Intelligent Big Data SQL Assessment Test

The command "Codegen" helps to generate code to interact with database records. This command is specifically designed to generate code that allows developers to perform various operations on database records such as creating, reading, updating, and deleting. It automates the process of generating code, saving time and effort for developers. By using "Codegen", developers can easily generate the necessary code to interact with the database without having to manually write it from scratch.

The default file format for data import in Sqoop is the Delimited text file format. This format is commonly used for importing and exporting data between Hadoop and relational databases. Delimited text files store data in plain text format, with each record separated by a delimiter character, such as a comma or a tab. This format is widely supported and can be easily processed by various tools and applications.

Eval is the correct answer because it is a command in Sqoop that evaluates SQL statements and displays the results. It allows users to execute SQL queries directly from the command line and view the output. The Eval command is useful for testing and debugging SQL queries before running them in production.

Swoop imports copy data from RDBMS (Relational Database Management System). RDBMS is a software system that allows for the creation, management, and organization of relational databases. It is commonly used for storing and retrieving data in a structured format. Swoop, in this context, is likely a data integration or migration tool that utilizes RDBMS as a source for importing copy data.

A tool that hosts a shared metadata repository is called a metastore. This repository stores metadata information about various data sources, such as databases, tables, columns, and their properties. It acts as a central hub for managing and organizing metadata, allowing different tools and applications to access and utilize this information efficiently. The other options, Metallica, MetaStock, and Warehouse, are unrelated to the concept of a shared metadata repository.

The metastore database can be hosted both inside and outside the Hadoop cluster. This means that it can be located within the cluster itself, allowing for easy access and integration with other Hadoop components. Additionally, it can also be hosted outside the cluster, providing flexibility and the ability to access the metastore database from external systems or applications. This allows for greater scalability and the possibility of utilizing the metastore database for various purposes beyond the Hadoop cluster.

Sqoop is the best tool for transferring data between Hadoop and relational database servers. Sqoop is specifically designed for efficiently importing and exporting large amounts of data between Hadoop and structured datastores, such as relational databases. It provides a simple command-line interface that allows users to specify the source and target database, tables, and other parameters for data transfer. Sqoop also supports parallel data transfer, data compression, and incremental data imports, making it a powerful tool for efficiently moving data between Hadoop and relational databases.

The WHERE clause is used in SQL queries to filter the rows returned by a SELECT statement. It allows you to specify a condition that the rows must meet in order to be included in the result set. By using the WHERE clause, you can import only a subset of rows from a table by specifying the criteria that the rows must satisfy. This allows for more targeted and efficient data retrieval.

Sqoop export is the correct answer because it is a tool specifically designed to transfer data from HDFS (Hadoop Distributed File System) to RDBMS (Relational Database Management System). Sqoop is a command-line interface tool that allows users to import data from RDBMS into HDFS, as well as export data from HDFS into RDBMS. Therefore, Sqoop export is the appropriate tool for transferring data from HDFS to RDBMS.

In Sqoop merge, the dataset that is preserved is the new one. This means that when merging datasets using Sqoop, the new dataset will overwrite the old dataset, preserving the data from the new dataset and discarding the data from the old dataset. This ensures that the most up-to-date information is retained in the merged dataset.