Amazon DBS-C01 Online Practice Questions and Exam Preparation

Amazon DBS-C01 Online Questions & Answers

• Question 311:

  A database professional is tasked with the task of migrating 25 GB of data files from an on- premises storage system to an Amazon Neptune database.

  Which method of data loading is the FASTEST?

  A. Upload the data to Amazon S3 and use the Loader command to load the data from Amazon S3 into the Neptune database.
  B. Write a utility to read the data from the on-premises storage and run INSERT statements in a loop to load the data into the Neptune database.
  C. Use the AWS CLI to load the data directly from the on-premises storage into the Neptune database.
  D. Use AWS DataSync to load the data directly from the on-premises storage into the Neptune database.
  A. Upload the data to Amazon S3 and use the Loader command to load the data from Amazon S3 into the Neptune database.

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  Explanation/Reference:

  1.Copy the data files to an Amazon Simple Storage Service (Amazon S3) bucket.

  2.

  Create an IAM role with Read and List access to the bucket.

  3.

  Create an Amazon S3 VPC endpoint.

  4.

  Start the Neptune loader by sending a request via HTTP to the Neptune DB instance.

  5.

  The Neptune DB instance assumes the IAM role to load the data from the bucket.

• Question 312:

  A company uses an Amazon RDS for PostgreSQL database in the us-east-2 Region. The company wants to have a copy of the database available in the us-west-2 Region as part of a new disaster recovery strategy.

  A database architect needs to create the new database. There can be little to no downtime to the source database. The database architect has decided to use AWS Database Migration Service (AWS DMS) to replicate the database across Regions. The database architect will use full load mode and then will switch to change data capture (CDC) mode.

  Which parameters must the database architect configure to support CDC mode for the RDS for PostgreSQL database? (Choose three.)

  A. Set wal_level = logical.
  B. Set wal_level = replica.
  C. Set max_replication_slots to 1 or more, depending on the number of DMS tasks.
  D. Set max_replication_slots to 0 to support dynamic allocation of slots.
  E. Set wal_sender_timeout to 20,000 milliseconds.
  F. Set wal_sender_timeout to 5,000 milliseconds.
  A. Set wal_level = logical.
  C. Set max_replication_slots to 1 or more, depending on the number of DMS tasks.
  E. Set wal_sender_timeout to 20,000 milliseconds.

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  Explanation/Reference:

  Correct Answer: A, C, E from Amazon documents: To enable CDC mode for RDS for PostgreSQL database, the database architect needs to configure the following parameters12: Set wal_level = logical. This parameter determines how much information is written to the write-ahead log (WAL). For CDC mode, the wal_level must be set to logical, which enables logical decoding of the WAL and allows AWS DMS to read changes from the source database1. Set max_replication_slots to 1 or more, depending on the number of DMS tasks. This parameter specifies the maximum number of replication slots that the source database can support. A replication slot is a data structure that records the state of a replication stream. AWS DMS uses replication slots to set up logical replication and track changes in the source database. The max_replication_slots parameter must be equal to or greater than the number of DMS tasks that use CDC mode for the source database1. Set wal_sender_timeout to 20,000 milliseconds. This parameter specifies the amount of time that a WAL sender process waits for feedback from a WAL receiver process before terminating the connection. A WAL sender process is a background process that streams WAL data from the source database to AWS DMS. A WAL receiver process is a background process that receives WAL data from a WAL sender process and writes it to a local file. The wal_sender_timeout

  parameter must be set to a value greater than 10,000 milliseconds (10 seconds) to prevent connection timeouts during CDC mode2.

  Therefore, option A, C, and E are the correct parameters to support CDC mode for RDS for PostgreSQL database. Option B is incorrect because wal_level = replica is not sufficient for logical decoding and CDC mode. Option D is incorrect

  because max_replication_slots must be a positive integer, not zero. Option F is incorrect because wal_sender_timeout = 5,000 milliseconds is too low and may cause connection timeouts during CDC mode.

• Question 313:

  An online retailer uses Amazon DynamoDB for its product catalog and order data. Some popular items have led to frequently accessed keys in the data, and the company is using DynamoDB Accelerator (DAX) as the caching solution to cater to the frequently accessed keys. As the number of popular products is growing, the company realizes that more items need to be cached. The company observes a high cache miss rate and needs a solution to address this issue.

  What should a database specialist do to accommodate the changing requirements for DAX?

  A. Increase the number of nodes in the existing DAX cluster.
  B. Create a new DAX cluster with more nodes. Change the DAX endpoint in the application to point to the new cluster.
  C. Create a new DAX cluster using a larger node type. Change the DAX endpoint in the application to point to the new cluster.
  D. Modify the node type in the existing DAX cluster.
  C. Create a new DAX cluster using a larger node type. Change the DAX endpoint in the application to point to the new cluster.

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  Explanation/Reference:

  Correct Answer: C. Create a new DAX cluster using a larger node type. Change the DAX endpoint in the application to point to the new cluster. from Amazon documents: The cache miss rate is the percentage of read requests that are not satisfied by the DAX cache and have to be forwarded to DynamoDB1. A high cache miss rate indicates that the DAX cluster does not have enough memory to store all the frequently accessed items. Increasing the number of nodes in the existing DAX cluster (option A) or creating a new DAX cluster with more nodes (option B) will not increase the total memory available for caching, because DAX uses a partitioned cache model, where each node is responsible for caching a subset of the data2. Modifying the node type in the existing DAX cluster (option D) will cause downtime and data loss, because DAX does not support online resizing of clusters3. Therefore, the best option is to create a new DAX cluster using a larger node type (option C), which will provide more memory per node and allow more items to be cached. The application will need to change the DAX endpoint to point to the new cluster, which can be done with minimal disruption by using DNS aliasing or load balancing3.

• Question 314:

  Amazon Aurora MySQL is being used by an ecommerce business to migrate its main application database. The firm is now doing OLTP stress testing using concurrent database connections. A database professional detected sluggish performance for several particular write operations during the first round of testing.

  Examining the Amazon CloudWatch stats for the Aurora DB cluster revealed a CPU usage of 90%.

  Which actions should the database professional take to determine the main cause of excessive CPU use and sluggish performance most effectively? (Select two.)

  A. Enable Enhanced Monitoring at less than 30 seconds of granularity to review the operating system metrics before the next round of tests.
  B. Review the VolumeBytesUsed metric in CloudWatch to see if there is a spike in write I/O.
  C. Review Amazon RDS Performance Insights to identify the top SQL statements and wait events.
  D. Review Amazon RDS API calls in AWS CloudTrail to identify long-running queries.
  E. Enable Advance Auditing to log QUERY events in Amazon CloudWatch before the next round of tests.
  A. Enable Enhanced Monitoring at less than 30 seconds of granularity to review the operating system metrics before the next round of tests.
  C. Review Amazon RDS Performance Insights to identify the top SQL statements and wait events.

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  Explanation/Reference:

  https://aws.amazon.com/premiumsupport/knowledge-center/rds-instance- high-cpu/ https://aws.amazon.com/premiumsupport/knowledge-center/rds-mysql-slow-query/

• Question 315:

  A pharmaceutical company uses Amazon Quantum Ledger Database (Amazon QLDB) to store its clinical trial data records. The company has an application that runs as AWS Lambda functions. The application is hosted in the private subnet in a VPC.

  The application does not have internet access and needs to read some of the clinical data records. The company is concerned that traffic between the QLDB ledger and the VPC could leave the AWS network. The company needs to secure access to the QLDB ledger and allow the VPC traffic to have read-only access.

  Which security strategy should a database specialist implement to meet these requirements?

  A. Move the QLDB ledger into a private database subnet inside the VPC. Run the Lambda functions inside the same VPC in an application private subnet. Ensure that the VPC route table allows read-only flow from the application subnet to the database subnet.
  B. Create an AWS PrivateLink VPC endpoint for the QLDB ledger. Attach a VPC policy to the VPC endpoint to allow read-only traffic for the Lambda functions that run inside the VPC.
  C. Add a security group to the QLDB ledger to allow access from the private subnets inside the VPC where the Lambda functions that access the QLDB ledger are running.
  D. Create a VPN connection to ensure pairing of the private subnet where the Lambda functions are running with the private subnet where the QLDB ledger is deployed.
  B. Create an AWS PrivateLink VPC endpoint for the QLDB ledger. Attach a VPC policy to the VPC endpoint to allow read-only traffic for the Lambda functions that run inside the VPC.

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  Explanation/Reference:

  https://docs.aws.amazon.com/qldb/latest/developerguide/vpc-endpoints.html

• Question 316:

  Amazon DynamoDB global tables are being used by a business to power an online gaming game. The game is played by gamers from all around the globe. As the game became popularity, the amount of queries to DynamoDB substantially rose. Recently, gamers have complained about the game's condition being inconsistent between nations. A database professional notices that the ReplicationLatency metric for many replica tables is set to an abnormally high value.

  Which strategy will resolve the issue?

  A. Configure all replica tables to use DynamoDB auto scaling.
  B. Configure a DynamoDB Accelerator (DAX) cluster on each of the replicas.
  C. Configure the primary table to use DynamoDB auto scaling and the replica tables to use manually provisioned capacity.
  D. Configure the table-level write throughput limit service quota to a higher value.
  A. Configure all replica tables to use DynamoDB auto scaling.

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  Explanation/Reference:

  https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/V2globaltables_req s_bestpractices.html

• Question 317:

  A company is using a Single-AZ Amazon RDS for MySQL DB instance for development. The DB instance is experiencing slow performance when queries are executed. Amazon CloudWatch metrics indicate that the instance requires more I/ O capacity.

  Which actions can a database specialist perform to resolve this issue? (Choose two.)

  A. Restart the application tool used to execute queries.
  B. Change to a database instance class with higher throughput.
  C. Convert from Single-AZ to Multi-AZ.
  D. Increase the I/O parameter in Amazon RDS Enhanced Monitoring.
  E. Convert from General Purpose to Provisioned IOPS (PIOPS).
  B. Change to a database instance class with higher throughput.
  E. Convert from General Purpose to Provisioned IOPS (PIOPS).

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  Explanation/Reference:

  https://aws.amazon.com/blogs/database/best-storage-practices-for-running- production-workloads-on-hosted-databases-with-amazon-rds-or-amazon-ec2/ "If you find the pattern of IOPS usage consistently going beyond more than 16,000, you should modify the DB instance and change the storage type from gp2 to io1.

• Question 318:

  An online advertising website uses an Amazon DynamoDB table with on-demand capacity mode as its data store. The website also has a DynamoDB Accelerator (DAX) cluster in the same VPC as its web application server. The application needs to perform infrequent writes and many strongly consistent reads from the data store by querying the DAX cluster.

  During a performance audit, a systems administrator notices that the application can look up items by using the DAX cluster. However, the QueryCacheHits metric for the DAX cluster consistently shows 0 while the QueryCacheMisses metric continuously keeps growing in Amazon CloudWatch. What is the MOST likely reason for this occurrence?

  A. A VPC endpoint was not added to access DynamoDB.
  B. Strongly consistent reads are always passed through DAX to DynamoDB.
  C. DynamoDB is scaling due to a burst in traffic, resulting in degraded performance.
  D. A VPC endpoint was not added to access CloudWatch.
  B. Strongly consistent reads are always passed through DAX to DynamoDB.

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  Explanation/Reference:

  https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/DAX.concepts.html

  "If the request specifies strongly consistent reads, DAX passes the request through to DynamoDB. The results from DynamoDB are not cached in DAX. Instead, they are simply returned to the application."

• Question 319:

  A financial company is hosting its web application on AWS. The application's database is hosted on Amazon RDS for MySQL with automated backups enabled.

  The application has caused a logical corruption of the database, which is causing the application to become unresponsive. The specific time of the corruption has been identified, and it was within the backup retention period.

  How should a database specialist recover the database to the most recent point before corruption?

  A. Use the point-in-time restore capability to restore the DB instance to the specified time. No changes to the application connection string are required.
  B. Use the point-in-time restore capability to restore the DB instance to the specified time. Change the application connection string to the new, restored DB instance.
  C. Restore using the latest automated backup. Change the application connection string to the new, restored DB instance.
  D. Restore using the appropriate automated backup. No changes to the application connection string are required.
  B. Use the point-in-time restore capability to restore the DB instance to the specified time. Change the application connection string to the new, restored DB instance.

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  Explanation/Reference:

  The point-in-time restore capability of Amazon RDS for MySQL allows you to create a new DB instance with the same configuration as the original one, but with data restored to a specific time within your backup retention period. You can specify any time within your backup retention period, up to the last five minutes of your DB instance's usage1. This feature is useful for recovering from logical corruption or user errors that affect your database. However, when you use the point-in-time restore capability, you are creating a new DB instance with a different endpoint. Therefore, you need to change the application connection string to point to the new, restored DB instance. You can also delete or rename the original DB instance if you no longer need it1

• Question 320:

  A news portal is looking for a data store to store 120 GB of metadata about its posts and comments. The posts and comments are not frequently looked up or updated. However, occasional lookups are expected to be served with single-digit millisecond latency on average.

  What is the MOST cost-effective solution?

  A. Use Amazon DynamoDB with on-demand capacity mode. Purchase reserved capacity.
  B. Use Amazon ElastiCache for Redis for data storage. Turn off cluster mode.
  C. Use Amazon S3 Standard-Infrequent Access (S3 Standard-IA) for data storage and use Amazon Athena to query the data.
  D. Use Amazon DynamoDB with on-demand capacity mode. Switch the table class to DynamoDB Standard-Infrequent Access (DynamoDB Standard-IA).
  C. Use Amazon S3 Standard-Infrequent Access (S3 Standard-IA) for data storage and use Amazon Athena to query the data.

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  Explanation/Reference:

  Correct Answer: C from Amazon documents: Amazon S3 Standard-Infrequent Access (S3 Standard-IA) is a storage class for data that is accessed less frequently, but requires rapid access when needed. S3 Standard-IA offers the high durability, throughput, and low latency of S3 Standard, with a low per GB storage price and per GB retrieval fee1. S3 Standard-IA is designed for long-lived and infrequently accessed data. Examples include disaster recovery, backups, and long-term data retention1. Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run2. Athena scales automatically--executing queries in parallel--so results are fast, even with large datasets and complex queries2. The news portal can use S3 Standard-IA to store its metadata about posts and comments, which are not frequently looked up or updated. This way, the portal can benefit from the low storage cost of S3 Standard-IA ($0.0125 per GB per month) and the high durability and availability of S31. The portal can also use Athena to query the data stored in S3 using SQL, without having to set up any servers or databases. The portal only pays for the amount of data scanned by each query ($5 per TB scanned) and can optimize the query cost by partitioning, compressing, and converting the data into columnar formats2. Therefore, option C is the most cost-effective solution for the news portal's use case. Option A is not cost-effective because DynamoDB on-demand capacity mode charges for read and write requests ($1.25 per million read requests and $1.25 per million write requests), regardless of how frequently the data is accessed3. Purchasing reserved capacity can reduce the cost, but it requires a minimum commitment of 100 units per region. Option B is not suitable because ElastiCache for Redis is an in-memory data store that provides sub-millisecond latency, but it is more expensive than S3 Standard-IA ($0.046 per GB per hour for cache.t2.micro node type). ElastiCache for Redis is also not designed for long-term data storage, but for caching frequently accessed data. Option D is not available because DynamoDB Standard-Infrequent Access (DynamoDB Standard-IA) is not a valid table class for DynamoDB. The only table classes for DynamoDB are On-Demand and Provisioned.