PDE Storing the Data Practice Test 8 — 15 Questions

Question 1

A financial services company uses Cloud Bigtable to store trade data. They are experiencing hot-spotting on a single node, causing high latency. The row key format is [trade_id]#[timestamp]. Which row key design change would BEST distribute writes across tablets?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Use a hashed prefix of the trade_id, e.g., [hash(trade_id)]#[trade_id]#[timestamp]. Adding a hashed prefix of the trade_id ensures that writes are evenly distributed across all Bigtable tablets. Bigtable partitions data by row key lexicographic order; without a hash, sequential trade IDs or timestamps cause all recent writes to land on a single tablet, creating a hotspot. The hash spreads the write load uniformly, regardless of the underlying key pattern.

Answer

Use a single row key of [timestamp]

Answer

Increase the number of Bigtable nodes to 20

Answer

Change row key to [timestamp]#[trade_id]

Question 2

A data engineer needs to enforce that all datasets in a project expire after 90 days to reduce storage costs. They want to automate this without manual intervention. Which approach should they use?

Accepted Answer

Set a default table expiration on each BigQuery dataset to 90 days. BigQuery datasets support a default table expiration setting that automatically deletes tables after a specified number of days. This enforces a 90-day lifecycle for all tables in the dataset without requiring manual intervention or external automation, directly addressing the cost reduction goal.

Answer

Use Cloud Storage lifecycle rules to delete tables after 90 days

Answer

Create an IAM policy that revokes access after 90 days

Answer

Use BigQuery scheduled queries to delete tables older than 90 days

Question 3

An application needs to store user profile data in a document database with flexible schema. The data is accessed frequently from a mobile app. Which Google Cloud database is BEST suited?

Accepted Answer

Cloud Firestore. Cloud Firestore is a NoSQL document database designed for mobile and web app development, offering flexible schema, real-time data synchronization, and automatic scaling. It directly supports frequent reads from mobile apps through its client SDKs and offline persistence, making it the best fit for storing user profile data with varying attributes.

Answer

Cloud Bigtable

Answer

BigQuery

Answer

Cloud Spanner

Question 4

A company wants to build a data lake on Cloud Storage for raw, curated, and processed data zones. They need to enforce data governance including column-level security and row-level filtering for BigQuery queries. Which solution should they use?

Accepted Answer

BigLake tables over Cloud Storage. BigLake tables provide a unified governance layer over Cloud Storage data, enabling fine-grained access control such as column-level security and row-level filtering directly on BigQuery queries. This is achieved by integrating BigQuery's access control policies with the external data stored in GCS, without needing to move data into BigQuery native storage. The other options either lack these granular security features or require complex workarounds.

Answer

BigQuery external tables reading from GCS

Answer

Dataproc with Spark SQL

Answer

Cloud Storage with IAM and VPC Service Controls

Question 5

A healthcare organization stores patient data in BigQuery. They need to encrypt a specific column (e.g., SSN) using a key they manage, and decrypt it only for authorized queries via a user-defined function. Which approach should they use?

Accepted Answer

Use BigQuery AEAD encryption functions with a Cloud KMS key. BigQuery AEAD encryption functions (e.g., `AEAD.ENCRYPT` and `AEAD.DECRYPT`) allow you to encrypt a specific column using a customer-managed key stored in Cloud KMS, and then decrypt it only within a user-defined function (UDF) that enforces access controls. This meets the requirement of per-column encryption with key management and authorized decryption via a UDF.

Answer

Use BigQuery column-level access controls

Answer

Use Cloud Key Management Service (Cloud KMS) with CMEK for the BigQuery dataset

Answer

Use Cloud Data Loss Prevention (DLP) to de-identify the column

Question 6

A company has a Cloud SQL for PostgreSQL instance that must be highly available across zones with automatic failover. They also need a read replica for reporting workloads. Which configuration should they use?

Accepted Answer

Enable high availability (regional) and create a read replica. Cloud SQL for PostgreSQL supports regional high availability (HA) with synchronous replication across two zones, ensuring automatic failover without data loss. Additionally, you can create a read replica in a different zone or region to offload reporting workloads without impacting the primary instance's performance. This combination meets both the high availability and read replica requirements.

Answer

Deploy Cloud SQL in multi-region mode

Answer

Enable automatic backups and point-in-time recovery

Answer

Create a cross-region replica and use it for failover

Question 7

A data engineer is designing a Cloud Bigtable schema for high-volume time-series data. Which TWO practices should they follow to avoid performance issues?

Accepted Answer

Use a hashed prefix in the row key to distribute writes. Option C is correct because Cloud Bigtable sorts rows lexicographically by row key, so monotonically increasing keys (like raw timestamps) concentrate writes on a single tablet, creating a hotspot; adding a hashed prefix distributes writes across multiple tablets and improves throughput. Option D is correct because grouping related columns into a small number of column families keeps data that is accessed together physically co-located, which improves read efficiency and avoids excessive per-row overhead. Option A is incorrect because placing the timestamp first produces sequential, monotonically increasing keys that cause write hotspots rather than distributing load. Option B is incorrect because Bigtable recommends keeping the number of column families small (typically fewer than 10), since each family adds memory and compaction overhead. Option E is incorrect because cramming all columns into one family prevents efficient access patterns and mixes unrelated data, hurting read performance and locality.

Answer

Place the timestamp as the first component of the row key

Answer

Create as many column families as possible

Answer

Store all columns in a single column family

Question 8

A data engineer wants to set up automatic deletion of objects from a Cloud Storage bucket after 30 days, and transition objects older than 7 days to Nearline storage. Which THREE steps should they take? (Select three.)

Accepted Answer

Create a lifecycle rule with action Delete and condition age 30 days. Option B is correct because a lifecycle rule with the Delete action and an age condition of 30 days will automatically remove objects once they reach 30 days old, satisfying the deletion requirement. Option C is correct because a lifecycle rule with the SetStorageClass action targeting Nearline and an age condition of 7 days transitions objects older than 7 days to Nearline storage, exactly matching the transition requirement. Option E is correct because lifecycle rules must be applied to the bucket by submitting the JSON configuration with the gsutil lifecycle set command (or equivalent API call); creating rules without applying them has no effect. Option A is not needed because changing the bucket's default storage class only affects newly uploaded objects and does not perform age-based transitions or deletions. Option D is not required because Object Versioning is unrelated to time-based deletion or storage-class transitions and would actually complicate deletion by retaining noncurrent versions.

Answer

Set the bucket's default storage class to Nearline

Answer

Enable Object Versioning on the bucket

Question 9

Which Google Cloud service is a fully managed relational database for MySQL, PostgreSQL, and SQL Server, offering automatic replication and backups?

Accepted Answer

Cloud SQL. Cloud SQL is the correct answer because it is Google Cloud's fully managed relational database service that supports MySQL, PostgreSQL, and SQL Server. It provides automatic replication across zones and automated backups, making it the ideal choice for traditional relational database workloads without the need for manual administration.

Answer

Cloud Spanner

Answer

AlloyDB

Answer

Bigtable

Question 10

A company uses Cloud Storage as a data lake with raw, curated, and processed zones. Data in the raw zone should be automatically moved to a cheaper storage class after 30 days, and deleted after 1 year. What is the most efficient way to implement this?

Accepted Answer

Use Object Lifecycle Management with rules to transition to Coldline after 30 days and delete after 365 days.. Object Lifecycle Management in Cloud Storage allows you to set rules based on object age. You can transition objects to a lower-cost storage class (e.g., Nearline or Coldline) after 30 days and delete after 365 days.

Answer

Write a Cloud Function that runs daily, checks object ages, and moves/deletes them.

Answer

Use Cloud Scheduler to run a script that changes storage class and deletes objects.

Answer

Set a retention policy on the raw zone to prevent deletion and manually clean up.

Question 11

You are designing a row key for Cloud Bigtable to store user activity logs. Each log entry has a timestamp (millisecond precision) and a user ID. There will be millions of writes per second from many users. To avoid hotspotting, which row key design is BEST?

Accepted Answer

hash(userID)#userID#timestamp_millis. Best because it uses a hash of the user ID as the row key prefix, which distributes writes across all Bigtable nodes and avoids hotspotting. Appending the user ID and timestamp ensures uniqueness and supports efficient queries for a specific user's logs. This design prevents the sequential timestamp from creating a single hot node, which is critical for handling millions of writes per second.

Answer

timestamp_millis#hash(userID)

Answer

timestamp_millis#userID

Answer

userID#timestamp_millis

Question 12

Which Google Cloud service is a serverless, highly scalable data warehouse for analytical queries, supporting SQL and integration with BI tools?

Accepted Answer

BigQuery. BigQuery is a serverless, highly scalable data warehouse designed for analytical queries over large datasets. It supports standard SQL and integrates seamlessly with BI tools like Looker and Tableau, making it the correct choice for this use case.

Answer

Firestore

Answer

Cloud SQL

Answer

Cloud Spanner

Question 13

A company wants to run hybrid transactional and analytical workloads on a PostgreSQL-compatible database with high performance. Which service should they choose?

Accepted Answer

AlloyDB. AlloyDB is the correct choice because it is a fully managed PostgreSQL-compatible database service specifically designed for high-performance hybrid transactional and analytical workloads. It combines transactional processing with built-in columnar analytics, delivering up to 4x faster transactional performance and up to 100x faster analytical queries than standard PostgreSQL, without requiring any schema changes or ETL.

Answer

Cloud Spanner

Answer

Cloud SQL for PostgreSQL

Answer

BigQuery

Question 14

You need to store and query a large dataset of customer profiles. The data is semi-structured and frequently updated. The application requires offline support for mobile users. Which database is MOST appropriate?

Accepted Answer

Firestore. Firestore is the most appropriate choice because it is a NoSQL document database designed for semi-structured data, real-time synchronization, and offline support. It provides built-in offline persistence for mobile clients, allowing users to read and write data even without network connectivity, and automatically syncs changes when the connection is restored. This directly meets the requirements of semi-structured data, frequent updates, and offline mobile support.

Answer

BigQuery

Answer

Cloud Bigtable

Answer

Cloud SQL

Question 15

Which Google Cloud database offers global distribution, strong consistency, and a 99.999% SLA?

Accepted Answer

Cloud Spanner. Cloud Spanner is the only Google Cloud database that provides global distribution (horizontally scaling across regions), strong consistency (external consistency with TrueTime), and a 99.999% SLA. It combines the benefits of relational database structure with non-relational horizontal scale, making it ideal for globally distributed, strongly consistent workloads.

Answer

Cloud Bigtable

Answer

Firestore

Answer

Cloud SQL