Data Operations and Support

Refer to the exhibit. This log snippet is from a failed AWS Glue job. The job processes a large dataset in memory. What is the MOST likely cause of the OutOfMemoryError?

A data engineer is monitoring an Amazon Redshift cluster and notices that the disk space usage is increasing rapidly. The engineer wants to reclaim space from deleted rows. Which command should the engineer run?

A data engineer is using Amazon Athena to query data stored in Amazon S3. The engineer wants to reduce query costs and improve performance for a table that is frequently queried with filters on a date column. The data is stored as uncompressed CSV files partitioned by year/month/day. Which action should the engineer take?

A data engineer is using Amazon Kinesis Data Firehose to deliver streaming data to an Amazon S3 bucket. The engineer notices that some data records are missing from S3, and the Firehose delivery stream metrics show increased DeliveryToS3.DataFreshness. The engineer needs to ensure all records are delivered. Which action should the engineer take?

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 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 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?

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 manages an AWS Glue ETL job that processes JSON files from Amazon S3 and writes to Amazon Redshift. The job fails with the error 'Unable to find a suitable JDBC driver in the classpath'. The engineer has included the Redshift JDBC driver as a job parameter in the Glue job configuration. Which step should the engineer take to resolve the error?

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 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 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 engineer is using Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to orchestrate a data pipeline. The engineer needs to ensure that the Airflow environment can access an Amazon S3 bucket to read and write data. The S3 bucket is in the same AWS account and Region as the MWAA environment. Which configuration is required to allow MWAA to access the S3 bucket?

A data engineer maintains an AWS Glue ETL job that processes millions of small JSON files stored in Amazon S3. The job's runtime has increased significantly, and CloudWatch logs show many small executor tasks and frequent garbage collection. The engineer wants to improve job performance by reducing the number of small files processed per task. Which action should the engineer take?

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 data engineer needs to set up a data catalog for a new data lake in AWS Glue. The data resides in S3 in Parquet format. The engineer wants to ensure that the schema is automatically detected and updated when new columns are added to the data. Which configuration should the engineer use?

A data engineer manages an AWS Glue ETL job that processes millions of small JSON files in Amazon S3. The job is slow and often fails with an OutOfMemory error on the driver. The engineer wants to improve performance without changing the output format. Which solution should the engineer implement?

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 data engineer is responsible for monitoring an AWS Glue ETL job that runs daily. The job reads data from an Amazon S3 bucket and writes to an Amazon Redshift table. The engineer wants to receive an alert if the job fails or if it takes longer than expected to complete. Which AWS service should the engineer use to set up these alerts with the LEAST operational overhead?

A data analyst needs to query a large Amazon S3 bucket containing CSV files using Amazon Athena. The bucket has millions of small files (less than 1 MB each). The analyst reports that queries are very slow and often time out. The data is partitioned by date and the partition columns are defined in the table. What is the most effective way to improve query performance?

Match each AWS data analytics service to its primary function.

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 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 data engineer is using AWS Step Functions to orchestrate a daily ETL workflow that includes an AWS Glue job, an Amazon EMR step, and an Amazon Redshift stored procedure. The workflow occasionally fails and the engineer needs to troubleshoot and recover. Which TWO actions should the engineer take to identify the failure and resume from the failed step? (Choose two.)

A data engineer is using AWS Step Functions to orchestrate a daily ETL pipeline that includes an AWS Glue job, an Amazon EMR step, and an Amazon Redshift stored procedure. The pipeline occasionally fails with the error 'States.TaskFailed' from the Glue job, but the Glue job's own logs show that it completed successfully. The Step Functions execution history shows that the Glue job task timed out after 15 minutes, while the Glue job actually ran for 18 minutes. The Step Functions state machine uses the optimized Glue service integration with a TaskTimeout of 900 seconds. Which change will allow the pipeline to complete successfully without reducing the Glue job's runtime?

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 data engineer is using AWS Glue to process data from an Amazon Kinesis Data Stream. The Glue job is configured to run every 15 minutes and uses job bookmarks to track processed data. Recently, the job started reprocessing old data, leading to duplicate records in the target Amazon S3 bucket. The engineer verifies that the job bookmark is enabled and the job is not being run manually. Which TWO actions should the engineer take to resolve the duplicate processing issue? (Choose two.)

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 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 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?

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 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 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 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 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?

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 using AWS Database Migration Service (AWS DMS) to migrate an on-premises Oracle database to Amazon Aurora PostgreSQL. The migration is running but the engineer observes that some tables are not being replicated. The DMS task logs show no errors, and the task status is 'Running'. Which action should the engineer take to identify the missing tables?

A company is using AWS Glue to catalog data stored in Amazon S3. The data is partitioned by year, month, and day. A data analyst reports that new partitions are not automatically discovered by the Glue crawler. The crawler runs on a schedule every hour. What is the MOST likely reason for the missing partitions?

A data engineer is using AWS Step Functions to orchestrate a daily pipeline that runs several AWS Glue jobs in sequence. One Glue job intermittently fails due to a transient Amazon S3 503 error. The engineer wants the state machine to automatically retry only that Glue job up to three times with exponential backoff, without retrying the other jobs. What should the engineer do?

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 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 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 monitoring an AWS Glue ETL job that intermittently fails with 'Container killed by YARN for exceeding memory limits' during a large shuffle stage. The job reads from Amazon S3, performs a groupByKey aggregation, and writes to Amazon S3. The engineer wants to reduce the chance of executor memory exhaustion without changing the source data. (Choose two.)

A data engineer is using AWS Database Migration Service (AWS DMS) to migrate an on-premises Oracle database to Amazon Aurora PostgreSQL. The migration is ongoing, and the engineer notices that some transactions are not being replicated to the target. The DMS task is configured for full load plus change data capture (CDC). Which action should the engineer take to troubleshoot the missing transactions?

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 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 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 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 data engineer maintains an AWS Glue job that reads JSON files from Amazon S3, applies a transform, and writes Parquet to a second bucket. The job's bookmark was enabled at creation, but each nightly run reprocesses all previously handled files, and downstream tables now contain duplicate rows. The job script has not been modified and the S3 prefix is unchanged. Which action will MOST directly resolve the duplicate processing?

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 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 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 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?

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 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 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 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 has an AWS Glue job that processes data from an Amazon S3 bucket and writes to an Amazon Redshift cluster. The job is scheduled to run daily. Recently, the job started failing with the error: 'java.sql.SQLException: [Amazon](500310) Invalid operation: Spectrum Scan Error: S3 Access Denied'. The engineer verifies that the IAM role associated with the Glue job has full access to the S3 bucket. What is the most likely cause of this error?

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 needs to monitor an AWS Glue ETL job that runs daily. The job sometimes fails due to missing partitions in the Data Catalog. The engineer wants to receive an alert when the job fails. What is the MOST operationally efficient way to achieve this?

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 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 needs to schedule a recurring AWS Glue ETL job that must run every night at 02:00 UTC and must not start a new run while a previous run is still executing. The engineer wants the simplest managed scheduling option that integrates natively with Glue job run state. Which approach should the engineer use?

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 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 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?

A data engineer runs an AWS Glue ETL job that reads CSV files from an Amazon S3 bucket, applies transformations, and writes Parquet output to another S3 bucket. The job fails with the error 'AnalysisException: Unable to infer schema for CSV. It must be specified manually.' The CSV files are stored with a header row, and the job's script uses the default Glue DynamicFrame reader without specifying format options. What is the MOST likely cause of the failure?

A data engineer has set up an AWS Lambda function that processes files uploaded to an S3 bucket. The function is triggered by S3 event notifications. However, the function is not being invoked when a file is uploaded. The engineer checks the Lambda function's CloudWatch Logs and finds no execution logs. What should the engineer check FIRST?

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 data engineer is managing an Amazon Redshift cluster that experiences performance degradation during peak query hours. The engineer notices that some queries are waiting in the queue for a long time, and the WLM (Workload Management) configuration is set to auto. The engineer wants to implement manual WLM to improve query throughput and ensure that short-running queries are not blocked by long-running ones. Which TWO actions should the engineer take to achieve this? (Choose two.)

A data engineer needs to schedule a daily AWS Glue job that extracts data from Amazon S3 and loads it into Amazon Redshift. The engineer wants to ensure the job runs at 2:00 AM UTC every day and can be monitored for failures. What is the simplest way to achieve this?

A data engineer is using AWS Step Functions to orchestrate an ETL workflow that includes an AWS Glue job. The Glue job occasionally fails due to transient issues, such as network timeouts. The engineer wants the Step Functions state machine to automatically retry the Glue job up to three times with exponential backoff before failing the workflow. Which Step Functions state configuration should the engineer use?

A data engineer is running an Amazon EMR cluster with Spark to process log files. The cluster uses instance fleets with m5.xlarge core nodes. The engineer observes that the Spark job is running slower than expected. CloudWatch metrics show that the cluster's CPU utilization is below 20% but memory utilization is near 90%. Which configuration change would most likely improve performance?

A data engineer is managing an Amazon Redshift cluster that experiences performance degradation during peak query hours. The engineer needs to identify and resolve issues related to workload management (WLM). Which TWO actions should the engineer take to improve query performance? (Choose two.)

A company is migrating its on-premises data warehouse to Amazon Redshift. The data includes tables with up to 100 columns and 500 million rows. The migration involves a full load followed by incremental updates. The company needs to minimize downtime during the final cutover. Which THREE strategies should the data engineer use to facilitate the migration? (Choose THREE.)

A data engineer is designing a data pipeline that processes sensitive personal data. The data is ingested via Amazon Kinesis Data Firehose and stored in Amazon S3. The pipeline must ensure that the data is encrypted at rest and in transit. The engineer also needs to audit access to the data. Which combination of services meets these requirements?

A data engineer is using Amazon Kinesis Data Firehose to deliver streaming data to Amazon S3. The data is in JSON format, and the engineer needs to convert it to Parquet before storage to optimize Athena queries. The Firehose delivery stream is configured with an AWS Lambda function for record transformation. However, the transformed data is still in JSON format in S3. What is the likely cause?

A data engineer manages an AWS Glue job that processes JSON files from Amazon S3 and writes Parquet to another S3 location. The job intermittently fails with 'Unable to find catalog table' errors, even though the table exists in the Glue Data Catalog. The job's IAM role has full S3 access but only limited Glue permissions. Which action will resolve the failure with the LEAST privilege?

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 data engineer is using AWS Step Functions to orchestrate a series of AWS Glue jobs. One of the Glue jobs occasionally fails due to transient issues, such as a temporary network glitch. The engineer wants the Step Functions state machine to automatically retry that specific Glue job up to three times before moving to a failure state. Which Step Functions feature should be used to implement this?

A data engineer is using AWS Database Migration Service (AWS DMS) to migrate an on-premises Oracle database to Amazon Aurora PostgreSQL. The migration is ongoing, and the engineer needs to ensure that changes made to the source database during the migration are replicated to the target. The engineer has set up a full load plus change data capture (CDC) task. However, after the full load completes, the CDC task fails with an error indicating that it cannot find the archive log files. What should the engineer do to resolve this 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 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 company uses Amazon Kinesis Data Firehose to deliver streaming data to an Amazon S3 bucket. The data is then processed by a scheduled AWS Glue ETL job that loads it into an Amazon Redshift table. Recently, the Glue job has been failing with the error: 'S3ServiceException: Access Denied'. The Firehose delivery stream is configured with a prefix and error logging to the same S3 bucket. The Glue job uses the same IAM role that has s3:GetObject and s3:ListBucket permissions on the bucket. What is the most likely cause?

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 pipeline that ingests streaming data into Amazon S3 using Amazon Kinesis Data Firehose. The data must be delivered to S3 in Parquet format and partitioned by date. The engineer needs to configure the Firehose delivery stream. Which two actions are required to meet these requirements? (Choose two.)

A data engineer is using AWS Lake Formation to manage permissions on a data lake in Amazon S3. The engineer grants SELECT permission on a table to an IAM role used by an Amazon Athena user. However, the user reports that queries against the table return an 'Access Denied' error. The engineer verifies that the IAM role has the necessary S3 permissions and that Lake Formation permissions are correctly set. What is the most likely cause of the error?

A data engineer is using AWS Step Functions to orchestrate a series of AWS Glue jobs and Amazon EMR steps as part of a nightly ETL pipeline. The pipeline occasionally fails due to transient issues such as Amazon S3 throttling or temporary network errors. The engineer wants to make the workflow more resilient without duplicating the entire state machine. Which Step Functions feature should be used to automatically retry failed states?

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 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 data engineer is using AWS Step Functions to orchestrate a series of AWS Glue jobs that process data in Amazon S3. The engineer needs to ensure that if a Glue job fails, the entire workflow stops and an Amazon SNS notification is sent. Which Step Functions state type should be used to handle the error and send the notification?

A data engineer manages an AWS Glue ETL job that reads CSV files from Amazon S3 and writes Parquet to another S3 prefix. The job recently started failing with the error 'AnalysisException: Unable to infer schema for CSV.' The engineer confirms the S3 path contains files and the IAM role has s3:GetObject permissions. The job's script uses glueContext.create_dynamic_frame.from_catalog with a database and table name. What is the MOST likely cause?

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?

Which TWO actions are effective ways to monitor the health of an Amazon DynamoDB table? (Choose two.)

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 uses AWS CloudTrail to investigate a security incident. The engineer runs the command shown in the exhibit. What does the output indicate?

A data engineer is using AWS Step Functions to orchestrate an ETL workflow that includes an AWS Glue job, an Amazon EMR step, and an Amazon Redshift stored procedure. The workflow sometimes fails due to transient errors, and the engineer wants to implement a retry strategy that avoids duplicate data processing. Which TWO actions should the engineer take? (Choose two.)

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 data engineer manages an AWS Glue ETL job that processes JSON files from an S3 bucket and writes Parquet to another bucket. The job uses a Glue DynamicFrame with a specified schema. During execution, the job fails with the error: 'AnalysisException: cannot resolve column 'transaction_id' given input columns: [txn_id, amount, timestamp]'. The source data has a column named 'txn_id', but the Glue job's script references 'transaction_id'. The job's catalog table for the source points to the correct S3 location and has the correct schema. What is the most likely cause of this error?

A data engineer manages an Amazon Kinesis Data Stream with multiple shards. The stream is experiencing high throughput, and the engineer notices that some shards are throttling while others are underutilized. The engineer needs to redistribute the data evenly across shards to avoid throttling. Which action should the engineer take?

A data engineer needs to grant an AWS Lambda function permission to read objects from a specific Amazon S3 bucket. The Lambda function assumes an IAM role. Which policy should the engineer attach to the IAM role to allow the Lambda function to read objects from the bucket?

Which THREE are best practices for managing data in Amazon S3 for a data lake? (Choose three.)

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

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 investigating intermittent failures in an AWS Step Functions state machine that orchestrates a nightly ETL workflow. The state machine invokes an AWS Glue job, then an Amazon EMR step, then an AWS Lambda function. Occasionally a task fails transiently and the entire workflow stops instead of retrying. The engineer needs the workflow to automatically retry failed tasks with exponential backoff before alerting. What should the engineer do?

A data engineer is using Amazon Athena to query data stored in Amazon S3. The engineer notices that queries are returning incorrect results, specifically missing some rows that are known to exist in the underlying data. The data is stored in Parquet format and is partitioned by date. The engineer runs a query with a WHERE clause on the date partition and finds that some dates are missing from the results. The S3 bucket contains folders for each date, but some folders are empty. What is the MOST likely cause of the missing rows?

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 data engineer is using AWS Step Functions to orchestrate a complex ETL workflow that includes multiple AWS Glue jobs, Amazon EMR steps, and AWS Lambda functions. The engineer notices that on rare occasions, the entire workflow fails due to a transient error in one of the Lambda functions. The engineer wants to make the workflow more resilient without changing the overall architecture. Which approach is the MOST effective?

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.)

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?

Which THREE are valid considerations when troubleshooting data loss in an AWS Glue ETL job? (Choose three.)

A data engineer is setting up a data pipeline using Amazon Kinesis Data Firehose to deliver data to Amazon S3. The data must be transformed using an AWS Lambda function before delivery. Which THREE steps are required to configure this?

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 engineer is monitoring an AWS Glue job that reads from an Amazon S3 bucket and writes to Amazon Redshift. The job has been running for 2 hours, which is longer than usual. The engineer checks the Glue job's metrics and sees that the number of active executors is high, but the job is not making progress. The engineer suspects a data skew issue. Which action should the engineer take to diagnose and mitigate the skew?

A data engineer is using Amazon Kinesis Data Streams to ingest real-time data. The stream has 4 shards and is receiving 2 MB/s of data. The engineer notices that the WriteProvisionedThroughputExceeded metric is increasing. The engineer wants to resolve this issue with minimal changes. What should the engineer do?

A company uses Amazon Kinesis Data Firehose to deliver streaming data to Amazon S3. The data is in JSON format, and each record is approximately 5 KB. The company has set the buffer interval to 60 seconds and the buffer size to 5 MB. However, the data engineer observes that the delivery to S3 is delayed by up to 5 minutes during peak traffic. The engineer wants to reduce the delivery latency to under 1 minute. Which TWO actions should the engineer take? (Choose TWO.)

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

A data engineer is troubleshooting a slow Amazon Redshift query. The query scans a large table with interleaved sort keys. The engineer notices that the query plan shows a sequential scan instead of a range-restricted scan. What is the MOST likely reason?

A data engineer is using AWS Glue job bookmarks to process incremental data from Amazon S3. The job reads from a partitioned S3 path and writes to Amazon Redshift. After a recent run, the engineer notices that some new partitions were not processed. The job bookmark state shows that the job has already processed up to a certain timestamp. What is the most likely reason for the missing partitions?

A data engineer is using AWS Glue to run a PySpark ETL job that processes millions of small JSON files stored in an Amazon S3 bucket. The job is experiencing high memory usage and failing with 'Container killed by YARN for exceeding memory limits'. The engineer wants to optimize the job to handle the data more efficiently without changing the source data format. Which solution will MOST effectively reduce memory usage and improve performance?

A data engineer is troubleshooting an AWS Glue job that writes data to an Amazon S3 bucket in Parquet format. The job runs successfully but the output files are smaller than the configured 'groupFiles' size. The engineer has set 'groupFiles' to 'inPartition' and 'groupSize' to 1 GB. The input data is 10 GB in a single partition. What is the most likely reason for the small files?

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?

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 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?

A data engineer is using AWS Lake Formation to manage access to a data lake stored in Amazon S3. The engineer grants SELECT permission on a table in the AWS Glue Data Catalog to an IAM role used by an Amazon Athena user. However, the user still cannot query the table and receives an 'Access Denied' error. The engineer verifies that the IAM role has the necessary AWS Lake Formation permissions and that the S3 bucket policy allows access. What is the most likely cause of the issue?

A data engineer maintains an Amazon Kinesis Data Firehose delivery stream that writes JSON records to Amazon S3 and then invokes an AWS Lambda function for transformation. The Lambda function occasionally times out, causing records to be delivered untransformed. The engineer must ensure failed records are captured for later reprocessing without blocking delivery. What should the engineer do?

A data engineer is using Amazon Managed Workflows for Apache Airflow (MWAA) to orchestrate a data pipeline. The pipeline includes a task that runs an AWS Glue job. The engineer notices that the Glue job occasionally fails due to transient issues, and the Airflow task fails immediately without retrying. The engineer wants to configure the Airflow task to retry the Glue job up to 2 times with a 5-minute delay between retries. Which configuration in the Airflow DAG should the engineer use?

A data engineer is using AWS Database Migration Service (AWS DMS) to replicate ongoing changes from an Amazon RDS for MySQL database to an Amazon S3 bucket in Parquet format. The replication task is configured with full load plus change data capture (CDC). After several hours, the engineer notices that the S3 bucket contains only the full load data and no incremental changes. Which action should the engineer take to ensure CDC changes are captured?

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 data engineer is optimizing an AWS Glue ETL job that processes large Parquet files in Amazon S3. The job currently takes several hours to complete. The engineer wants to improve performance by tuning the job's execution parameters. Which TWO actions will MOST effectively reduce the job's runtime? (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 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 engineer is designing a data pipeline that ingests streaming data from an IoT device fleet. The data must be processed in near real-time and stored in Amazon S3 for long-term analytics. Which TWO AWS services should the engineer use together to achieve this?

A data engineer is troubleshooting an AWS Glue ETL job that fails with an 'Access Denied' error when trying to write to an S3 bucket. The IAM role used by the job has the policy shown in the exhibit. The bucket 'my-bucket' uses S3 default encryption with AWS KMS. What is the most likely missing permission?

A data engineer is using AWS Step Functions to orchestrate a series of AWS Glue jobs. The engineer notices that when a Glue job fails, the Step Functions execution also fails, but the engineer wants to retry the failed job up to three times with exponential backoff before failing the entire workflow. The engineer needs to implement this with minimal changes to the state machine. What should the engineer do?

A data engineer is using AWS Step Functions to orchestrate a series of AWS Glue jobs. During a recent run, a Glue job failed due to a transient network issue, and the Step Functions execution stopped. The engineer needs to ensure that the workflow can automatically retry the failed Glue job up to three times before considering the step failed. Which Step Functions state configuration should the engineer implement?

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 data engineer is using Amazon Athena to query data stored in Amazon S3 in Parquet format. The engineer notices that a specific query is scanning much more data than expected, resulting in high costs and slow performance. The query filters on a column named 'event_date' which is a string in 'YYYY-MM-DD' format. The table is partitioned by 'year', 'month', and 'day' as separate string columns. The engineer wants to reduce the amount of data scanned. Which action should the engineer take?

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 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 data engineer is using AWS Glue to run an ETL job that reads from an Amazon RDS for PostgreSQL database and writes to Amazon S3. The job is configured with a JDBC connection to RDS. The engineer notices that the job fails intermittently with a 'Connection timed out' error. The RDS instance is in a private subnet, and the Glue job has been configured with a VPC connection. Which action should the engineer take to resolve the timeout 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?

A company uses Amazon S3 to store log files from multiple applications. The logs are written in JSON format. A data engineer wants to use Amazon Athena to query these logs. The logs are stored in a bucket with the following structure: 's3://logs/app1/date=2021-01-01/'. The engineer creates an Athena table with partitions. However, when querying, Athena returns zero results for partitions that exist. The engineer has run MSCK REPAIR TABLE to add partitions. What is the most likely cause of 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 data engineer manages an AWS Glue ETL job that reads JSON files from Amazon S3, transforms the data, and writes to an Amazon Redshift table. The job recently started failing with the error 'Communication link failure: connection reset'. The Redshift cluster is healthy and the IAM role used by the Glue job has the necessary permissions. The engineer notices that the job runs longer than before and the Redshift cluster's WLM queue is often full. Which action should the engineer take to resolve the failure?

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 managing an Amazon Kinesis Data Firehose delivery stream that writes to an Amazon S3 bucket. The engineer notices that some records are being delivered to the S3 bucket with a prefix of 'errors/' instead of the intended 'data/' prefix. The Firehose stream is configured with an AWS Lambda function for data transformation, and the S3 bucket has a lifecycle policy that transitions objects to Glacier after 30 days. Which TWO actions should the engineer take to ensure that only successfully transformed records are delivered to the 'data/' prefix and that failed records are handled appropriately? (Choose two.)

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 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 data engineer maintains an Amazon Redshift cluster where a nightly COPY job loads data into a large fact table. After the load, analysts run queries that filter on a `sale_date` column and join to a small dimension table. Query performance degrades over time as the fact table grows. The engineer wants to improve performance for these recurring queries without changing the query text. Which combination of actions should the engineer take?

A data engineer manages an AWS Glue ETL job that reads from an Amazon S3 bucket and writes to an Amazon Redshift table. The job runs daily and recently started failing with the error 'Unable to find a suitable security group for the connection'. The Glue connection is configured with a VPC, subnet, and security group. The engineer verifies that the IAM role has the necessary permissions and the S3 bucket is accessible. What is the most likely cause of this error?

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 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 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 troubleshooting an AWS Glue ETL job that fails with a 'java.lang.OutOfMemoryError: Java heap space' error. The job processes a 50 GB Parquet file from an S3 bucket. The job uses a G.1X DPU (16 GB memory) and default parameters. Which action should the engineer take to resolve the issue?

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?

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 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 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 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 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?

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 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?

A data engineer is using Amazon Kinesis Data Firehose to deliver streaming data to an Amazon S3 bucket. The engineer notices that some records are being delivered to S3 with a delay of several minutes, and sometimes records are missing. The Firehose stream is configured with a buffer size of 5 MB and a buffer interval of 300 seconds. The engineer wants to reduce latency and ensure all records are delivered. Which action should the engineer take?

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?

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 manages an AWS Glue job that processes JSON files from Amazon S3 and writes to Amazon Redshift. The job fails with the error "Unable to find a suitable JDBC driver". The engineer has verified that the Glue connection to Redshift is configured correctly and the IAM role has the necessary permissions. What is the most likely cause of this error?

A data engineer is building an AWS Glue ETL job that reads from an Amazon S3 bucket containing CSV files and writes to an Amazon Redshift table. The job runs successfully but the Redshift table ends up empty. The engineer checks the AWS Glue job run metrics and sees that the job processed 0 rows. The S3 bucket contains files under the prefix 'data/'. The Glue crawler created a table with the correct schema. What is the MOST likely cause of the empty output?

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?

A data engineer needs to monitor the performance of an Amazon Redshift cluster. Which Amazon CloudWatch metric should the engineer monitor to detect disk space issues?

A data engineer is using AWS Step Functions to orchestrate a data pipeline that includes an AWS Glue job, an Amazon EMR step, and an Amazon Redshift stored procedure. The engineer needs to ensure that if the AWS Glue job fails, the pipeline retries the job up to three times before failing the entire execution. Which Step Functions state should the engineer use to implement this retry logic?

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 is using Amazon Athena to query data stored in Amazon S3. The engineer notices that queries are slow and scan large amounts of data. The data is stored in CSV format without compression. Which action should the engineer take to improve query performance and reduce cost?

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 uses Amazon Kinesis Data Streams to ingest clickstream data. The data is consumed by an AWS Lambda function that processes each record and writes to an Amazon DynamoDB table. Recently, the Lambda function has been failing with 'ProvisionedThroughputExceededException' from DynamoDB. The Lambda function uses the AWS SDK to batch write items in batches of 25. The DynamoDB table has on-demand capacity mode. The stream has 10 shards, and the Lambda function is configured with a batch size of 100 and 5 concurrent invocations per shard. What step should the team take to resolve the issue?

A data engineer is troubleshooting an AWS Glue job that is reading from an Amazon Kinesis Data Stream. The job is configured with a 1-minute window and is supposed to process the latest records. However, the engineer notices that the job is reprocessing old data from the stream. What is the most likely cause of this issue?

A data engineer is using AWS Step Functions to orchestrate a series of AWS Glue jobs and Amazon EMR steps. The state machine has a task that starts a Glue job and waits for completion using the 'StartJobRun' API with the 'sync' integration. Occasionally, the Step Functions execution fails with the error: 'States.TaskFailed: Glue job failed with error: ResourceNumberLimitExceededException'. The engineer confirms that the Glue job itself runs successfully when triggered manually. What is the most likely cause of this intermittent failure?

A data engineer needs to schedule a recurring AWS Glue ETL job to run every day at 2:00 AM UTC. The job must be triggered automatically without manual intervention. Which AWS service should the engineer use to create this schedule?

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?

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 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 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 managing an Amazon Redshift cluster and needs to load data from Amazon S3. The engineer uses the COPY command but encounters the error: 'S3ServiceException: Access Denied.' The Redshift cluster has an IAM role attached with permissions to access the S3 bucket. What is the most likely cause of this error?

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 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 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 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 Amazon S3 to store raw data files. They have an AWS Glue ETL job that reads from an S3 bucket, transforms the data, and writes to a Redshift cluster. The job runs daily and has been failing intermittently with the error: 'An error occurred while calling o143.pyWriteDynamicFrame. S3 Access Denied'. The team has confirmed that the IAM role used by the Glue job has s3:GetObject and s3:PutObject permissions on the bucket and all objects. The Redshift cluster is in the same VPC and the Glue connection is configured correctly. What is the most likely cause of the failure?

A data engineer manages an AWS Glue ETL job that writes Parquet files to Amazon S3. Downstream Amazon Athena queries started returning duplicate rows after the job was modified to enable job bookmarks. The job reads from an S3 source prefix where new files are appended hourly and the transformation includes a join that reorders records. Which action will most reliably eliminate the duplicate rows while preserving incremental processing?

A data engineer is using Amazon Athena to query Parquet data in Amazon S3. Queries are slow and scan more data than expected. The data is partitioned by year/month/day in S3, but the AWS Glue Data Catalog table has no partition metadata. Which action will improve query performance and reduce data scanned?

A data engineer manages an AWS Glue ETL job that reads JSON files from Amazon S3 and writes to Amazon Redshift. The job recently started failing with the error: 'Unable to find catalog table' when trying to access a table in the AWS Glue Data Catalog. The engineer confirms that the table exists in the Data Catalog and that the IAM role used by the job has glue:GetTable permissions. What is the most likely cause of this error?

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 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 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 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 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 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 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 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 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 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 company uses Amazon S3 to store raw data and AWS Glue to run ETL jobs. The data is partitioned by date in the format 'year=YYYY/month=MM/day=DD'. A new data source started sending data with a different date format 'YYYY-MM-DD'. The Glue crawler is configured to create a single table for the entire bucket. The crawler runs daily, but it is not detecting the new partitions from the new data source. The existing partitions are in the format 'year=2024/month=05/day=10', while the new data is stored as '2024-05-10/' without the key-value structure. How should the engineer modify the data pipeline to include the new data?

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 needs to ensure that an AWS Glue job has access to an Amazon RDS database in a private subnet. The Glue job will run in a VPC and requires a security group and subnet configuration. Which combination of steps should the engineer take?

A data engineering team is troubleshooting a failing AWS Glue ETL job that processes data from an S3 bucket. The job writes output to another S3 bucket. The job fails with an AccessDenied error when writing to the output bucket. The IAM role used by the job has the following policy attached: {"Version":"2012-10-17","Statement":[{"Effect":"Allow","Action":["s3:GetObject","s3:ListBucket"],"Resource":["arn:aws:s3:::input-bucket/*","arn:aws:s3:::input-bucket"]}]}. What is the most likely cause of the failure?

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?

Which TWO are valid approaches to troubleshoot a slow Amazon Redshift query? (Choose two.)

A data engineer is using AWS Step Functions to orchestrate a series of AWS Glue jobs. The state machine includes a task that runs an AWS Glue job and then waits for its completion. The engineer notices that the Step Functions execution times out after 15 minutes, even though the Glue job takes about 30 minutes to complete. The Step Functions state machine has a timeout of 1 hour. What is the most likely cause of the timeout?

A data engineer is using AWS Step Functions to orchestrate a series of AWS Glue jobs. One of the Glue jobs occasionally fails due to transient network issues. The engineer wants the Step Function to retry the failed Glue job up to 3 times with exponential backoff before failing the entire workflow. Which Step Functions state configuration should be used?

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 is optimizing an AWS Glue ETL job that reads from Amazon S3 and writes to Amazon Redshift. The job currently uses a single large file and takes hours to complete. The engineer wants to improve performance by using partitioning and parallelism. Which TWO actions should the engineer take? (Choose two.)

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 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 runs an Apache Spark application on Amazon EMR that writes partitioned Parquet output to Amazon S3. A downstream AWS Glue crawler registers the table in the Data Catalog, but Athena queries return zero rows for partitions added by the most recent run, while older partitions query correctly. The S3 objects exist and are readable. Which action should the engineer take?

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 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 data engineer maintains an AWS Glue ETL job that processes JSON files from Amazon S3 and writes Parquet to another S3 location. The job has been running successfully for months. Recently, the job started failing intermittently with the error 'Unable to infer schema for JSON'. The engineer confirms the source bucket contains valid JSON files. Which action should the engineer take to resolve the failure?

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 maintains an Amazon Kinesis Data Streams pipeline that feeds an AWS Lambda consumer. During traffic spikes, the Lambda function is throttled and records are reprocessed, causing duplicate entries in the downstream Amazon S3 sink. The engineer needs to reduce duplicates with the LEAST code change. What should the engineer do?

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?

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 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?

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 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 company uses AWS Glue to run ETL jobs that process data from an Amazon RDS for MySQL database and load it into an Amazon S3 data lake. The Glue job runs daily and processes incremental data. Recently, the job has been taking longer than expected. The engineer checks the CloudWatch logs and sees that the job is spending most of its time on the 'Reading from JDBC' phase. The MySQL table has 10 million rows and is indexed on the primary key. The Glue job uses a 'job bookmark' to track processed data. The engineer wants to improve the performance of the read phase. Which action is most likely to help?

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?

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

A company runs a daily batch processing job on Amazon EMR that reads data from Amazon S3 and writes results back to S3. The job takes longer than expected. The engineer wants to monitor the job's resource utilization. Which AWS service should be used to collect and visualize metrics such as CPU and memory usage of the EMR cluster's nodes?

A data engineer is using AWS Step Functions to orchestrate a data pipeline that includes an AWS Glue job, an Amazon EMR step, and an Amazon Redshift stored procedure. The engineer needs to ensure that if the Glue job fails, the pipeline stops and does not proceed to the EMR step. Which Step Functions state type should be used to handle the error and stop the execution?

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 is using Amazon Athena to query data stored in Amazon S3. The data is partitioned by date, but the engineer notices that queries are scanning the entire bucket instead of only the relevant partitions. The table is defined in the AWS Glue Data Catalog. Which action should the engineer take to ensure that Athena only scans the necessary partitions?

A data engineer is using Amazon Kinesis Data Streams to ingest real-time data. The engineer needs to ensure that records are delivered to consumers in the same order they were written and that each record is processed exactly once. Which combination of Kinesis Data Streams features should the engineer use?

A data engineer maintains an AWS Glue Data Catalog table for an S3-based dataset. After new files were added, queries in Amazon Athena fail with the error 'HIVE_BAD_DATA: Error parsing field value for field 3: For input string: "N/A"'. The column is defined as bigint in the Data Catalog but contains the string 'N/A' in some records. Which action should the data engineer take to allow Athena to query the data without changing the underlying files?

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?

A data engineer is monitoring an AWS Glue job that reads from Amazon S3 and writes to Amazon Redshift. The job runs daily and recently started taking significantly longer to complete. The engineer checks the job metrics and notices that the number of DPUs used is consistently at the maximum allocated, and the job's Spark UI shows many tasks spilling to disk. Which action should the engineer take to improve performance?

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 maintains an AWS Glue ETL job that reads from an Amazon Kinesis Data Streams stream and writes to Amazon S3 in Parquet format. The job has been running successfully, but after the data volume increased threefold, the job now fails with an error stating that the Glue job's bookmarks are not advancing and the job is reprocessing old data. The engineer has enabled job bookmarks with the default settings. Which action should the engineer take to resolve the issue?

A data engineer has an AWS Glue job that reads JSON files from Amazon S3, applies transformations, and writes Parquet files to another S3 location. The job runs daily and takes about 2 hours. Recently, the job has been failing intermittently with an error indicating that the job bookmark is not being updated correctly, causing duplicate processing of some files. The engineer needs to ensure that only new files are processed on each run. Which action should the engineer take to resolve this issue?

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 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?

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 stores raw event files in an Amazon S3 bucket that receives thousands of small objects per hour. An AWS Glue job reads the prefix and writes a compacted Parquet dataset to a curated bucket. Operations reports that the Glue job's runtime keeps growing even though the hourly data volume is constant. Which change is MOST likely to reduce runtime?

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 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 data engineer is using Amazon Kinesis Data Streams to ingest clickstream data. The stream has 10 shards and each record is 50 KB. The engineer notices that the PutRecords API is frequently returning ProvisionedThroughputExceededException errors, even though the total incoming data rate is below the stream's overall capacity. What is the MOST likely cause?

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 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 data engineer is using AWS Step Functions to orchestrate a series of AWS Glue jobs. The engineer notices that one of the Glue jobs occasionally fails due to a transient network error. The engineer wants to implement a retry mechanism that retries the failed job up to three times with an exponential backoff. Which Step Functions state configuration should the engineer use?

A company stores raw clickstream data in an Amazon S3 bucket and uses AWS Glue crawlers to populate the AWS Glue Data Catalog. Analysts report that new partitions are not appearing in Amazon Athena queries even though new date-based folders exist in S3. The crawler runs successfully each night. What is the MOST likely cause?

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 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 data engineer is managing an Amazon Redshift cluster that experiences performance degradation during peak query hours. The engineer notices that many queries are waiting in the queue, and the WLM query queue wait time is high. The cluster uses automatic WLM. Which action should the engineer take to improve query throughput?

A data engineer is troubleshooting an Amazon Redshift cluster where nightly COPY loads from Amazon S3 are intermittently slow and sometimes fail with 'S3ServiceException' errors. The engineer suspects the cluster's network configuration and load design are contributing. Which TWO actions should the engineer take to improve load performance and reliability? (Choose two.)

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 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 uses Amazon S3 as a data lake. A data engineer needs to ensure that all objects uploaded to the 'incoming' prefix are automatically encrypted at rest using AWS KMS with a specific customer managed key. What is the simplest way to enforce this?

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 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 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 monitoring an Amazon Kinesis Data Stream used to ingest clickstream data. The engineer notices that the stream's 'WriteProvisionedThroughputExceeded' metric is frequently above zero. Which TWO actions could help mitigate this issue? (Choose TWO.)

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 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 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 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 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 data engineer is using AWS Database Migration Service (AWS DMS) to migrate an on-premises Oracle database to Amazon Redshift. The migration uses a full load plus change data capture (CDC). During the CDC phase, the engineer notices that some updates are not being applied to the target Redshift tables. The DMS task logs show no errors. What is the MOST likely cause?

A company is ingesting streaming data from thousands of IoT devices into Amazon Kinesis Data Streams. The data is processed by a Kinesis Data Analytics application. Recently, the application started reporting high iterator age (millisBehindLatest). Which action would BEST reduce the iterator age?

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 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?