Updated June 19, 2023
Introduction to Sqoop Interview Questions and Answers
Sqoop is an open-source data transfer tool; the scoop tool transfers the data between Hadoop Ecosystem and Relational Database Servers (RDBMS). It imports the Hadoop file system (HDFS) data from Relational Databases such as Oracle, MySQL, etc., and export data from the Hadoop File System to RDMS.
So you have finally found your dream job in Sqoop but are wondering how to crack the Sqoop interview and what the probable 2023 Sqoop Interview Questions could be. Every interview is different, and the job scope is different too. Keeping this in mind, we have designed the most common Sqoop Interview Questions and Answers to help you get success in your interview.
Below are the 15 crucial 2023 Sqoop Interview Questions and Answers. These questions are divided into two parts as follows:
Part 1 – Sqoop Interview Questions (Basic)
This first part covers basic Sqoop Interview Questions And Answers.
1. Define Sqoop, and why do we use Sqoop?
Answer:
Sqoop is an open-source tool that transfers data between Hadoop Ecosystem and Relational Database Servers (RDBMS). Sqoop is used to import data from Relational Databases such as Oracle, MySQL, etc., to the Hadoop file system (HDFS) and for exporting data from the Hadoop file system to relational databases.
2. What are the different features of Sqoop?
Answer:
- Loading capacity
- Total Loading and Incremental Loading
- Data Compression Techniques
- Importing the SQL queries results
- Data Connectors for all the major databases
- Direct data loading support into Hadoop File Systems
- Security configurations like Kerberos
- Concurrent Import or Export functionalities
Let us move to the following Sqoop Interview Questions.
3. Name the relational databases and Hadoop ecosystem sources supported in Sqoop.
Answer:
Sqoop currently supports MySQL, PostgreSQL, Oracle, MSSQL, Teradata, and IBM’s Netezza as part of Relation Databases.
Currently supported Hadoop Ecosystem destination services are HDFC, Hive, HBase, H Catalog, and Accumulo.
Sqoop uses MySQL as the default database.
4. How does Sqoop work?
Answer:
These are the common Sqoop Interview Questions asked in an interview. To perform data transfer, Sqoop uses export and import commands. The map Reduce program will be used in Sqoop internally for storing datasets in HDFS. Headquarters will be associated with Map tasks to retrieve data from Relational Databases; Reduce task will take the responsibility of placing the retrieved data into the destinations (HDFS/HBase/Hive)
Sqoop also uses various API connectors for connecting with several databases. Sqoop also provides the ability to create custom connectors for meeting specific requirements.
Let’s see the sample commands below for import and export.
A command for connecting to MySQL database for importing data from the ‘Log’ table
sqoop import --connect jdbc:mysql://localhost/<databasename> --username <USER_NAME> --password <PASSWORD> --table <tablename> --m 1
sqoop import --connect jdbc:mysql://localhost/mytestdb --username root --password admin123 --table log --m 1
A command for exporting data from HDFS to Relational Database
sqoop export --connect jdbc:mysql://localhost/sqoop_export –table <table_name> export-dir /sqoop/emp_last/part-m-00000 --update-key id
sqoop export --connect jdbc:mysql://localhost/sqoop_export --table log_table--export-dir /sqoop/data/foler1/part-m-00000
5. What is Sqoop Metastore? Explain it.
Answer:
The Sqoop Metastore is a tool available in the Sqoop which will be used to configure the Sqoop application to enable the hosting of a shared repository in the form of metadata. This Metastore can execute jobs and manage several users based on user roles and activities. All multiple users can perform various tasks or operations concurrently to achieve the tasks efficiently. The Sqoop megastore will be implemented as an in-memory representation by default. When a job is created within Sqoop, the job definition is stored inside the Metastore and will be listed using Sqoop jobs if needed.
6. What file formats does Sqoop support while importing the data?
Answer:
Sqoop uses two file formats for data import. They are:- Delimited Test File Format and Sequence File Format.
- Delimited Text File Format: Delimited Text Format is the default file format for importing. We can still explicitly specify using the –as-textile argument. Likewise, passing the argument will set the delimiter characters between rows and columns.
- Sequence File Format: In this file format, it’s a binary file format. This type of format file records is stored in custom record-specific data types exposed to Java Classes.
7. Can we control the number of mappers in a scoop? If yes, How?
Answer:
Yes, we can control the number of mappers in Sqoop by specifying “-num-mappers” in the sqoop command. This parameter can manage the number of map tasks; that is, nothing but the degree of parallelism will be used by sqoop.
- Syntax: Use these flags to control the number of mappers: m, -num- mappers
Part 2 – Sqoop Interview Questions (Advanced)
Let us now have a look at the advanced Sqoop Interview Questions.
1. What is Sqoop-merge, and explain its use?
Answer:
Sqoop merge is a tool that combines two different datasets that maintain the only version by overwriting the entries in an older version of a dataset with new files to make it the latest version dataset. There is a flattening process while merging the two different datasets, which preserves the data without any loss, efficiency, and safety. To perform this operation merge key command will be used like “–merge-key.”
2. What are the differences between Sqoop, flume, and distcp?
Answer:
In contrast, Sqoop transfers data between Relational databases and the Hadoop ecosystem, such as Hive, HDFS, HBase, etc. But both methods use the same approach to copy the data: pull/transfer.
Flume has distributed a tool that follows agent-based architecture to stream logs into the Hadoop ecosystem. At the same time, Sqoop is a connector-based architecture.
Flume collects and aggregates a massive amount of log data. Flume can collect data from different types of resources; it doesn’t consider the schema or structured/unstructured data. Flume can pull any data. In comparison, Sqoop can only import the Relational Database Data, so the schema is mandatory for sqoop to process. Generally, for moving bulk workloads, the flume is the best option.
Let us move to the following Sqoop Interview Questions.
3. What does Apache Sqoop support the data sources?
Answer:
The different data sources from various applications supported by Apache Sqoop are as below:
- Hive
- HBase
- Hadoop Distributed File System (HDFS)
- HCatalog
- Accumulation
4. What are the most used commands/functions in Sqoop?
Answer:
Interview Questions asked in an interview. The list of basic commands used in Sqoop is as follows:
- Codegen -Codegen is used to generate code to communicate with database records.
- Eval -Sqoop Eval helps run sample SQL queries against the databases and provides the results on the console.
- Help -Help list the available commands
- Import -Import will import the table into the Hadoop Ecosystem.
- Create-hive-table -This command helps import table definitions into Hive.
- Import-all-tables -Import-all-tables will import the tables to form Relational Databases to HDFS.
- List databases -It will list all the databases present on a server.
- List-tables -It will list all the tables present in a database.
- Versions -It will display the version information.
- Functions -Parallel import/export, Full load, Incremental Load, Full load, Comparison, Connectors for RDBMS Databases, Kerberos Security Integration, Load data directly into HDFS (Hive/HBase)
5. Explain the Best Practices while importing tables from MySQL or any other databases using Sqoop.
Answer:
While importing the tables from MySQL, we should make sure about a few things like authentication and authorization to the target server and databases. If we don’t have the necessary permission, we will get a connection failure exception while connecting to the database.
6. How do you update the data or rows already exported?
Answer:
To update the rows that are already exported to the destination, we can use the parameter “–update-key.” In this, a comma-separated column list is used, uniquely identifying a row, and all of these columns are used in the WHERE clause of the generated UPDATE query. The SET part of the query will take care of all the other table columns.
Let us move to the following Sqoop Interview Questions.
7. How to configure and install the JDBC driver in Apache Sqoop?
Answer:
It slightly varies in its configuration based on the Hadoop provider. Apart from the JDBC driver, Apache Sqoop requires a connector to establish a connection between different relational databases.
8. What is the split-by clause, and when do we use it?
Answer:
A split-by parameter is for slicing the data to be imported into multiple parallel tasks. Using this parameter, we can specify the column names; these are columns name based on which school will be dividing the data to be imported into multiple chunks, and they will be running in a parallel fashion. It is one of the techniques to tune the performance in Sqoop.
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