A company is using an AWS Lambda function to run Amazon Athena queries against a cross-account AWS Glue Data Catalog. A query returns the following error:
HIVE METASTORE ERROR
The error message states that the response payload size exceeds the maximum allowed payload size. The queried table is already partitioned, and the data is stored in an
Amazon S3 bucket in the Apache Hive partition format.
Which solution will resolve this error?
A company uses Amazon EC2 instances to receive files from external vendors throughout each day. At the end of each day, the EC2 instances combine the files into a single file, perform gzip compression, and upload the single file to an Amazon S3 bucket. The total size of all the files is approximately 100 GB each day.
When the files are uploaded to Amazon S3, an AWS Batch job runs a COPY command to load the files into an Amazon Redshift cluster.
Which solution will MOST accelerate the COPY process?
A company wants to use a data lake that is hosted on Amazon S3 to provide analytics services for historical dat
a. The data lake consists of 800 tables but is expected to grow to thousands of tables. More than 50 departments use the tables, and each department has hundreds of users. Different departments need access to specific tables and columns.
Which solution will meet these requirements with the LEAST operational overhead?
A social media company is using business intelligence tools to analyze data for forecasting. The company is using Apache Kafka to ingest dat
a. The company wants to build dynamic dashboards that include machine learning (ML) insights to forecast key business trends.
The dashboards must show recent batched data that is not more than 75 minutes old. Various teams at the company want to view the dashboards by using Amazon QuickSight with ML insights.
Which solution will meet these requirements?
A company uses Amazon Connect to manage its contact center. The company uses Salesforce to manage its customer relationship management (CRM) dat
a. The company must build a pipeline to ingest data from Amazon Connect and Salesforce into a data lake that is built on Amazon S3.
Which solution will meet this requirement with the LEAST operational overhead?
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