Google prepway google Cloud Certified Professional-data-engineer Release Date by Woody q188 vce pdf

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Exam Name:	Google Professional Data Engineer Exam
Exam Code:	Professional-Data-Engineer Dumps
Vendor:	Google	Certification:	Google Cloud Certified
Questions:	387 Q&A's	Shared By:	woody

Question 60

You have a query that filters a BigQuery table using a WHERE clause on timestamp and ID columns. By using bq query – -dry_run you learn that the query triggers a full scan of the table, even though the filter on timestamp and ID select a tiny fraction of the overall data. You want to reduce the amount of data scanned by BigQuery with minimal changes to existing SQL queries. What should you do?

Options:

Create a separate table for each ID.

Use the LIMIT keyword to reduce the number of rows returned.

Recreate the table with a partitioning column and clustering column.

Use the bq query - -maximum_bytes_billed flag to restrict the number of bytes billed.

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Question 61

Given the record streams MJTelco is interested in ingesting per day, they are concerned about the cost of Google BigQuery increasing. MJTelco asks you to provide a design solution. They require a single large data table called tracking_table. Additionally, they want to minimize the cost of daily queries while performing fine-grained analysis of each day’s events. They also want to use streaming ingestion. What should you do?

Options:

Create a table called tracking_table and include a DATE column.

Create a partitioned table called tracking_table and include a TIMESTAMP column.

Create sharded tables for each day following the pattern tracking_table_YYYYMMDD.

Create a table called tracking_table with a TIMESTAMP column to represent the day.

Discussion

Question 62

MJTelco’s Google Cloud Dataflow pipeline is now ready to start receiving data from the 50,000 installations. You want to allow Cloud Dataflow to scale its compute power up as required. Which Cloud Dataflow pipeline configuration setting should you update?

Options:

The zone

The number of workers

The disk size per worker

The maximum number of workers

Discussion

Question 63

You need to compose visualization for operations teams with the following requirements:

Telemetry must include data from all 50,000 installations for the most recent 6 weeks (sampling once every minute)

The report must not be more than 3 hours delayed from live data.

The actionable report should only show suboptimal links.

Most suboptimal links should be sorted to the top.

Suboptimal links can be grouped and filtered by regional geography.

User response time to load the report must be <5 seconds.

You create a data source to store the last 6 weeks of data, and create visualizations that allow viewers to see multiple date ranges, distinct geographic regions, and unique installation types. You always show the latest data without any changes to your visualizations. You want to avoid creating and updating new visualizations each month. What should you do?

Options:

Look through the current data and compose a series of charts and tables, one for each possiblecombination of criteria.

Look through the current data and compose a small set of generalized charts and tables bound to criteria filters that allow value selection.

Export the data to a spreadsheet, compose a series of charts and tables, one for each possiblecombination of criteria, and spread them across multiple tabs.

Load the data into relational database tables, write a Google App Engine application that queries all rows, summarizes the data across each criteria, and then renders results using the Google Charts and visualization API.

Discussion

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