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Topic 5: Practice Questions
Which software libraries are supported by Cloud Machine Learning Engine?
A.
Theano and TensorFlow
B.
Theano and Torch
C.
TensorFlow
D.
TensorFlow and Torch
TensorFlow
Explanation
Cloud ML Engine mainly does two things:
Enables you to train machine learning models at scale by running TensorFlow training applications in the
cloud.
Hosts those trained models for you in the cloud so that you can use them to get predictions
about new data.
You want to use a BigQuery table as a data sink. In which writing mode(s) can you use BigQuery as a sink?
A.
Both batch and streaming
B.
BigQuery cannot be used as a sink
C.
Only batch
D.
Only streaming
Both batch and streaming
When you apply a BigQueryIO.Write transform in batch mode to write to a single table, Dataflow invokes a
BigQuery load job. When you apply a BigQueryIO.Write transform in streaming mode or in batch mode using
a function to specify the destination table, Dataflow uses BigQuery's streaming inserts
Which of the following is not possible using primitive roles?
A.
Give a user viewer access to BigQuery and owner access to Google Compute Engine instances.
B.
Give UserA owner access and UserB editor access for all datasets in a project.
C.
Give a user access to view all datasets in a project, but not run queries on them.
D.
Give GroupA owner access and GroupB editor access for all datasets in a project.
Give a user access to view all datasets in a project, but not run queries on them.
Primitive roles can be used to give owner, editor, or viewer access to a user or group, but they can't be used to
separate data access permissions from job-running permissions
Which methods can be used to reduce the number of rows processed by BigQuery?
A.
Splitting tables into multiple tables; putting data in partitions
B.
Splitting tables into multiple tables; putting data in partitions; using the LIMIT clause
C.
Putting data in partitions; using the LIMIT clause
D.
Splitting tables into multiple tables; using the LIMIT clause
Splitting tables into multiple tables; putting data in partitions
If you split a table into multiple tables (such as one table for each day), then you can limit your query to the
data in specific tables (such as for particular days). A better method is to use a partitioned table, as long as
your data can be separated by the day.
Which of these is not a supported method of putting data into a partitioned table?
A.
If you have existing data in a separate file for each day, then create a partitioned table and upload each
file into the appropriate partition.
B.
Run a query to get the records for a specific day from an existing table and for the destination table,
specify a partitioned table ending with the day in the format "$YYYYMMDD".
C.
Create a partitioned table and stream new records to it every day.
D.
Use ORDER BY to put a table's rows into chronological order and then change the table's type to
"Partitioned".
Use ORDER BY to put a table's rows into chronological order and then change the table's type to
"Partitioned".
Explanation
You cannot change an existing table into a partitioned table. You must create a partitioned table from scratch.
Then you can either stream data into it every day and the data will automatically be put in the right partition,
or you can load data into a specific partition by using "$YYYYMMDD" at the end of the table name.
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