The _________ for Cloud Bigtable makes it possible to use Cloud Bigtable in a Cloud Dataflow pipeline.
Answer(s): A
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.
https://cloud.google.com/bigtable/docs/dataflow-hbase
Does Dataflow process batch data pipelines or streaming data pipelines?
Answer(s): B
Dataflow is a unified processing model, and can execute both streaming and batch data pipelines
https://cloud.google.com/dataflow/
You are planning to use Google's Dataflow SDK to analyze customer data such as displayed below. Your project requirement is to extract only the customer name from the data source and then write to an output PCollection.Tom,555 X streetTim,553 Y streetSam, 111 Z streetWhich operation is best suited for the above data processing requirement?
In Google Cloud dataflow SDK, you can use the ParDo to extract only a customer name of each element in your PCollection.
https://cloud.google.com/dataflow/model/par-do
Which Cloud Dataflow / Beam feature should you use to aggregate data in an unbounded data source every hour based on the time when the data entered the pipeline?
Answer(s): D
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.
https://beam.apache.org/documentation/programming-guide/#triggers
Which of the following is NOT true about Dataflow pipelines?
Dataflow pipelines can also run on alternate runtimes like Spark and Flink, as they are built using the Apache Beam SDKs
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