Sqoop is designed to handle and ingest large amounts of structured data, such as SQL tables.
Explanation: If complex function calls are specified, then the --where parameter imposes a significant burden on the database server. Also, some functions lead to locking tables, which prevents Sqoop from transferring data in parallel. This, in turn, affects performance.
Explanation: Correct. Sqoop jobs are used to copy/transfer data from a relational database to a Hadoop cluster/HDFS. No aggregation work is done using Sqoop jobs. Therefore, these jobs are map-only.
Sqoop provides an incremental import mode, which can be used to retrieve only those rows that are newer than some previously imported set of rows.
Sqoop is not an event-driven data ingestion tool.
Sqoop is mainly used for dealing with structured data from RDBMSs.
Explanation: If a job exceeds a pre-defined number of Reads and Writes, the job might fail.
Sqoop jobs can be easily set up to automate operations such as incremental import.
