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Netezza interview questions and answers - Page 1

1. What is Netezza?

IBM Netezza is a powerful and highly parallelized Data Warehousing system that is simple to govern and to maintain. Netezza is purposefully built for data warehousing. The system is commonly referred to as data warehouse appliance that is designed specifically for running complex data warehousing workloads. The concept of an appliance is realized by integrating the database, server and the storage into an easy to deploy and manage system.

2. What is Database Accelerator in Netezza?

IBM Netezza uses commodity FPGA (Field-Programmable Gate Array) to make SQL closer to silicon.

This is the very important feature of Netezza since IO is always a problem in database management system.
Netezza leverages the IO processing by the effective usage of FPGA.
This core component of the appliance is referred to as the Database Accelerator.

3. What is nzload?

This is a wrapper command line tool around external tables that provides an easy method loading data into the Netezza appliance.

4. What are External Tables in Netezza?

These are tables stored as flat files on the host or client systems and registered like tables in the Netezza catalog. They can be used to load data into the Netezza appliance or unload data to the file system.

5. Advantages of Netezza architecture

The Netezza architecture combines the best elements of Symmetric Multiprocessing (SMP) and Massively Parallel Processing (MPP) to create an appliance purpose-built for analyzing petabytes of data quickly.

Every component of the architecture, including the processor, FPGA, memory, and network, is carefully selected and optimized to service data as fast as the physics of the disk allows, while minimizing cost and power consumption.

The Netezza software orchestrates these components to operate concurrently on the data stream in a pipeline fashion, thus maximizing utilization and extracting the utmost throughput from each MPP node. In addition to raw performance, this balanced architecture delivers linear scalability to more than a thousand processing streams executing in parallel, while offering a very economical total cost of ownership.