You are developing a software application using Google's Dataflow SDK, and want to use conditional, for loops and other complex programming structures to create a branching pipeline. Which component will be used for the data processing operation?
Answer(s): B
In Google Cloud, the Dataflow SDK provides a transform component. It is responsible for the data processing operation. You can use conditional, for loops, and other complex programming structure to create a branching pipeline.
https://cloud.google.com/dataflow/model/programming-model
Which of the following IAM roles does your Compute Engine account require to be able to run pipeline jobs?
Answer(s): A
The dataflow.worker role provides the permissions necessary for a Compute Engine service account to execute work units for a Dataflow pipeline
https://cloud.google.com/dataflow/access-control
Which of the following is not true about Dataflow pipelines?
Answer(s): D
The data and transforms in a pipeline are unique to, and owned by, that pipeline. While your program can create multiple pipelines, pipelines cannot share data or transforms
https://cloud.google.com/dataflow/model/pipelines
By default, which of the following windowing behavior does Dataflow apply to unbounded data sets?
Dataflow's default windowing behavior is to assign all elements of a PCollection to a single, global window, even for unbounded PCollections
https://cloud.google.com/dataflow/model/pcollection
Which of the following job types are supported by Cloud Dataproc (select 3 answers)?
Answer(s): A,B,D
Cloud Dataproc provides out-of-the box and end-to-end support for many of the most popular job types, including Spark, Spark SQL, PySpark, MapReduce, Hive, and Pig jobs.
https://cloud.google.com/dataproc/docs/resources/faq#what_type_of_jobs_can_i_run
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