Google Professional-Data-Engineer Exam Success: Google Professional Data Engineer Exam Complete Study and Preparation Tips

The HBase shell is a command-line tool that performs administrative tasks, such as creating and deleting tables. The Cloud Bigtable HBase client for Java makes it possible to use the HBase shell to connect to Cloud Bigtable.

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.

Using the Drain option to stop your job tells the Dataflow service to finish your job in its current state. Your job will immediately stop ingesting new data from input sources, but the Dataflow

service will preserve any existing resources (such as worker instances) to finish processing and writing any buffered data in your pipeline.

When collecting and grouping data into windows, Beam uses triggers to determine when to emit the aggregated results of each window.

Processing time triggers. These triggers operate on the processing time – the time when the data element is processed at any given stage in the pipeline.

Event time triggers. These triggers operate on the event time, as indicated by the timestamp on each data element. Beam’s default trigger is event time-based.

To make updating files and properties easy, the --properties command uses a special format to specify the configuration file and the property and value within the file that should be updated. The formatting is as follows: file_prefix:property=value.

Cloud Bigtable is a sparsely populated table that can scale to billions of rows and thousands of columns, allowing you to store terabytes or even petabytes of data. A single value in each row is indexed; this value is known as the row key.

All operations are atomic at the row level. For example, if you update two rows in a table, it's possible that one row will be updated successfully and the other update will fail. Avoid schema designs that require atomicity across rows.

The Cloud Dataflow connector for Cloud Bigtable makes it possible to use Cloud Bigtable in a Cloud Dataflow pipeline. You can use the connector for both batch and streaming operations.

A Cloud Dataproc Viewer is limited in its actions based on its role. A viewer can only list clusters, get cluster details, list jobs, get job details, list operations, and get operation details.