DAS-C01 · Question #89
A company has collected more than 100 TB of log files in the last 24 months. The files are stored as raw text in a dedicated Amazon S3 bucket. Each object has a key of the form year-month- day_log_HHm
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Question
A company has collected more than 100 TB of log files in the last 24 months. The files are stored as raw text in a dedicated Amazon S3 bucket. Each object has a key of the form year-month- day_log_HHmmss.txt where HHmmss represents the time the log file was initially created. A table was created in Amazon Athena that points to the S3 bucket. One-time queries are run against a subset of columns in the table several times an hour. A data analyst must make changes to reduce the cost of running these queries. Management wants a solution with minimal maintenance overhead. Which combination of steps should the data analyst take to meet these requirements? (Choose three.)
Options
- AConvert the log files to Apace Avro format.
- BAdd a key prefix of the form date=year-month-day/ to the S3 objects to partition the data.
- CConvert the log files to Apache Parquet format.
- DAdd a key prefix of the form year-month-day/ to the S3 objects to partition the data.
- EDrop and recreate the table with the PARTITIONED BY clause. Run the ALTER TABLE ADD
- FDrop and recreate the table with the PARTITIONED BY clause. Run the MSCK REPAIR TABLE
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