Google Professional Data Engineer Exam - Topic 3 Question 48 Discussion

Actual exam question for Google's Professional Data Engineer exam

Question #: 48
Topic #: 3

[All Professional Data Engineer Questions]

You have historical data covering the last three years in BigQuery and a data pipeline that delivers new data to BigQuery daily. You have noticed that when the Data Science team runs a query filtered on a date column and limited to 30--90 days of data, the query scans the entire table. You also noticed that your bill is increasing more quickly than you expected. You want to resolve the issue as cost-effectively as possible while maintaining the ability to conduct SQL queries. What should you do?

ARe-create the tables using DDL. Partition the tables by a column containing a TIMESTAMP or DATE Type.

BRecommend that the Data Science team export the table to a CSV file on Cloud Storage and use Cloud Datalab to explore the data by reading the files directly.

CModify your pipeline to maintain the last 30--90 days of data in one table and the longer history in a different table to minimize full table scans over the entire history.

DWrite an Apache Beam pipeline that creates a BigQuery table per day. Recommend that the Data Science team use wildcards on the table name suffixes to select the data they need.

Show Suggested Answer

Suggested Answer: C

by Andra at May 08, 2022, 03:16 PM

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Rebbecca

4 months ago

A is definitely the most cost-effective option here.

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Ernestine

4 months ago

Wait, D? Creating a table per day? That seems excessive!

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King

4 months ago

C could work, but managing multiple tables might get messy.

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Dulce

4 months ago

I disagree, B is way too cumbersome for daily queries.

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Alline

5 months ago

A sounds like a solid plan! Partitioning is key.

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Larae

5 months ago

I feel like using wildcards in option D could be useful, but it might not address the underlying issue of scanning the entire table. I lean towards partitioning instead.

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Portia

5 months ago

I'm a bit hesitant about option C; maintaining two separate tables sounds complicated. Wouldn't that just add more overhead to our data management?

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Lisandra

5 months ago

I remember a similar question about optimizing queries in BigQuery, and partitioning was definitely a key point. It seems like option A makes the most sense here.

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Laurena

5 months ago

I think partitioning the tables by date could really help with the query performance, but I'm not entirely sure if that's the only solution we need.

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King

5 months ago

I'm a bit unsure about this. Does a macro really cover both requirements of automating tasks and sharing knowledge articles? I'll need to think this through more carefully.

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Jose

5 months ago

I'm a bit confused by this question. I'll need to re-read it and think through what information is required to properly set up the invoice discount terms for the vendor in Sweden.

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