Data Operations and Support

A data engineer notices that an AWS Glue job processing data from an Amazon S3 bucket frequently fails with 'OutOfMemoryError'. The job reads CSV files, applies transformations, and writes Parquet to another S3 bucket. The job has 10 workers of type G.1X. Which change is MOST likely to resolve the issue?

A company uses Amazon Kinesis Data Streams to ingest clickstream data. The data is consumed by a custom consumer application that writes to Amazon S3 every 5 minutes. The consumer is falling behind and processing lag is increasing. Which action is MOST effective to reduce the lag?

A data team runs a daily AWS Glue ETL job that processes data from an Amazon Redshift cluster and writes results to Amazon S3. The job completes successfully but takes 2 hours longer than expected. The job uses the JDBC connection to Redshift. The Redshift cluster is 4 dc2.large nodes. The Glue job has 10 workers of type G.1X. Which change would MOST likely reduce the job duration?

A company uses Amazon DynamoDB as a source for an AWS Glue job. The job reads a large table using a DynamoDB export to S3 feature. The job is failing with 'ThrottlingException' from DynamoDB. What should the data engineer do to resolve this issue WITHOUT changing the job's logic?

A data engineer is monitoring an Amazon Kinesis Data Analytics application that uses a SQL query to aggregate streaming data. The application is falling behind and the millisBehindLatest metric is increasing. Which action should the engineer take to improve performance?

A data engineer is troubleshooting an AWS Glue job that reads from an Amazon RDS for PostgreSQL database using a JDBC connection. The job fails with the error 'java.sql.SQLException: No suitable driver'. Which TWO actions should the engineer take to resolve this issue? (Select TWO.)

A company uses Amazon S3 to store raw data and runs AWS Glue ETL jobs to transform it into Parquet. The data is then queried using Amazon Athena. Queries are slow and expensive due to high scan volumes. Which THREE design changes can improve query performance and reduce costs? (Select THREE.)

A data engineer runs a Spark job on Amazon EMR that reads data from Amazon S3 and writes results back to S3. The job fails with an 'S3AccessDenied' error. The engineer verifies that the IAM role attached to the EMR cluster has s3:GetObject and s3:PutObject permissions on the relevant buckets. What is the MOST likely cause of the error?

An AWS Glue job that processes streaming data from Amazon Kinesis Data Streams is failing intermittently with 'Failed to checkpoint' errors. The job uses checkpointing to an Amazon S3 bucket every 60 seconds. Which action should the engineer take to resolve the issue?

A company uses AWS DMS to migrate data from an on-premises Oracle database to Amazon Redshift. The migration is successful, but after a few days, data in Redshift becomes inconsistent with the source due to ongoing changes. The company needs to keep Redshift synchronized with minimal latency. Which approach should the data engineer use?

A data engineer notices that an Amazon Kinesis Data Firehose delivery stream is failing to deliver data to an Amazon S3 bucket. The CloudWatch metrics show 'DeliveryToS3.Success' is 0 and 'S3.BucketExists' is 1. What is the MOST likely cause?

A company runs a batch ETL job on Amazon EMR every night. Recently, the job started failing with 'Out of Memory' errors in the Spark executors. The data volume has grown 20% in the past month. The cluster uses uniform instance groups with 5 core nodes of r5.xlarge (4 vCPU, 32 GB RAM). Which change should the data engineer implement to resolve the issue with minimal cost increase?

A data engineer is troubleshooting an AWS Glue ETL job that fails with the error: 'An error occurred while calling o123.pyWriteDynamicFrame. Access Denied when writing to S3 bucket: my-bucket'. The job uses a Glue service role named 'GlueServiceRole'. Which TWO actions should the engineer take to resolve the issue? (Choose TWO.)

A data engineer is monitoring an Amazon Kinesis Data Analytics for Apache Flink application that processes streaming data. The application is falling behind (increasing 'MillisBehindLatest') and the CPU utilization of the Flink task managers is consistently above 80%. Which THREE actions should the engineer take to improve performance? (Choose THREE.)

A data engineer is troubleshooting a nightly AWS Glue ETL job that reads from an Amazon RDS for MySQL table and writes to an Amazon S3 bucket in Parquet format. The job runs successfully most days, but occasionally fails with the error 'ERROR: An error occurred while calling o67.pyWriteDynamicFrame. The transaction log for the database is full due to 'LOG_BACKUP'.' What is the MOST likely cause of this error?

A company runs a data pipeline that ingests clickstream data from a web application into Amazon Kinesis Data Streams. A Lambda function processes records from the stream and writes them to an Amazon S3 bucket in JSON format. The pipeline has been running smoothly, but for the past hour, the Lambda function has been failing with 'Rate exceeded' errors, and the Kinesis stream shows elevated 'IteratorAgeMilliseconds' metrics. The Lambda function has a reserved concurrency of 100, and the Kinesis stream has 10 shards. The average record size is 5 KB, and the data rate is approximately 15 MB per second. Which combination of actions should a data engineer take to resolve the issue and prevent recurrence? (Choose TWO.)

A company uses AWS Glue to run ETL jobs that process data from Amazon S3 and write results to Amazon Redshift. The Glue job uses the JDBC connection to Redshift. Recently, the job has been failing intermittently with the error: 'java.sql.SQLException: [Amazon](500310) Invalid operation: INSERT has more expressions than target columns;' The Glue job writes to a staging table in Redshift before performing a merge into the final table. The staging table schema matches the source data. The error occurs only on some days and affects different columns each time. The data engineer suspects that the source data occasionally contains extra columns due to a schema drift in the upstream data producer. Which approach should the data engineer take to handle this issue robustly?

A data engineer is troubleshooting a Glue ETL job that reads from an S3 bucket and writes to a Redshift table. The job fails with a 'MemoryError' when processing a large dataset. Which TWO actions should the engineer take to resolve this issue? (Choose TWO.)

A data engineer applies the above S3 bucket policy to an S3 bucket used by a Glue ETL job. The Glue job writes objects to the bucket. Which of the following is true about the behavior of the policy?

A company runs a nightly batch processing pipeline using AWS Glue ETL jobs. The pipeline reads data from an Amazon S3 bucket, transforms it, and writes results to an Amazon Redshift cluster. Recently, the data volume has increased significantly, and some Glue jobs are failing with the error 'java.lang.OutOfMemoryError: Java heap space'. The data engineer needs to modify the job configuration to prevent these failures without changing the code. The job currently uses 10 DPUs and processes data in a single Spark DataFrame. Which of the following is the MOST effective solution?

Order the steps to set up a Kinesis Data Analytics application for real-time stream processing.

Arrange the steps to set up a streaming ETL pipeline using Amazon Kinesis Data Firehose to Amazon S3.

Match each AWS data compression format to its typical use case.

Match each AWS data analytics service to its primary function.

A data engineer notices that a nightly AWS Glue ETL job has been failing for the past three days with the error 'Unable to locate credentials'. The job uses an IAM role for execution. What is the most likely cause of this error?

A company runs a data pipeline using AWS Lambda to process records from an Amazon Kinesis Data Stream. Recently, the Lambda function has been experiencing high invocation errors and the stream is throttling. The function performs simple transformations and writes to Amazon S3. What is the most effective way to reduce throttling and errors?

A data engineer is troubleshooting a slow Amazon Redshift query that joins a large fact table with several dimension tables. The EXPLAIN plan shows a hash join on the distribution key, but the query still runs slowly. The fact table is distributed by KEY(column_x) and the dimension tables are distributed ALL. The engineer notices that the fact table has a high number of rows with the same value in column_x. What is the most likely cause of the slow performance?

A company uses Amazon S3 to store large CSV files and runs Amazon Athena queries on them. The queries are becoming slower as data grows. A data engineer suggests converting the files to Apache Parquet format and partitioning the data. What is the primary benefit of converting to Parquet?

A data engineer is running an AWS Glue ETL job that reads from an Amazon RDS MySQL database and writes to Amazon S3. The job fails with a 'Communications link failure' error. The security group for the RDS instance allows inbound traffic from the Glue job's security group. What is the most likely cause of the failure?

A company runs a critical data pipeline using Amazon Kinesis Data Firehose to deliver data to Amazon S3. The data is compressed with GZIP and partitioned by year/month/day/hour. Recently, the delivery to S3 has been failing with 'Rate exceeded' errors. The Firehose delivery stream has a buffer size of 128 MB and buffer interval of 60 seconds. What is the most effective way to resolve this issue?

A data engineer is monitoring an Amazon EMR cluster running a Spark job. The job is processing a large dataset and the engineer notices that the cluster is using a high percentage of disk space on the core nodes. The job fails with 'No space left on device' error. What is the most effective way to resolve this issue without modifying the job logic?

A company uses Amazon CloudWatch Logs to collect application logs from EC2 instances. The logs are exported to Amazon S3 for long-term storage. Recently, the export task failed with the error 'Access Denied'. What is the most likely cause of this failure?

A data engineer is troubleshooting an AWS Glue crawler that is not correctly inferring the schema of CSV files stored in Amazon S3. The files have headers, but the crawler is treating the header row as data. The crawler is configured with a custom classifier that has a CSV classifier with 'Column header' set to 'Use first row as header'. What is the most likely reason the crawler is not recognizing the header?

A company is using Amazon DynamoDB as a data store for a real-time application. The application reads a single item by primary key and occasionally updates it. The data engineer notices high read latency during peak hours. Which TWO actions would most effectively reduce read latency?

A data engineer is designing a data lake on Amazon S3. The data is ingested from multiple sources and must be queryable using Amazon Athena. The engineer needs to optimize query performance and reduce costs. Which THREE actions would achieve this?

A company is using AWS Glue ETL jobs to process data from Amazon S3 and write results back to S3. The jobs are failing intermittently with 'ThrottlingException' errors. Which TWO configurations would help reduce these errors?

A data engineer is troubleshooting a nightly ETL job that reads data from an RDS MySQL instance and writes to an S3 bucket in Parquet format. The job runs on an EMR cluster and uses PySpark. Recently, the job started failing with 'OutOfMemoryError' in the executor logs. The data volume has grown 30% in the last month. Which is the MOST efficient solution to resolve this issue without changing the code?

A data engineer receives an alert that a Kinesis Data Stream has a 'WriteProvisionedThroughputExceeded' error. The stream has 5 shards with 1 MB/s write capacity per shard. The producer application is sending data at 8 MB/s sustained. What should the engineer do to resolve the issue?

A company ingests IoT sensor data into an S3 bucket. Daily, a Lambda function reads new objects, processes them, and writes results to a DynamoDB table. Recently, the Lambda function started timing out after 15 minutes. The data volume has increased, and the function processes records one by one. Which solution would improve performance without significant cost increase?

A data engineer is monitoring a Redshift cluster that is experiencing slow query performance. The cluster has 4 dc2.large nodes. The engineer notices that disk space usage is at 85% across all nodes. Which action would MOST likely improve query performance?

A data engineer is tasked with setting up a data pipeline that moves data from an on-premises Oracle database to Amazon S3 every hour. The network bandwidth is limited, and the engineer needs to ensure data consistency. Which AWS service should the engineer use?

A company uses a DynamoDB table with on-demand capacity for a gaming application. During a new game launch, the table experienced throttling errors. The engineer checks CloudWatch metrics and sees that the 'ConsumedWriteCapacityUnits' exceeded the 'ProvisionedWriteCapacityUnits' (on-demand uses the table's previous peak). The application is writing at 50,000 WCU but the table's peak was 30,000 WCU. What should the engineer do to resolve throttling?

A data engineer is monitoring an AWS Glue ETL job that processes data from an S3 bucket and writes to a Redshift table. The job completes successfully but takes longer than expected. The engineer notices that the job uses 10 DPUs and the data size is 500 GB. The job runs in standard mode. Which change would MOST reduce job duration?

A data engineer needs to ensure that a Redshift cluster can recover from a failure with minimal data loss. The cluster is used for reporting and can tolerate a few minutes of downtime. Which feature should the engineer enable?

A data engineer is troubleshooting a Kinesis Data Analytics application that processes streaming data. The application is falling behind and has a high 'MillisBehindLatest' metric. The application uses a parallelism of 2. The source stream has 4 shards. What is the MOST likely cause and solution?

A data engineer is designing a data lake on Amazon S3 with sensitive data. The engineer needs to ensure that data at rest is encrypted and that access is logged for compliance. Which TWO actions should the engineer take? (Choose TWO.)

A data engineer is migrating a legacy data warehouse to Amazon Redshift. The engineer needs to load data from multiple sources efficiently. Which THREE services can be used to load data into Redshift? (Choose THREE.)

A company runs a data processing pipeline on Amazon EMR. The pipeline reads data from S3, processes it with Spark, and writes results back to S3. The engineer notices that the cluster is underutilized and wants to reduce costs. Which TWO actions should the engineer take? (Choose TWO.)

A data engineer is troubleshooting a failed AWS Glue ETL job. The job reads from an S3 bucket and writes to an RDS MySQL database. The job fails with an 'Access Denied' error when trying to write to RDS. What is the most likely cause?

A company uses Kinesis Data Streams to ingest real-time clickstream data. The data is processed by a Lambda function that writes to an S3 bucket. Recently, the Lambda function has been failing with 'ProvisionedThroughputExceededException' errors. Which action should be taken to resolve this issue?

A data engineer is monitoring an Amazon Redshift cluster and notices that queries are taking longer than expected. The engineer checks the system tables and sees that many queries are waiting for 'WLM' resources. What is the most likely cause and recommended fix?

A data pipeline using AWS Glue ETL jobs is failing intermittently with the error 'Rate exceeded' when writing to an Amazon Redshift cluster. Which action is MOST effective to resolve this issue?

A company is using Amazon S3 as a data lake. Data is ingested hourly from multiple sources. The data engineer needs to ensure that once an object is written to S3, it cannot be overwritten or deleted for 30 days. Which S3 feature should be used?

A data engineer is running a Spark job on Amazon EMR. The job reads from S3, processes data, and writes to S3. The job is taking longer than expected. The engineer notices that the job is spending a lot of time in the 'GC' (garbage collection) phase. Which configuration change is most likely to improve performance?

A team manages an Amazon DynamoDB table with on-demand capacity. Recently, they noticed increased throttling errors during peak hours. The table has a Lambda trigger that processes changes and writes to an S3 bucket. Which design change would BEST reduce throttling?

A company uses AWS Database Migration Service (DMS) to migrate an on-premises Oracle database to Amazon RDS for PostgreSQL. The migration completes successfully, but the data engineer notices that some tables have fewer rows in the target than the source. Which DMS setting should be checked to ensure full data migration?

A data engineer needs to transfer 50 TB of data from an on-premises HDFS cluster to Amazon S3. The on-premises network has a 1 Gbps link to AWS. Which AWS service should be used to perform the transfer efficiently?

A data engineer needs to transfer 10 TB of data from an on-premises data center to Amazon S3. The network bandwidth is limited to 100 Mbps, and the data transfer must be completed within 5 days. What is the most cost-effective solution?

An Amazon Kinesis Data Streams application is lagging behind. The data records are small (1 KB) and the shard count is 10. The consumer uses the KCL with default configuration. Which action will MOST effectively reduce the consumer lag?

A company is using Amazon Athena to query data stored in S3. Queries are failing with 'HIVE_INVALID_PARTITION' errors. What is the most likely cause?

A company runs a nightly Amazon EMR job that processes data from S3 and writes results back to S3. The job fails with 'OutOfMemoryError' in the reduce phase. The cluster currently uses 5 m5.xlarge instances. Which cost-effective change should the data engineer make?

A data engineer is using Amazon Kinesis Data Firehose to deliver streaming data to an S3 bucket. The data is delivered in 5-minute intervals. However, the engineer notices that the data in S3 is often delayed by up to 30 minutes. Which configuration change would most likely reduce the delay?

A data engineer notices that an Amazon RDS for PostgreSQL instance's CPU utilization is consistently above 90% during business hours. The database is used for reporting queries. Which action should be taken FIRST to improve performance?

A data engineer is monitoring an Amazon RDS for PostgreSQL instance. The engineer wants to set up alerts for high CPU utilization and low free storage space. Which AWS services can be used together to achieve this? (Choose TWO.)

A company uses AWS Lake Formation to manage data lake permissions. A data analyst cannot query a table in Athena, although the table appears in the catalog. The analyst has IAM permissions to run Athena. What is the MOST likely cause?

A company is running a critical data pipeline using AWS Glue. The pipeline must be highly available and fault-tolerant. Which TWO strategies should the data engineer implement? (Choose TWO.)

A data pipeline uses AWS Step Functions to orchestrate multiple Lambda functions for data transformation. The pipeline occasionally fails with a 'StateMachineExecutionLimitExceeded' error. What is the MOST likely cause?

A data engineer is designing an Amazon Redshift data warehouse for a high-traffic analytics workload. The engineer needs to ensure fast query performance and minimize data movement. Which THREE design decisions should be made? (Choose THREE.)

A data engineer needs to monitor the number of Amazon S3 PUT requests that result in a 403 AccessDenied error. Which CloudWatch metric and dimension should be used?

Refer to the exhibit. A data engineer is troubleshooting an IAM policy attached to a user who cannot list objects in the S3 bucket 'example-bucket'. What is the most likely reason?

Refer to the exhibit. A data engineer runs a Glue ETL job that reads from a CSV file and writes to a Redshift table. The job fails with the error shown. What is the most likely cause?

Refer to the exhibit. A data engineer is configuring an AWS Lambda function to process records from a Kinesis stream. The function is set up with an event source mapping, but no records are being processed. The Lambda function's IAM role has the policy shown. What is the most likely reason for the issue?

A data engineer is troubleshooting an AWS Glue ETL job that fails with a memory error when processing a large dataset. Which approach can help reduce memory usage?

A company runs a data processing pipeline using Amazon EMR with Spark. The pipeline reads from S3, processes data, and writes to S3. Recently, the job started failing with 'S3AccessDeniedException' even though the EMR role has appropriate S3 permissions. Which TWO actions should the data engineer take to resolve this issue? (Choose TWO.)

A company uses Amazon Kinesis Data Streams to ingest real-time clickstream data. The data is consumed by a Lambda function that writes to an S3 bucket. Recently, the Lambda function started timing out. Which step should be taken to resolve this issue?

A data engineer is troubleshooting an AWS Glue job that fails with 'java.lang.OutOfMemoryError: Java heap space'. The job processes a large dataset. Which TWO configuration changes should the engineer consider to resolve this issue? (Choose TWO.)

A data engineer is designing a data pipeline that uses AWS Glue to process data from an RDS MySQL database. The pipeline must capture only incremental changes (inserts and updates) and run every hour. Which approach is most cost-effective and reliable?

A company uses Amazon Kinesis Data Firehose to deliver streaming data to Amazon S3. The delivery stream is failing with 'Insufficient capacity' errors. Which THREE actions should the data engineer take to resolve this issue? (Choose THREE.)

A company runs a Redshift cluster and notices that query performance has degraded over time. The data engineer suspects that table statistics are stale. What should the engineer do to improve query performance?

A data pipeline uses AWS Glue to process data from Amazon S3. The job fails with an 'OutOfMemoryError' during the transformation phase. Which action should the data engineer take to resolve this issue?

A data engineer is monitoring an Amazon EMR cluster and notices that the cluster is running out of disk space on the core nodes. Which action can be taken to resolve this issue?

A company runs an Amazon Redshift cluster for analytics. During peak hours, query performance degrades significantly. The data engineer notices that disk space usage is above 80% on many nodes. Which of the following is the MOST effective long-term solution to improve query performance?

A company has an S3 data lake with millions of objects. A data engineer needs to provide a daily report of objects that are not accessed for 90 days. The engineer must minimize cost and impact on performance. Which approach should be used?

A data engineer needs to monitor Amazon DynamoDB table metrics to detect throttled requests. Which CloudWatch metric should the engineer set an alarm on?

A data engineer is troubleshooting a failed AWS Glue Crawler. The crawler logs show 'Insufficient permissions to access S3 bucket'. What should the engineer do to resolve this?

A company uses AWS Kinesis Data Streams to ingest real-time data. The data engineer notices that the stream's 'WriteProvisionedThroughputExceeded' error occurs frequently during peaks. Which action should be taken to resolve this issue?

A company is using Kinesis Data Firehose to deliver data to an S3 bucket. The delivery stream is failing with 'S3 bucket access denied' errors. The bucket policy allows the Firehose service principal. What could be the issue?

A data engineer is troubleshooting a failed AWS Glue ETL job that reads from a JDBC source. The error log shows 'java.sql.SQLException: Connection timed out'. The job previously ran successfully. Which of the following is the MOST likely cause?

A data engineer is designing a solution to move data from an on-premises Oracle database to Amazon S3 using AWS DMS. The engineer needs to ensure that data changes are replicated continuously with minimal latency. Which DMS configuration is most appropriate?

A company stores sensitive data in Amazon S3 and needs to ensure that data is encrypted at rest. Which AWS service can be used to manage the encryption keys?

A data engineer is troubleshooting a slow-running Amazon Athena query on a large dataset stored in S3. The query scans many small files. Which TWO actions can improve query performance?

A company is running a Redshift cluster and wants to improve query performance for a frequently used dashboard. Which THREE approaches are recommended?

A data engineer is designing a data lake on Amazon S3. The data is accessed frequently for the first 30 days, then rarely after that. Which lifecycle policy is MOST cost-effective?

A data engineer is setting up a data pipeline using AWS Glue. The engineer wants to monitor job failures and receive notifications. Which TWO services can be used together for this purpose?

A company runs an Amazon EMR cluster with Spark jobs. One job fails with 'Container killed by YARN for exceeding memory limits'. The data engineer has already increased the executor memory. What is the NEXT best step to resolve the issue?

Refer to the exhibit. A data engineer runs the command on an object in S3. The engineer expected the object to have a tag 'type=raw' but sees no metadata. What is the likely cause?

A data engineer needs to automate the backup of an Amazon RDS for PostgreSQL database. Which AWS service can be used to schedule and manage the backups?

Refer to the exhibit. A data engineer has attached this IAM policy to a user. The user reports being unable to upload files to my-bucket from an on-premises network with a public IP of 203.0.113.5. What is the issue?

A data engineer is troubleshooting a slow-running Amazon Athena query. The query scans a large amount of data. Which TWO actions can improve query performance? (Choose TWO.)

Refer to the exhibit. A data engineer runs this CloudWatch Logs Insights query on a log group but gets no results. What is the most likely reason?

A company is experiencing high costs from Amazon Redshift. The data engineer wants to optimize costs. Which THREE actions should the engineer take? (Choose THREE.)

A data engineer notices that an AWS Glue ETL job processing data from Amazon S3 to Amazon Redshift has been failing intermittently with the error 'S3ServiceException: SlowDown'. Which action is MOST likely to resolve this issue?

A data engineer needs to ensure that data in an Amazon S3 bucket is not publicly accessible. Which TWO measures should the engineer implement? (Choose TWO.)

A company runs a data pipeline that ingests streaming data via Amazon Kinesis Data Streams, processes it with an AWS Lambda function, and stores results in Amazon DynamoDB. The Lambda function sometimes fails due to 'ProvisionedThroughputExceededException' on the DynamoDB table. Which combination of steps should a data engineer take to resolve this issue?

A data engineer notices that an AWS Glue ETL job is failing with an OutOfMemory error when processing a large dataset. The job uses a Standard worker type. Which action is MOST effective to resolve this issue without changing the job script?

A data engineer needs to troubleshoot a failed AWS Glue job that reads from an Amazon RDS for MySQL database. The error log shows 'Communications link failure'. Which step should the engineer take FIRST?

A company uses AWS DMS to migrate a 2 TB Oracle database to Amazon RDS for PostgreSQL. The migration completes successfully, but data validation shows some tables have missing rows. The task is configured for ongoing replication using change data capture (CDC). What is the MOST likely cause of the missing rows?

A company uses Amazon EMR to process large datasets stored in Amazon S3. The data engineer notices that EMR tasks are failing with 'DiskOutOfSpace' errors. The cluster uses m5.xlarge instances with 1 EBS volume of 64 GB. What is the MOST cost-effective solution to resolve this issue?

A data engineer is optimizing an Amazon Redshift cluster that runs a nightly ETL workload. The engineer notices that the query performance degrades over the week and improves after a VACUUM operation. Which action should the engineer take to automate this maintenance and minimize impact on performance?

A team uses Amazon Kinesis Data Analytics to process streaming data. They notice that the application's output is delayed. Which AWS service can be used to monitor the application's performance and identify bottlenecks?

A data engineer is troubleshooting an AWS Glue job that reads from an Apache Kafka topic using a Glue connector. The job fails with 'TimeoutException'. The Kafka cluster is in a VPC. Which step should the engineer take FIRST?

A company runs a daily batch process that reads data from Amazon S3, transforms it with AWS Glue, and loads it into Amazon Redshift. The process takes 6 hours, but the business requires completion within 4 hours. Which design change would MOST reduce runtime?

A company uses Amazon S3 to store raw data files. An AWS Glue crawler creates metadata in the Data Catalog. The data engineer discovers that the crawler is not detecting new partitions after new data is added to the S3 bucket. What is the MOST likely cause?

A data engineer is troubleshooting an AWS Step Functions workflow that calls a Lambda function to process data. The workflow sometimes fails with a 'StateMachineExecutionLimitExceeded' error. What is the MOST likely cause?

A data engineer is monitoring an Amazon Redshift cluster using Amazon CloudWatch. The engineer notices that the 'WriteThroughput' metric is consistently below the provisioned IOPS for the cluster's EBS volumes. The query performance is slower than expected. Which action is MOST likely to improve write performance?

A company stores sensitive data in Amazon S3. To meet compliance requirements, they need to ensure that any data older than 1 year is automatically moved to a lower-cost storage class. Which S3 feature should they use?

A data engineer is troubleshooting a failed AWS Glue job that writes results to Amazon S3. The error log shows 'AccessDenied' when trying to list the bucket. Which IAM policy statement should the engineer add to the Glue job's role?

A data engineer uses Amazon EMR to run a Spark job that reads from S3 and writes to HDFS on the cluster. The job fails with an 'OutOfMemoryError: Java heap space' error in the executors. Which parameter adjustment should be made to resolve this?

A data engineer is designing a disaster recovery strategy for an Amazon RDS for PostgreSQL database that is used in a data pipeline. The database must have a Recovery Point Objective (RPO) of less than 1 minute and a Recovery Time Objective (RTO) of less than 5 minutes. Which TWO actions should the engineer take?

A company runs a data lake on Amazon S3 with AWS Glue and Amazon Athena. The data engineer notices that queries are slow and scanning large amounts of data. Which THREE actions should the engineer take to optimize query performance and reduce costs?

A company uses AWS Lake Formation to manage access to data in S3. A data analyst reports being unable to query a table in Amazon Athena, receiving an 'Access Denied' error. The analyst has SELECT permission on the table in Lake Formation. What additional configuration is MOST likely causing the issue?

A data engineer is troubleshooting an Amazon EMR cluster that has been running for several days. The cluster uses Amazon S3 as the data source and HDFS for intermediate storage. The engineer notices that some tasks fail with 'Java heap space' errors. Which TWO actions should the engineer take to resolve this issue?

A company uses Amazon Redshift for data warehousing. They notice that query performance has degraded over time. Which maintenance operation should be performed to improve performance?

Refer to the exhibit. An AWS Glue job is failing with 'AccessDenied' when trying to write to the 'data-lake-bucket' which is encrypted with an AWS KMS key. The IAM role used by the Glue job has the attached policy shown. What is the MOST likely cause of the failure?

A company uses Amazon DynamoDB as the primary data store for a web application. The application experiences high read latency. Which TWO actions can improve read performance?

Refer to the exhibit. A data engineer is troubleshooting an AWS Lambda function that processes data from Amazon S3. The function is triggered by S3 events, but no logs appear in CloudWatch Logs. The engineer runs the AWS CLI command shown. What is the MOST likely reason for the missing logs?

A data engineer is designing a data pipeline that ingests data from multiple sources into Amazon S3, then processes it with AWS Glue and loads it into Amazon Redshift. Which THREE practices should be implemented to ensure data quality?

Refer to the exhibit. A data engineer runs the command on an Amazon S3 bucket used for data lake storage. The engineer is concerned about accidental overwrites of objects. What does the output indicate?

A company is using AWS Glue to process data stored in Amazon S3. The Glue job runs successfully but takes longer than expected. Which TWO actions can reduce the job runtime?

A data engineering team uses AWS Glue ETL jobs to process data from Amazon S3. The jobs recently started failing with 'Access Denied' errors when writing to the output S3 bucket. What is the most likely cause?

Refer to the exhibit. A data engineer sees this output from the AWS CLI for a failed Glue job. The job uses 10 workers of Standard type. What is the MOST appropriate action to resolve the OutOfMemoryError?

A data engineer needs to monitor the number of records processed by a Kinesis Data Firehose delivery stream and set an alarm if the count drops below a threshold. Which CloudWatch metric should be used?

A company runs a Redshift cluster for analytics. The data engineering team notices that COPY commands from S3 are failing for large files (>1 GB) with the error 'S3ServiceException: SlowDown'. What is the most effective solution?

Refer to the exhibit. This IAM policy is attached to a user who is trying to read the object s3://data-bucket/confidential/report.csv. The user's principal tag 'role' is set to 'analyst'. What will happen when the user attempts to read the object?

A data engineer is troubleshooting a step function that orchestrates ETL jobs. The state machine fails with 'State Machine Execution Throttled' error. What should the engineer do to resolve this?

Refer to the exhibit. A data engineer runs this CLI command to check an object's metadata. The engineer wants to verify if the object is eligible for lifecycle transition to S3 Glacier based on its age. What additional information is needed?

A company uses Amazon Athena to query data in S3. Recently, queries have become slow. The data is stored as CSV files in a partitioned table. What is the most effective way to improve query performance?

A data engineer is troubleshooting a failed AWS Glue ETL job that reads from an S3 bucket and writes to an Amazon Redshift table. The job fails with a permission error. Which IAM policy addition is MOST likely required for the Glue job's role?

A data engineer is troubleshooting a DMS task that is replicating data from an on-premises Oracle database to an RDS for MySQL instance. The task is failing with 'ORA-1555: snapshot too old' error. What is the best course of action?

A company runs an Amazon RDS for PostgreSQL database and wants to capture change data (inserts, updates, deletes) to stream into Amazon Kinesis Data Streams for real-time processing. Which AWS service should be used to capture the changes directly from the database?

A data engineer is designing a data pipeline that ingests streaming data from an IoT fleet using Kinesis Data Streams and processes it with a Lambda function. The Lambda function often times out when the data volume spikes. What is the most scalable solution?

A company uses Amazon Kinesis Data Analytics for Apache Flink to process streaming data. The application reads from a Kinesis data stream and writes results to an S3 bucket. The application is consistently running out of memory and failing. The operator has already increased the Parallelism and TaskManager memory. What is the next BEST step to troubleshoot?

A company stores sensitive customer data in an S3 bucket. The data engineer needs to ensure that all data is encrypted at rest. Which S3 feature should be enabled?

A data engineer needs to export data from an Amazon DynamoDB table to Amazon S3 for archival purposes. The export should be a one-time operation and must not impact the read capacity of the table. Which approach meets these requirements?

A data engineer is running a Glue ETL job that reads from a JDBC source and writes to S3 in Parquet format. The job is slow and the engineer notices that the number of DPUs used is low. What can be done to improve performance?

A data engineer is setting up a Redshift cluster and needs to ensure high availability. Which TWO actions should be taken?

A company is using Amazon Athena to query data in an S3 bucket. Queries are failing with the error 'HIVE_PATH_ALREADY_EXISTS'. The data is partitioned by year, month, day. What is the MOST likely cause?

A company is using Amazon EMR to run Spark jobs. The jobs are failing due to memory issues. Which THREE configurations can help mitigate out-of-memory errors?

A data engineer is designing a data pipeline that ingests millions of small JSON files (1-10 KB each) from an S3 bucket into Amazon Redshift. The current approach uses a Lambda function triggered by S3 events to call the Redshift COPY command for each file. This is causing high latency and throttling. Which alternative is MOST cost-effective and efficient?

A data engineer needs to monitor the performance of an RDS for PostgreSQL database. Which THREE CloudWatch metrics are most useful for this purpose?

A company runs an Amazon EMR cluster that processes data from S3 and writes results back to S3. The cluster uses Spot Instances for task nodes. Some tasks are failing due to Spot Instance interruptions. What is the BEST way to handle this without manual intervention?

Refer to the exhibit. An IAM policy is attached to an IAM role used by an application. The application needs to read objects from 'my-bucket' that have the tag 'classification=public'. The application account is 123456789012. However, the application is getting 'Access Denied' errors. What is the most likely reason?

A company uses AWS Glue DataBrew to clean and transform data. A data engineer notices that a DataBrew recipe step that should remove duplicates is not working as expected. The dataset has millions of rows. What is the MOST likely reason?

Refer to the exhibit. A data engineer sees this error in CloudWatch Logs from an AWS Glue ETL job. The job reads from an S3 location that contains both .parquet and .csv files. What is the most likely cause?

A data engineer needs to monitor the number of records processed by an Amazon Kinesis Data Analytics application and trigger an alarm if the count drops below a threshold over 5 minutes. Which CloudWatch metric should be used?

Refer to the exhibit. A CloudFormation template is used to create a DynamoDB table. After creation, a data engineer wants to restore the table to a point in time from 3 hours ago. Which action is required?

Which TWO actions should a data engineer take to optimize Amazon S3 query performance for Amazon Athena when dealing with large Parquet files? (Choose 2.)

A data engineer is troubleshooting a nightly ETL job that extracts data from an Amazon RDS MySQL instance and loads it into an Amazon S3 bucket in Parquet format. The job runs on an Amazon EMR cluster and has been failing with the error 'Access Denied' when writing to S3. The IAM role attached to the EMR cluster has permissions for S3 PutObject. What is the MOST likely cause?

Which THREE considerations are important when designing a data pipeline that uses AWS Glue to process streaming data from Amazon Kinesis Data Streams? (Choose 3.)

A company runs a data pipeline on AWS Glue that processes streaming data from Amazon Kinesis Data Streams and writes results to an Amazon Redshift cluster. The pipeline has been running smoothly, but recently the Glue job started failing with 'ResourceNotFoundException' for the Redshift table. What should the data engineer check first?

Which TWO AWS services can be used to schedule and orchestrate ETL workflows that involve multiple steps and dependencies? (Choose 2.)

A data engineer is monitoring an Amazon Kinesis Data Analytics application that processes real-time clickstream data. The application uses a Flink application with multiple operators. The engineer notices that the 'millisBehindLatest' metric is increasing steadily. Which action is MOST likely to reduce the lag?

A data engineer is tasked with designing a disaster recovery solution for a data lake stored in Amazon S3. The data lake contains sensitive customer data that must be replicated to a different AWS Region. The engineer needs to ensure that all objects, including those with encryption using SSE-KMS, are replicated. Which solution meets the requirements?

A data engineer is troubleshooting a failed AWS Glue ETL job that reads from and writes to the S3 bucket 'example-bucket'. The job's IAM role has the policy shown in the exhibit. The job fails with an Access Denied error when writing to a prefix 'output/'. Which permission is MISSING?

A company runs a data warehouse on Amazon Redshift. The data engineer notices that some queries are running slowly. Upon reviewing the system tables, the engineer finds that the 'svv_table_info' shows high 'unsorted' percentage for several large tables. What is the MOST effective action to improve query performance?

A data engineer is running an AWS Glue ETL job that converts CSV files to Parquet. The job fails with the error shown in the exhibit. The input files are about 500 MB each. The job uses 5 workers of type G.1X (16 GB memory each). What is the MOST likely cause?

A data engineer is designing a data pipeline that ingests data from an on-premises database into Amazon S3 using AWS Database Migration Service (DMS). The data must be encrypted at rest in S3 using SSE-S3. The engineer also needs to track changes to the source database in real time. Which DMS configuration should the engineer use?

A data engineer is investigating why Amazon Athena queries on the 'my-data-lake' bucket are slow. The table is partitioned by year/month/day. The exhibit shows the objects in one partition. What is the MOST likely cause of poor query performance?

A company uses Amazon Athena to query data stored in an S3 bucket. The data is partitioned by year, month, day, and hour. The data engineer notices that queries are scanning a large amount of data even with a WHERE clause on the partition columns. What is the MOST likely cause?

A data engineering team notices that an Amazon Kinesis Data Stream is frequently exceeding its shard write throughput limit, causing throttling. The team needs a long-term solution to handle variable write traffic without manual intervention. Which action should the team take?

A data engineer is monitoring an Amazon Redshift cluster and notices that the 'WLM query wait time' metric is consistently high during peak hours. The cluster uses automatic WLM. The engineer wants to reduce query wait times without changing the cluster size. Which action is MOST effective?

A data pipeline uses AWS Glue ETL jobs to process data from Amazon RDS for MySQL to Amazon S3. Recently, the jobs have been failing with the error 'Communications link failure' during the connection phase. The RDS instance is in a private subnet, and the Glue job uses a VPC endpoint for S3. What is the most likely cause?

A company runs a data pipeline that uses AWS Glue to process data from an Amazon DynamoDB table and write results to Amazon S3. The Glue job runs on a schedule every hour. Recently, the job started failing intermittently with 'ProvisionedThroughputExceededException' errors from DynamoDB. What is the BEST solution?

A company uses Amazon S3 to store raw data and AWS Lambda to process files as they arrive. The Lambda function sometimes times out when processing large files. The team wants to improve reliability and scalability. Which approach should the team take?

A data engineer is designing a data pipeline that ingests JSON data from Amazon Kinesis Data Streams and processes it using AWS Lambda. The Lambda function writes the processed data to an Amazon S3 bucket. The engineer needs to ensure at-most-once processing semantics. Which TWO configurations should the engineer implement? (Choose two.)

A data engineer runs an AWS Glue Crawler that updates a table in the AWS Glue Data Catalog. The table is used by Amazon Athena queries. After the crawler runs, some queries start failing with the error 'HIVE_CANNOT_OPEN_SPLIT'. What is the most likely cause?

A company uses Amazon EMR to run Spark jobs on data stored in Amazon S3. The data engineer notices that the jobs are running slower than expected. The engineer suspects that the S3 storage class might be affecting performance. Which THREE factors can impact read performance from S3? (Choose three.)

A team uses Amazon Redshift for analytics. They notice that some queries are slow and the system shows high disk usage. The team wants to improve query performance without adding more nodes. Which action should they take first?

A data engineer is setting up a new Amazon Redshift cluster for a data warehouse. The engineer wants to ensure data durability and high availability. Which THREE features should the engineer consider? (Choose three.)

A company uses AWS DMS to migrate data from an on-premises Oracle database to Amazon RDS for PostgreSQL. The migration completes successfully, but the target database has inconsistent data. What should the team do to ensure data consistency?

A data engineer is troubleshooting an AWS Glue job that writes data to an S3 bucket. The IAM role attached to the Glue job has the policy shown in the exhibit. The job fails when writing to the 'secrets/' prefix but succeeds when writing to other prefixes. What is the reason for the failure?

A data pipeline uses Amazon Kinesis Data Firehose to deliver data to an Amazon S3 bucket. The delivery stream is configured with a buffer size of 5 MB and a buffer interval of 60 seconds. The team notices that the S3 objects are much smaller than 5 MB. What is the most likely explanation?

A data engineer is investigating a failed AWS Glue job. The engineer runs the CLI command shown in the exhibit to retrieve the latest log stream. The output shows storedBytes: 0. What does this indicate?

A data engineer runs an AWS Glue ETL job that reads from an S3 bucket containing JSON files. The job fails with an error indicating that some records are malformed. The engineer wants to skip the malformed records and continue processing. Which approach should the engineer take?

A data engineer is configuring an S3 bucket for a data lake. The engineer runs the command shown in the exhibit. What does the output indicate about the bucket?

A data engineering team notices that an AWS Glue ETL job fails intermittently with a 'ThrottlingException' error. The job reads from an Amazon S3 bucket and writes to an Amazon Redshift table. What is the MOST likely cause of this error?

A company uses Amazon EMR to run Spark jobs on a transient cluster. The jobs process data from S3 and write results back to S3. The team wants to reduce costs by optimizing the cluster. Which action should the team take?

A company runs an Amazon DynamoDB table with on-demand capacity. A new reporting application performs frequent Scan operations on the table, causing occasional 'ProvisionedThroughputExceededException' errors. The operations team needs to resolve this with minimal cost. What should they do?

A data engineer is troubleshooting a failed AWS Glue ETL job that reads from an S3 bucket. The job logs show the following error: 'java.lang.RuntimeException: java.lang.ClassNotFoundException: Class org.apache.hadoop.fs.s3a.S3AFileSystem not found'. Which TWO actions will resolve this issue?

A data engineer is troubleshooting a failed Amazon Kinesis Data Firehose delivery stream. The stream is configured to deliver data to an Amazon S3 bucket. The error log shows: 'The destination S3 bucket's bucket policy does not allow the firehose to put objects.' What is the MOST likely issue?

A company uses Amazon RDS for MySQL as a source for AWS DMS. The replication tasks are failing due to large transactions on the source. The team wants to reduce the impact of large transactions on DMS. Which THREE actions should the team take?

A company uses Amazon Redshift for data warehousing. They notice that queries are running slowly, and the STL_LOAD_ERRORS table shows many 'Parse error' entries. The data is loaded from Amazon S3 using COPY commands. What is the MOST likely cause of the parse errors?

A data engineer is monitoring Amazon CloudWatch metrics for an Amazon Redshift cluster and notices high CPU utilization. The engineer wants to reduce CPU usage. Which TWO actions should the engineer take?

A data engineer is monitoring an Amazon Kinesis Data Stream and notices that the 'WriteProvisionedThroughputExceeded' metric is frequently elevated. The stream has 5 shards and is used by multiple producers. What is the BEST action to resolve this issue?

A data engineer notices that an AWS Glue ETL job that processes streaming data from Amazon Kinesis Data Streams is failing intermittently with a 'ResourceNotFoundException' error for the Kinesis stream. The job has been running successfully for weeks. Which action should the engineer take to resolve the issue?

A company uses AWS Glue to run ETL jobs on a schedule. Recently, a job failed with the error: 'AnalysisException: cannot resolve '`column_name`' given input columns: ...'. The job reads from an Amazon S3 source that has a schema defined in the AWS Glue Data Catalog. What is the MOST likely cause?

A company uses AWS DMS to replicate data from an on-premises Oracle database to Amazon RDS for MySQL. The full load completes successfully, but ongoing replication (CDC) is failing with a 'Failed to add supplemental logging' error. What should the data engineer do to resolve this issue?

A data engineer needs to back up an Amazon DynamoDB table daily. The backup must be restorable to a specific point in time within the last 24 hours. Which solution meets these requirements with the LEAST operational overhead?

A company runs a critical PostgreSQL database on Amazon RDS. The database experiences high read latency during peak hours. The data engineer needs to reduce read latency with minimal changes to the application. Which solution is MOST effective?

A data engineer is monitoring an Amazon Redshift cluster and notices that some queries are experiencing high disk usage and slow performance. The engineer wants to identify the queries that are causing the most disk spills to temporary files. Which system table should the engineer query to get this information?

A data engineer is troubleshooting a data pipeline that uses Amazon Kinesis Data Firehose to deliver data to Amazon S3. The engineer notices that the S3 bucket contains many small files (less than 1 MB). This is causing performance issues in downstream processing. What is the BEST way to reduce the number of small files?

A company is running an Amazon EMR cluster with Spark for data processing. The data engineer wants to automatically scale the core and task nodes based on the YARN memory and CPU utilization. Which scaling metric should the engineer use for the EMR managed scaling policy?

A data engineer is using Amazon EMR to process large datasets. The cluster uses a mix of Spot Instances and On-Demand Instances. The engineer wants to reduce costs while ensuring the job can complete even if Spot Instances are reclaimed. Which TWO actions should the engineer take? (Choose two.)

A data engineer is troubleshooting a failed AWS Glue job that reads from an Apache Hive metastore in an Amazon EMR cluster. The error message indicates 'ClassNotFoundException: org.apache.hadoop.hive.ql.metadata.HiveException'. The Glue job uses a custom Python shell script. What is the most likely cause of this error?

A company uses Amazon S3 to store sensitive data. The security team requires that all data in transit between on-premises applications and S3 be encrypted. The data engineer must implement a solution that meets this requirement without changing the applications. Which TWO solutions should the engineer consider? (Choose two.)

A company stores sensitive data in Amazon S3 and uses AWS Lake Formation to manage fine-grained access control. A data engineer notices that users are able to access data in S3 directly via the AWS Management Console, bypassing Lake Formation permissions. What should the engineer do to enforce Lake Formation access controls for all access methods?

A data engineer is designing a data pipeline that processes streaming data. The pipeline must be able to handle duplicate records and ensure exactly-once processing semantics. Which THREE AWS services or features should the engineer consider? (Choose three.)

A data engineer is running an Amazon Athena query that scans a large amount of data in Amazon S3, resulting in high costs. The data is stored in Parquet format in a partitioned table. Which strategy would be MOST effective in reducing the amount of data scanned?

A data engineer has attached the IAM policy shown in the exhibit to a role used by an AWS Glue ETL job. The job fails when trying to write to the S3 bucket 'example-bucket' with the error: 'Access Denied'. What is the MOST likely reason?

A company uses Amazon DynamoDB as the primary data store for a real-time application. The data engineer observes that some read requests are returning stale data, even though the application uses strongly consistent reads. The table has auto-scaling enabled with a maximum read capacity of 10,000 RCUs. The observed read traffic averages 8,000 RCUs but occasionally spikes to 12,000 RCUs. What is the most likely cause of the stale reads?

A data engineer sees the CloudWatch log entry in the exhibit for a Lambda function that processes data from an Amazon SQS queue. What is the MOST likely cause of the timeout?

A data engineer needs to implement a data pipeline that ingests data from an on-premises database using AWS DMS and loads it into Amazon S3 in Parquet format. The data should be encrypted at rest in S3 using a customer-managed KMS key. Which combination of actions should the engineer take? (Choose the correct course of action.)

A data engineer creates an Amazon DynamoDB table using the CloudFormation snippet in the exhibit. The application writes 200 items per second to the table. The engineer notices that many write requests are being throttled. What is the MOST likely reason?

A data engineer is troubleshooting an Amazon Redshift cluster that has experienced a node failure. The engineer needs to ensure that the cluster is highly available and can withstand a single node failure without downtime. Which TWO actions should the engineer take?

A data engineer notices that an Amazon S3 bucket policy is overly permissive. What is the best practice to restrict access while maintaining required permissions?

A data pipeline using AWS Glue jobs is failing with 'Insufficient capacity' errors for Spark executors. Which action should the data engineer take to resolve this?

A company is using Amazon Kinesis Data Analytics (now part of Amazon Managed Service for Apache Flink) for streaming data processing. The application is experiencing high latency and the data engineer wants to improve performance. Which THREE actions should the engineer consider? (Choose three.)

A company uses AWS Lake Formation to manage data lake permissions. A data engineer needs to grant a group of analysts SELECT permission on a set of tables in the 'analytics' database, but only for columns that are not classified as 'PII'. Which approach should the engineer use?

A data engineer is setting up an AWS Glue job to process data from an Amazon S3 bucket. The job fails with an 'Access Denied' error. Which TWO IAM permissions are MOST likely missing from the Glue job's IAM role?

A data engineer is troubleshooting a slow Amazon Redshift query. The EXPLAIN plan shows a 'Seq Scan' on a large table. What is the most likely cause?

Refer to the exhibit. A data engineer has an IAM policy attached to an IAM role used by an AWS Glue job. The Glue job reads from S3 bucket 'example-bucket' and writes to an S3 bucket 'output-bucket'. The job fails with an 'Access Denied' error when writing to 'output-bucket'. What is the MOST likely cause?

A company uses AWS DMS to migrate data from an on-premises Oracle database to Amazon Aurora MySQL. The migration is successful, but the ongoing replication task is experiencing high latency. Which configuration change is most likely to reduce latency?

Refer to the exhibit. A data engineer is reviewing the configuration of an Amazon Redshift cluster. The engineer wants to ensure that the cluster can be restored to a point in time up to 35 days in the past. Based on the exhibit, what change is needed?

A data engineer is designing a data pipeline that ingests JSON files from an S3 bucket, transforms them using AWS Glue, and loads into Amazon Redshift. The data is updated daily, and the pipeline must handle late-arriving data from the previous day. Which approach minimizes reprocessing?

Refer to the exhibit. A data engineer sees this error log from an Amazon EC2 instance that is trying to access an S3 bucket in the us-west-2 region. The EC2 instance is in a VPC with a private subnet and no internet gateway. What is the MOST likely cause of this error?

An Amazon CloudWatch alarm is configured to monitor the CPUUtilization of an EC2 instance. The alarm state is 'INSUFFICIENT_DATA'. What is the most likely cause?

A data engineer notices that an AWS Glue ETL job is failing with a 'MemoryError' when processing a large dataset. Which approach should the engineer take to resolve this issue?

A data engineer needs to set up a cross-account access for an S3 bucket so that users in Account B can read objects. The bucket in Account A has a bucket policy that grants access. What additional step is required?

A company runs a production Amazon Redshift cluster. The data engineering team notices that queries are running slowly during peak hours. The cluster's CPU utilization is consistently above 80%. Which action should the engineer take to improve query performance?

A company uses Amazon Kinesis Data Streams with a Lambda consumer. The Lambda function is failing with 'ProvisionedThroughputExceededException' when writing to a DynamoDB table. Which action should the data engineer take to resolve this without losing data?

A data pipeline uses AWS DMS to replicate data from an on-premises Oracle database to Amazon S3 in Parquet format. The pipeline has been running successfully for months, but recently the DMS task status shows 'failed' with the error: 'The source database is running out of archive log space.' Which action should the engineer take to prevent this error?

A data engineer needs to ensure that sensitive data stored in Amazon S3 is encrypted at rest. Which TWO options meet this requirement? (Choose TWO.)

A data engineer is designing a disaster recovery strategy for an Amazon RDS for MySQL database with Multi-AZ deployment. Which THREE actions should the engineer take to meet a Recovery Point Objective (RPO) of 5 minutes and a Recovery Time Objective (RTO) of 15 minutes? (Choose THREE.)

A data engineer is troubleshooting a failed AWS Glue job that reads from an Amazon RDS for MySQL table. The error message indicates 'java.sql.SQLException: No suitable driver'. What is the most likely cause?

A data engineer is troubleshooting a failed AWS Glue job that reads from an S3 bucket and writes to an Amazon Redshift table. The error message indicates 'Access Denied'. Which TWO permissions are likely missing? (Choose TWO.)

A company uses Amazon Kinesis Data Streams to ingest real-time clickstream data. A Lambda function processes each record. Recently, the Lambda function has been failing with 'ProvisionedThroughputExceededException' when writing results to a DynamoDB table. The data engineer has already increased the DynamoDB write capacity. What else can the engineer do to resolve the issue?

An IAM policy is attached to an IAM role used by an EC2 instance in the 10.0.0.0/8 VPC. The EC2 instance cannot read objects from the S3 bucket. What is the most likely cause?

A data engineer needs to grant an IAM user read-only access to an S3 bucket named 'data-lake-bucket'. Which IAM policy statement should be attached to the user?

A data engineer runs the above AWS CLI command to investigate who uploaded a file to an S3 bucket. The output shows the event was recorded. Which additional step is needed to confirm the identity of the user?

An AWS Glue job that performs data transformation on large Parquet files in Amazon S3 is taking a long time to complete. The job uses the default number of DPUs. Which change would most likely improve the job's performance?

A data engineer has this IAM policy attached to their user. They are trying to create an Amazon EMR cluster with a custom service role 'EMR_CustomRole'. What will happen?

A company uses Amazon Athena to query data in an S3 bucket. A data engineer notices that a query fails with the error: 'HIVE_CANNOT_OPEN_SPLIT: Error opening Hive split s3://bucket/path/file.parquet (Path does not exist)'. However, the file exists in S3. What is the most likely cause?

A data engineer is troubleshooting a failed AWS Glue ETL job that reads from an S3 bucket and writes to an Amazon Redshift table. The job logs show a permission error. Which IAM policy change would resolve the issue?

A company uses Amazon Kinesis Data Streams to ingest real-time clickstream data. The consumer application is falling behind and the iterator age is increasing. Which action would most effectively improve throughput?

A data engineer is designing a disaster recovery strategy for an Amazon Redshift data warehouse. The RPO (Recovery Point Objective) is 1 hour, and the RTO (Recovery Time Objective) is 2 hours. Which approach meets these requirements with the least operational overhead?

A data engineer notices that an Amazon Athena query on a partitioned table in S3 scans more data than expected. The table is partitioned by year, month, day. The query includes a WHERE clause on a non-partition column but also filters on day='2023-01-01'. What is the most likely cause of the excessive data scan?

A data engineer is troubleshooting a slow Amazon Redshift query. The query plan shows a large number of 'DS_DIST_ALL_INNER' and 'DS_BCAST_INNER' operations. Which TWO actions would likely improve query performance?

A data engineer needs to set up a data pipeline that ingests CSV files from an S3 bucket, transforms them using AWS Glue, and loads the results into Amazon Redshift. The pipeline must handle schema evolution and data quality checks. Which combination of services is most appropriate?

A company runs an Amazon EMR cluster processing data from S3. The data engineer notices that the cluster's task nodes are underutilized while core nodes are fully utilized. Which TWO steps should the engineer take to improve resource utilization?

A company is running a critical Amazon RDS for MySQL database. They need to implement a backup strategy that allows point-in-time recovery (PITR) with a recovery time objective (RTO) of 15 minutes and a recovery point objective (RPO) of 5 minutes. Which solution meets these requirements?

A data engineer is setting up a data pipeline to ingest streaming data from an IoT fleet. The data must be processed in near real-time and stored in Amazon S3 for analytics. Which THREE AWS services should the engineer consider using?

A data engineer is monitoring an Amazon EMR cluster and notices that one core node is running out of disk space. The cluster is running a Spark job that processes large Parquet files. What should the engineer do to prevent the issue?

A data pipeline uses AWS Glue to process data from Amazon S3 and write results to Amazon Redshift. The pipeline fails intermittently with the error 'S3ServiceException: Access Denied'. The IAM role used by Glue has permissions to read from the S3 bucket. What is the most likely cause of this error?

A company uses AWS DMS to migrate an on-premises Oracle database to Amazon Aurora PostgreSQL. The migration is ongoing with continuous replication. The data engineer notices that the target Aurora database has a higher lag than expected. Which action would most likely reduce the lag?

A data engineer is designing a data lake on Amazon S3. The data includes sensitive personally identifiable information (PII). Which combination of services would provide the most comprehensive data protection?

A company uses Amazon DynamoDB as the primary data store for a high-traffic application. Recently, read latency has increased significantly. The DynamoDB table has on-demand capacity mode. Which action is MOST effective to reduce read latency?

A data engineer is troubleshooting a slow-running Amazon Redshift query. The query involves a large fact table with a distribution style of EVEN and a sort key on date. The table has 10 slices. The engineer notices that the query is performing a broadcast join with a small dimension table. Which change would most improve performance?

A data engineer needs to monitor the number of records processed by an AWS Glue ETL job. Which CloudWatch metric should the engineer use?

A data engineer is designing a data pipeline using AWS Step Functions to orchestrate multiple AWS Glue ETL jobs. The pipeline must handle failures and retries. Which TWO configurations should the engineer use to ensure the pipeline is resilient? (Choose two.)

A company stores sensitive data in Amazon S3 and requires that all data be encrypted at rest. The data is accessed by multiple AWS services. Which solution meets the encryption requirement with the LEAST operational overhead?

A company uses Amazon Kinesis Data Analytics for Apache Flink to process streaming data. The application is experiencing high latency and checkpoint failures. Which THREE actions should the data engineer take to improve performance and reliability? (Choose three.)

A data pipeline using Amazon Kinesis Data Streams is experiencing high consumer lag. The stream has 10 shards. The consumer is an AWS Lambda function that processes each record and writes to Amazon DynamoDB. What is the MOST likely cause of the lag?

A data engineer is setting up Amazon CloudWatch alarms for an Amazon Redshift cluster. The engineer wants to be alerted when the disk space usage exceeds 80% for more than 5 minutes and when the CPU utilization exceeds 90% for more than 10 minutes. Which TWO CloudWatch metrics and conditions should the engineer use? (Choose two.)

A data engineer needs to transform a large dataset stored in Amazon S3 using Apache Spark. The engineer wants to minimize startup time and use a serverless approach. Which AWS service should the engineer use?

A data engineer is responsible for a data pipeline that uses Amazon S3 as a data lake, AWS Glue for ETL, and Amazon Athena for ad-hoc queries. The pipeline ingests CSV files from an external partner via SFTP into an S3 bucket. The files are then processed by a Glue job that converts them to Parquet and writes to a separate S3 bucket partitioned by date. The Glue job runs daily and is triggered by a scheduled CloudWatch Events rule. Recently, the data engineer noticed that some days the Glue job fails because of memory errors, and on those days the Athena queries that rely on the data return incomplete results. The engineer needs to ensure that the pipeline is resilient and that Athena queries always see a complete view of the data, even if the Glue job fails mid-run. The engineer also needs to minimize re-processing of data. Which course of action should the engineer take?

A company uses AWS DMS to migrate data from an on-premises Oracle database to Amazon Aurora MySQL. After the migration, the data in Aurora is inconsistent with the source. The engineer needs to ensure ongoing replication with minimal downtime. Which solution should the engineer implement?

A data engineering team notices that an AWS Glue ETL job, which processes hourly data from an S3 bucket, is taking progressively longer to run. The job reads Parquet files partitioned by date and hour. Which action is MOST likely to improve the job's performance?

A company runs a time-series forecasting model that writes results to an S3 bucket every 5 minutes. A downstream ETL job reads this data, but sometimes fails because it encounters incomplete files (zero bytes). What is the MOST reliable way to ensure the ETL job only processes complete files?

A data engineer is troubleshooting an AWS Glue ETL job that fails with the error 'java.lang.OutOfMemoryError: Java heap space'. The job processes a large number of small files in Amazon S3. Which action would MOST effectively resolve the issue?

A data engineer needs to troubleshoot why an AWS Glue job is failing with a 'Insufficient Memory' error. The job processes a 10 GB dataset. Which step should the engineer take FIRST?

A data engineer needs to schedule a daily ETL job that runs on Amazon EMR. The job should be triggered automatically and send an email on failure. Which AWS service should the engineer use to orchestrate the job?

A company is using Amazon Redshift for its data warehouse. A data engineer notices that COPY commands from S3 are failing intermittently with 'S3ServiceException: Access Denied'. The IAM role used by Redshift has the correct permissions. What is the MOST likely cause?

A company runs a data lake on Amazon S3 with AWS Glue for ETL. The data is stored in Parquet format and partitioned by date. The data engineer notices that queries using Amazon Athena are scanning large amounts of data even when filtering on the partition column. Which TWO actions would improve query performance? (Choose TWO)

A data pipeline uses AWS Lambda to process records from an Amazon Kinesis Data Stream. The Lambda function is idempotent and runs once per record. Recently, the function started failing with 'ProvisionedThroughputExceededException' when writing to a DynamoDB table. Which action should the data engineer take to resolve this?

A data engineer is designing a disaster recovery plan for an Amazon Redshift data warehouse. The cluster is in us-east-1 and must be recoverable in us-west-2 with minimal data loss. Which THREE actions should the engineer take? (Choose THREE)

A data engineer needs to set up a disaster recovery solution for an Amazon RDS for MySQL database. The database must be available in another AWS Region with minimal data loss. What is the simplest approach?

A company uses Amazon Kinesis Data Firehose to deliver streaming data to Amazon S3. The data must be transformed in real-time using a custom Lambda function. Which TWO steps are required to enable this? (Choose TWO)

A company uses Amazon EMR to run Spark jobs on data stored in S3. After upgrading the EMR cluster to a new release, one of the Spark jobs fails with 'OutOfMemoryError' in the executor. Which configuration change is MOST likely to resolve this issue?

Refer to the exhibit. An IAM policy is attached to a user who needs to read objects from the 'example-bucket' S3 bucket. The user reports being unable to read any object under the 'confidential/' prefix. What is the reason for this access issue?

A data engineer is troubleshooting an AWS Glue ETL job that suddenly started failing with 'An error occurred while calling o103.pyWriteDynamicFrame. Unknown error'. The job writes data to an Amazon Redshift table. Which step should the engineer take FIRST?

Refer to the exhibit. A company has an S3 bucket 'my-data-lake' with the lifecycle policy shown. Objects under the 'logs/' prefix are being moved to GLACIER after 30 days and expire after 365 days. A data engineer notices that objects older than 365 days are still present in the bucket and are not being deleted. What is the most likely cause?

A data engineer needs to monitor the number of records processed by an AWS Glue ETL job and send an alert if the count drops below a threshold. Which AWS service should be used to create this custom metric?

Refer to the exhibit. A data engineer runs two queries on an Athena table partitioned by 'ds'. Both queries scan the same amount of data. What does this indicate?

A company's Amazon Redshift cluster is running slowly. The data engineer suspects that table design is the cause. Which TWO design practices can improve query performance? (Choose TWO.)

A data engineer is troubleshooting an AWS Glue ETL job that fails intermittently with the error 'Rate exceeded.' The job reads from an Amazon RDS for MySQL source and writes to Amazon S3. What is the MOST likely cause of this error?

A data engineer is designing an ETL pipeline that uses AWS Glue to process data from an Amazon DynamoDB table and write results to an S3 bucket in Parquet format. The pipeline must handle schema changes in the source DynamoDB table. Which THREE steps should the engineer take to ensure the pipeline handles schema evolution? (Choose THREE.)

A data engineer needs to transfer 50 TB of data from an on-premises Hadoop cluster to Amazon S3. The network bandwidth is limited to 500 Mbps. Which TWO methods are appropriate for this transfer? (Choose TWO.)

A company uses Amazon Redshift for its data warehouse. During a routine audit, the data engineer discovers that some queries are returning stale data even though the underlying source data has been updated. The engineer confirms that the COPY command completes successfully and that no errors are reported. Which action should the engineer take to ensure queries reflect the latest data?

A data engineer at a financial services company manages an AWS Glue ETL pipeline that processes transaction data from Amazon S3 to Amazon Redshift for reporting. The pipeline runs every hour and uses a Glue job that reads Parquet files, performs transformations in Spark, and writes to Redshift using the JDBC connector. Recently, the job has been failing intermittently with the error: 'java.sql.BatchUpdateException: ERROR: null value in column "transaction_id" violates not-null constraint'. The data engineer has verified that the source Parquet files do contain non-null values for transaction_id. The job uses a DynamicFrame and applies a mapping to rename columns. The engineer also noticed that the failure occurs only during peak hours when there is high concurrency on Redshift. Which course of action should the engineer take to resolve this issue?

A data engineer notices that an Amazon Kinesis Data Firehose delivery stream is failing to deliver data to an Amazon S3 bucket. The engineer verifies that the S3 bucket exists and that the IAM role attached to the delivery stream has the necessary permissions. What is the MOST likely cause of the failure?

A data engineer is responsible for a real-time data pipeline that ingests clickstream data from a website into Amazon Kinesis Data Streams, then processed by an AWS Lambda function that writes to an Amazon DynamoDB table for user session tracking. The Lambda function is idempotent and uses the DynamoDB PutItem API with a condition expression to avoid overwriting existing records. Over the past week, the engineer has observed an increase in DynamoDB write throttling (ProvisionedThroughputExceededException) during peak traffic hours. The DynamoDB table has on-demand capacity. The engineer checks the Lambda function's reserved concurrency and finds it set to 1000. The Kinesis stream has 10 shards. The Lambda function's batch size is set to 100. The engineer suspects that the retry behavior is causing duplicate writes and throttling. Which change should the engineer make to reduce throttling?

A company runs an Amazon EMR cluster with Spark jobs that process data from Amazon S3. The data engineer receives an alert that one of the Spark jobs failed with an OutOfMemoryError. The job processes large files and uses the default Spark configurations. Which configuration change is MOST likely to resolve the issue?

A data engineer is troubleshooting an AWS Glue ETL job that uses a Python shell script to extract data from an Amazon RDS for PostgreSQL database and load it into an Amazon Redshift table. The job runs successfully, but the data engineer notices that the row count in Redshift is consistently lower than the row count in PostgreSQL. The job uses a SELECT * query without any filtering. The data engineer suspects that some rows are being dropped during the transfer. The job uses the psycopg2 library to connect to PostgreSQL and the psycopg2 connection is configured with autocommit=True. The Redshift table has no constraints that would reject rows. What is the most likely cause of the missing rows?

A data engineer uses AWS Database Migration Service (DMS) to migrate an on-premises Oracle database to Amazon Aurora MySQL. The migration is successful, but the engineer notices that the target Aurora cluster has a higher CPU utilization than expected during the full load phase. What is the MOST likely cause?

A data engineer configured an AWS Glue job that reads from an S3 bucket and writes to an Amazon Redshift table. The job runs successfully, but the data in Redshift is missing some records that exist in S3. The engineer suspects the issue may be related to the job's bookmarks. What should the engineer do to ensure all records are processed?

A data engineer needs to move data from an Amazon S3 bucket to an Amazon Redshift cluster on a daily schedule. The data is in CSV format and the target table already exists. Which AWS service should the engineer use to automate this task?

A data engineer is troubleshooting a Kinesis Data Analytics application that processes streaming data. The application is falling behind, and the metric 'MillisBehindLatest' is consistently above 60000. The source Kinesis stream has 10 shards, and the application uses a Flink application with default parallelism. What is the MOST likely cause of the lag?

A company uses Amazon S3 to store sensitive data. The data engineer needs to ensure that all data in transit between the S3 bucket and clients is encrypted. Which configuration should the engineer implement?

Refer to the exhibit. An IAM policy is attached to an IAM user. The user is trying to upload an object to 's3://data-lake-bucket/confidential/report.pdf' using the AWS CLI. The upload fails with an AccessDenied error. What is the reason for the failure?

A company runs a data pipeline that uses AWS Lambda to process files uploaded to an S3 bucket. Recently, some files have been processed multiple times. The Lambda function is triggered by S3 event notifications. What is the MOST likely cause of duplicate processing?