Prepare 4 interview - Recent questions and answers in Greenplum Database Interview Questions and Answers

Answered: Tell me about the Greenplum Architecture

Fri, 15 Jul 2011 07:17:58 +0000

Greenplum Database is able to handle the storage and processing of large amounts of data by distributing the load across several servers or hosts. A database in Greenplum is actually an array of individual PostgreSQL databases, all working together to present a single database image. The master is the entry point to the Greenplum Database system. It is the database instance where clients connect and submit SQL statements. The master coordinates the work amongst the other database instances in the system, the segments, which handle data processing and storage.

Answered: How to create and use Greenplum External tables?

Fri, 15 Jul 2011 06:48:35 +0000

The CREATE EXTERNAL TABLE command creates an external table definition in Greenplum Database. External table data is considered static (meaning the data does not change midstream during the execution of a query). This allows the query planner to choose plans that allow for rescanning of the external table data.

You may specify multiple external data sources or URIs (uniform resource identifiers) with the LOCATION clause — up to the number of primary segment instances in your Greenplum Database array. Each URI points to an external data file or data source. These URIs do not need to exist prior to defining an external table (CREATE EXTERNAL TABLE does not validate the URIs specified). However you will get an error if they cannot be found when querying the external table.

There are two protocols that you can use to access the external table data sources.
1. gpfdist
2. file

Answered: What is the difference between external tables and web tables of Greenplum database?

Fri, 15 Jul 2011 06:23:53 +0000

The main difference between external tables and web tables are their data sources. External tables access static flat files, whereas web tables access dynamic data sources — either on a web server or by executing OS commands or scripts. When a query is planned using an external table, the external table is considered rescannable since the data is thought to be static for the course of the query. For web tables, the data is not rescannable because there is the possibility that the data could change during the course of the query’s execution.

Answered: What is external tables and web tables in Greenplum database?

Fri, 15 Jul 2011 06:22:30 +0000

External tables and web tables provide an easy way to perform basic extraction, transformation, and loading (ETL) tasks that are common in data warehousing. External and web table data is read in parallel by the Greenplum Database segment instances, so they also provide a means for fast data loading.

Once an external or web table is defined, its data can be queried directly (and in parallel) using SQL commands. You can, for example, select, join, or sort external or web table data. You can also create views for external or web tables. However external and web tables are read-only. DML operations (UPDATE, INSERT, DELETE, or TRUNCATE) are not allowed, and you cannot create indexes on external or web tables.

An external or web table definition can be thought of as a view that allows running any SQL query against external data sources without requiring that data to first be loaded into the database. External and web tables provide an easy way to perform basic extraction, transformation, and loading (ETL) tasks that are common in data warehousing. External and web table files are read in parallel by the Greenplum Database segment instances, so they also provide a means for fast data loading.

Answered: What is Greenplum database?

Fri, 15 Jul 2011 06:19:23 +0000

Greenplum Database is a massively parallel processing (MPP) database server based on PostgreSQL open-source technology. MPP (also known as a shared nothing architecture) refers to systems with two or more processors which cooperate to carry out an operation - each processor with its own memory, operating system and disks. Greenplum leverages this high-performance system architecture to distribute the load of multi-terabyte data warehouses, and is able to use all of a system’s resources in parallel to process a query.