how can you filter rows when reading data?
By specifying a column projection.
By using the withRowRestriction clause for row filtering.
By applying schema transformations before reading.
By defining dynamic destinations for row filtering.
Which feature of BigQuery IO can help reduce the amount of data read from BigQuery?
Dynamic destinations.
Column projection.
Row restriction.
Streaming write method.
What is the main advantage of using the BigQuery Storage API over the standard SQL method for reading data?
It provides direct access to BigQuery metadata.
It achieves higher throughput for reading data.
It automatically handles schema changes.
It simplifies the SQL query syntax.
