Vectorization is a feature in Apache Hive that enables the processing of large volumes of data by performing operations on entire vectors of data at once. This can significantly improve query performance in Hive.

The primary role of a DataNode in Hadoop is to store and manage the actual data blocks. DataNodes are responsible for storing and retrieving data, and they communicate with the NameNode to report the health and availability of the data blocks they store.

Sqoop is a tool in the Hadoop ecosystem specifically designed for efficiently transferring data between Hadoop and relational databases. It facilitates the import of data from databases such as MySQL, Oracle, and others into the Hadoop Distributed File System (HDFS) for further processing.

In Hadoop, Ambari is used to configure the settings for various services in the cluster. Ambari provides a web-based interface to manage, monitor, and configure Hadoop services, making it easier for administrators to handle cluster settings.

The SequenceFile format in Hadoop is particularly suited for sequential data access. It is optimized for storing large amounts of data in a serialized, binary format, making it efficient for applications that require sequential read and write access, such as MapReduce tasks.