DEA-C01 Data Ingestion and Transformation Practice Test 12 — 15 Questions

Question 1

A company uses Amazon Kinesis Data Analytics for Apache Flink to process streaming data. The application reads from a Kinesis stream with 10 shards and writes to an S3 bucket. The application is experiencing high latency. Analysis shows that the application is not keeping up with the incoming data rate. Which action would MOST effectively reduce latency?

Accepted Answer

Increase the Parallelism of the Flink application. Increasing the parallelism of the Flink application allows it to process more data concurrently. This directly addresses the processing bottleneck.

Answer

Increase the number of shards in the Kinesis stream

Answer

Enable exactly-once delivery to S3

Answer

Use a larger Kinesis Data Analytics application (increase KPU)

Question 2

A company uses AWS Lake Formation to manage data lake permissions. A data engineer needs to grant an IAM role 'Read' access to a specific database and all its tables in the Data Catalog. What is the MOST efficient way to achieve this?

Accepted Answer

Grant 'Select' on the database and select 'Include' to apply to all tables. Lake Formation allows granting permissions on the database with 'Include' option to apply to all tables. This is the most efficient method for granting access to all tables.

Answer

Grant 'Super' permission on the Data Catalog

Answer

Add the IAM role to the Lake Formation administrators group

Answer

Grant 'Describe' on the database and 'Select' on each table individually

Question 3

A company uses AWS Glue ETL to transform data from Amazon RDS for MySQL to Amazon S3. The Glue job reads from a JDBC connection. The job runs once daily and processes all records, but the data volume is growing. Which change would improve performance and reduce costs?

Accepted Answer

Enable Glue job bookmarking and set the job to process only new data. Using incremental extraction with bookmarking allows Glue to process only new data instead of full scans, reducing time and cost.

Answer

Increase the number of DPUs for the Glue job

Answer

Switch to a Glue Python shell job

Answer

Use a higher JDBC fetch size

Question 4

Which TWO options are valid methods to ingest on-premises relational database data into Amazon S3 for analytics? (Choose 2.)

Accepted Answer

AWS Glue ETL job with JDBC connection to source. AWS DMS can continuously replicate data to S3. AWS Glue ETL can connect to JDBC sources and write to S3. Both are valid ingestion methods.

Answer

AWS Snowball Edge

Answer

Amazon Kinesis Data Streams with Direct Put

Answer

Amazon AppFlow

Question 5

Which THREE factors should be considered when choosing between Amazon Kinesis Data Streams and Amazon Kinesis Data Firehose for a streaming ingestion architecture? (Choose 3.)

Accepted Answer

Ability to deliver data directly to Amazon Redshift. KDS offers custom processing with shard-level control, while Firehose auto-scales and can deliver to S3, Redshift, etc. KDS requires consumer management; Firehose is managed.

Answer

Data retention period longer than 7 days

Answer

Lower cost per GB ingested

Question 6

Which TWO AWS services can be used to transform data in transit during ingestion? (Choose 2.)

Accepted Answer

Amazon Kinesis Data Firehose with Lambda transformation. AWS Glue ETL can transform data before writing to target. Kinesis Data Firehose can invoke Lambda for transformation. Both transform data in transit.

Answer

Amazon S3 Transfer Acceleration

Answer

Amazon Athena

Answer

AWS Data Pipeline

Question 7

A company uses Amazon Kinesis Data Streams to ingest clickstream data from a website. The data is then consumed by a custom application for real-time analytics. Recently, the application has been experiencing high latency. The operations team suspects the shard count is insufficient. How should the team increase the shard count of the existing stream?

Accepted Answer

Use the UpdateShardCount API to increase the shard count for the stream.. Option C is correct because you can use the UpdateShardCount API to increase shards. Option A is wrong because you cannot manually split shards; the API handles it. Option B is wrong because you cannot change shard count via PutRecord. Option D is wrong because you cannot delete and recreate a stream without data loss.

Answer

Delete the existing stream and create a new one with a higher shard count.

Answer

Manually split a shard using the SplitShard API on each existing shard.

Answer

Modify the PutRecord calls to include a new shard key that distributes data across more shards.

Question 8

A data engineer needs to ingest data from an on-premises Oracle database into Amazon S3 on a daily basis. The data volume is approximately 500 GB per day. The source database is behind a firewall that does not allow direct internet access. Which service should the engineer use to transfer the data securely?

Accepted Answer

AWS DataSync with a network path through AWS Direct Connect or VPN.. Option B is correct because AWS DataSync can transfer data from on-premises to S3, and it supports private network connectivity via AWS Direct Connect or VPN. Option A is wrong because AWS DMS is for ongoing replication, not bulk daily transfers. Option C is wrong because S3 Transfer Acceleration requires internet. Option D is wrong because Snowball Edge is for offline transfer, not daily.

Answer

AWS Database Migration Service (AWS DMS) with ongoing replication from Oracle to S3.

Answer

Amazon S3 Transfer Acceleration with a public endpoint.

Answer

AWS Snowball Edge device for daily transfers.

Question 9

A company uses AWS Glue to transform data stored in Amazon S3. During a run, the job fails with a 'OutOfMemoryError' in the Spark executor. The job processes 2 TB of parquet files using 10 DPUs. The data is evenly distributed across partitions. Which action would MOST likely resolve the issue without impacting the job logic?

Accepted Answer

Increase the number of DPUs allocated to the Glue job.. Option A is correct because increasing DPUs provides more memory and cores. Option B is wrong because repartitioning may not reduce memory per executor if total DPUs unchanged. Option C is wrong because compressing reduces input size, but Spark uses memory for processing, not just storage. Option D is wrong because increasing S3 request rate does not help with executor memory.

Answer

Enable S3 request rate increase to speed up data reading.

Answer

Repartition the data to a larger number of partitions.

Answer

Change the input format from Parquet to Snappy-compressed CSV.

Question 10

A company is designing a data ingestion pipeline for real-time IoT sensor data. The data volume peaks at 10,000 messages per second. The pipeline must process messages in order per sensor and persist raw data to Amazon S3 for archival. Which TWO services should be used together to meet these requirements? (Choose TWO.)

Accepted Answer

Amazon Kinesis Data Firehose. Options B and C are correct. Kinesis Data Streams captures data in order per shard (sensor), and Kinesis Data Firehose delivers to S3. Option A is wrong because SQS does not guarantee order per sensor. Option D is wrong because AppFlow is for SaaS integration. Option E is wrong because Lambda can process but not persist to S3 efficiently for archival.

Answer

AWS Lambda

Answer

Amazon AppFlow

Answer

Amazon Simple Queue Service (Amazon SQS)

Question 11

A data engineer is building a batch ETL pipeline using AWS Glue. The source data is in Amazon RDS for MySQL. The pipeline must run daily and process only new and modified records since the last run. The engineer needs to implement change data capture (CDC) efficiently. Which THREE steps should the engineer take? (Choose THREE.)

Accepted Answer

Configure the Glue job to use a JDBC connection with a SQL query that reads from the binary log.. Options A, C, and D are correct. Enable binary logging for CDC, use a bookmark to track processed records, and create a job bookmark in Glue. Option B is wrong because querying entire table daily is inefficient. Option E is wrong because Kinesis Data Streams is for real-time, not batch CDC.

Answer

Ingest the RDS data into Kinesis Data Streams and then use Glue.

Answer

Use a full table scan with a WHERE clause on a timestamp column.

Question 12

A company uses Amazon Kinesis Data Analytics for Apache Flink to process streaming data. The Flink application reads from a Kinesis Data Streams source, performs aggregations, and writes results to Amazon S3. The application is experiencing high checkpoint failures, and the processing lag is increasing. The data volume is 50 MB/s with an average record size of 1 KB. Which TWO actions would improve checkpoint reliability and reduce lag? (Choose TWO.)

Accepted Answer

Increase the checkpoint interval in the Flink configuration.. Options A and D are correct. Increase the checkpoint interval to reduce frequency, and increase parallelism with more KPUs. Option B is wrong because reducing parallelism would worsen lag. Option C is wrong because decreasing checkpoint interval increases failures. Option E is wrong because Kinesis Data Firehose is not a direct solution to checkpoint failures.

Answer

Decrease the checkpoint interval to complete checkpoints faster.

Answer

Replace the S3 sink with Kinesis Data Firehose.

Answer

Decrease the parallelism of the Flink application.

Question 13

Refer to the exhibit. A data engineer is attaching this IAM policy to an IAM role used by an AWS Glue job. The job reads from a Kinesis Data Streams stream and writes transformed data to an S3 bucket. When the job runs, it fails with an AccessDenied error for the Kinesis stream. What is the MOST likely cause?

Accepted Answer

The IAM policy is missing the 'kinesis:DescribeStream' action.. Option B is correct because missing 'kinesis:DescribeStream' is required for Glue to read from the stream. Option A is wrong because the S3 policy is fine. Option C is wrong because resource ARN is correctly formatted. Option D is wrong because the policy does not allow 'kinesis:GetRecords' or 'kinesis:DescribeStream'.

Answer

The stream ARN in the policy is incorrect.

Answer

The Glue job does not have permissions to call 'kinesis:PutRecord'.

Answer

The S3 bucket policy blocks the PutObject action from the Glue role.

Question 14

Refer to the exhibit. A data engineer runs the describe-stream command on a Kinesis data stream. The stream has two shards. The engineer wants to increase the shard count to 4 using the UpdateShardCount API. What will be the resulting shard distribution?

Accepted Answer

Four shards with hash ranges: 0-5.67e37, 5.67e37-1.13e38, 1.13e38-1.70e38, 1.70e38-2.27e38.. Option D is correct because UpdateShardCount splits shards evenly: each existing shard splits into two, resulting in 4 shards with uniform hash ranges. Option A is wrong because it creates uneven ranges. Option B is wrong because the parent shards are not retained. Option C is wrong because the hash range of each new shard is exactly half of the original shard's range.

Answer

Four shards with hash ranges: 0-5.68e37, 5.68e37-1.13e38, 1.13e38-1.70e38, 1.70e38-2.27e38.

Answer

Two new shards are created with overlapping hash ranges, and the original two shards remain as parents.

Answer

Four shards with hash ranges: 0-5.67e37, 5.67e37-1.13e38, 1.13e38-1.70e38, 1.70e38-2.27e38.

Question 15

Refer to the exhibit. A company uses S3 Event Notifications to trigger an AWS Lambda function whenever a new object is uploaded to an S3 bucket. The Lambda function processes the file and moves it to a different bucket. Recently, the function has been failing intermittently. The engineer checks the Lambda CloudWatch logs and sees the above event. What is the MOST likely cause of the intermittent failures?

Accepted Answer

The S3 event notifications are not guaranteed to be delivered exactly once, causing duplicate processing.. Option C is correct because S3 Event Notifications are asynchronous and may be duplicated or delivered out of order, causing race conditions. Option A is wrong because the event has all required fields. Option B is wrong because the bucket name is valid. Option D is wrong because the event format is correct.

Answer

The event JSON is malformed; the 'EventSource' should be 's3.amazonaws.com'.

Answer

The S3 bucket name contains a hyphen, which is not allowed.

Answer

The event is missing the 'object:versionId' field.