It is virtual table which is defined as a stored procedure based on one or more tables.

- Rename : It is a permanent name provided to a table or column.
- Alias : It is a temporary name provided to a table or column which gets over after the execution of SQL statement.

- TABLES
- VIEWS
- INDEXES
- SYNONYMS
- SEQUENCES
- TABLESPACES

ANALYZE command is used to perform various functions on index, table, or cluster, as listed below:
- It helps in dentifying migrated and chained rows of the table or cluster.
- It helps in validating the structure of the object.
- It helps in collecting the statistics about object used by the optimizer. They are then stored in the data dictionary.
- It helps in deleting statistics used by object from the data dictionary.

In a mapreduce job the master pings each worker periodically. In case a worker does not respond to that system then the system is marked as failed. Even completed tasks are rescheduled because the output was stored in a in a local disk of a worker which failed. Hence mapreduce is able to handle large-scale failures easily by simply restarting a task. The master node always saves itself at checkpoints and in case of any failure it simply restarts from that checkpoint.

The mapreduce framework contains most of the key architecture principles of cloud computing such as:

- Scale: The framework is able to expand itself in direct proportion to the number of machines available.

- Reliable: The framework is able to compensate for a lost node and restart the task on a different node.

- Affordable: A user can start small and over time can add more hardware.

- Multi-threading fetching in Amazon S3 is used to fetch the objects concurrently using the multiple threads and map the task so that fetching can be made simpler. 

- It is not a good practice to increase the threading for a particular object as every node on the server has some bandwidth constraints. 

- It provides user the ease with which they can upload the files and upload the threads in parallel. 

- It provides high speed of data transfer and easy maintenance of the sever as well.

Amazon S3 provides uploading of large files and retrieve small offsets for end-to-end transfer data rates. The large file gets stored into small files that are smaller in size. Amazon S3 stores multiple of files together in a bundle or in a compressed form, For example in .gzip or .gz format and then convert them into Amazon S3 objects. The files get uploaded on the Amazon server by the use of FTP or another protocol and then retrieved through the HTTP GET request. The request includes the defined parameters like URL, offset (byte-range) and size (length).