A data engineer is processing a large amount of log data from web servers.

Use Amazon EMR to run Apache Hive queries on the raw log files in the S3 bucket to extract the specified fields. Store the output as ORC files in the original S3 bucket.

Use AWS Step Functions to orchestrate a series of AWS Batch jobs to parse the raw log files. Load the specified fields into an Amazon RDS for PostgreSQL database.

Use an AWS Glue crawler to parse the raw log data in the S3 bucket and to generate a schema. Use AWS Glue ETL jobs to extract and transform the data and to load it into Amazon Redshift.

Use AWS Glue DataBrew to run AWS Glue ETL jobs on a schedule to extract the specified fields from the raw log files in the S3 bucket. Load the data into partitioned tables in Amazon Redshift.