Datastage is an ETL, i.e., Extract, Transform, and Load tool provided by IBM in its InfoSphere suite and Information Solutions Platforms suite. It is a popular ETL tool and is used for working with large data sets and warehouses to create and maintain the data repositories. In this article, we will look at the most frequently asked DataStage interview questions, and we will also provide the answers to these questions.
The most common DataStage interview questions and answers are as follows:
DataStage Interview Questions & Answers
1. What is IBM DataStage, and why is it used?
DataStage is a tool provided by IBM and used to design, develop, and execute the applications to fill the data into data warehouses by extracting the data from databases from windows servers. It contains the feature of graphic visualizations for data integrations and can also extract data from multiple sources. It is therefore considered one of the most potent ETL tools. DataStage has various versions that companies can use based on their requirements. The versions are Server Edition, MVS Edition, and Enterprise Edition.
2. What are the characteristics of DataStage?
The characteristics of IBM DataStage are as follows:
- It can be deployed on local servers as well as the cloud as per the need and requirement.
- It is effortless to use and can increase the speed and flexibility of data integration efficiently.
- It supports big data and can access big data in many ways, such as JDBC integrator, JSON support, and distributed file systems.
3. Describe the DataStage architecture briefly.
IBM DataStage follows a client-server model as its architecture and has different architecture types for its various versions. The components of the client-server architecture are :
- Client components
- Servers
- Stages
- Table definitions
- Containers
- Projects
- Jobs
4. How can we run a job using the command line in DataStage?
The command is: dsjob -run -jobstatus <projectname> <jobname>
5. List a few functions that we can execute using the ‘dsjob’ command.
The different functions that we can perform using $dsjob command are:
- $dsjob -run: It is used to run the DataStage job
- $dsjob -stop: It is used to stop the job that is currently present in the process
- $dsjob -jobid: It is used for providing the job information
- $dsjob -report: It is used for displaying the complete job report
- $dsjob -lprojects: It is used for listing all the projects that are present
- $dsjob -ljobs: It is used for listing all the jobs that are present in the project
- $dsjob -lstages: It is used for listing all the stages of the current job
- $dsjob -llinks: It is used for listing all the links
- $dsjobs -lparams: It is used for listing all the parameters of the job
- $dsjob -projectinfo: It is used for retrieving the information about the project
- $dsjob -jobinfo: It is used for the information retrieval of the job
- $dsjob -stageinfo: It is used for the information retrieval of that stage of that job
- $dsjob -linkinfo: It is used for getting the information of that link
- $dsjob -paraminfo: It provides the information of all the parameters
- $dsjob -loginfo: It is used for getting the information about the log
- $dsjob -log: It is used for adding a text message in the log
- $dsjob -logsum: It is used for displaying the log data
- $dsjob -logdetail: It is used for displaying all the details of the log
- $dsjob -lognewest: It is used for retrieving the id of the newest log
6. What is a flow designer in IBM DataStage?
Flow designer is the web-based user interface of DataStage and is used to create, edit, load, and run the jobs in DataStage.
7. What are the main features of the flow designer?
The main features of the flow designer are:
- It is very useful to perform jobs with a large number of stages.
- There is no need to migrate the jobs to use the flow designer.
- We can use the provided palette to add and remove connectors and operators on the designer canvas using the drag and drop feature.
Learn about: Data Science Vs Data Mining: Difference Between Data Science & Data Mining
8. How to convert a server job to a parallel job in DataStage?
A server job can be converted to a parallel job using a Link collector and an IPC collector.
9. What is an HBase connector?
An HBase connector in DataStage is a tool used to connect databases and tables present in the HBase database. It is majorly used to perform the following tasks:
- Read and write data from and to the HBase database.
- Reading data in the parallel mode.
- Using HBase as a view table
10. What is a Hive connector?
Hive connector is a tool that is used to support partition modes while reading the data. It can be done in two ways:
- modulus partition mode
- minimum-maximum partition mode
11. What is Infosphere in DataStage?
The infosphere information server is capable of managing high volume requirements of the companies and delivers high-quality and faster results. It provides the companies with a single platform for managing the data where they can understand, clean, transform, and deliver enormous amounts of information.
12. List all the different tiers of InfoSphere Information Server?
The different tiers of the InfoSphere Information Server are:
- Client tier
- Services tier
- Engine tier
- Metadata Repository tier
13. Describe the Client tier of the Infosphere Information Server briefly.
The client tier of the Infosphere Information Server is used for the development and the complete administration of the computers using the client programs and consoles.
14. Describe the Services tier of Infosphere Information Server briefly.
The services tier of the Infosphere Information Server is used for providing standard services like metadata and logging and some other module-specific services. It contains an application server, various product modules, and other product services.
15. Describe the Engine tier of Infosphere Information Server briefly.
The engine tier of the Infosphere Information Server is a set of logical components used to run the jobs and other tasks for the product modules.
16. Describe the Metadata Repository tier of Infosphere Information Server briefly.
The metadata repository tier of the Infosphere Information Server includes the metadata repository, the analysis database, and the computer. It is used to share the metadata, shared data, and configuration information.
17. What are the types of parallel processing in the DataStage?
There are two different types of parallel processing, which are:
- Data Partitioning
- Data Pipelining
18. What is Data Partitioning?
Data partitioning is a type of parallel approach for data processing. It involves the process of breaking down the records into partitions for the processing. It increases the efficiency of processing in a linear model.
Read more: Data Preprocessing in Machine Learning: 7 Easy Steps To Follow
19. What is Data Pipelining?
Data Pipelining is a type of parallel approach for data processing where we perform the extraction of data from the source and then make them pass through a sequence of processing functions to get the required output.
20. What is OSH in DataStage?
OSH is an abbreviation of Orchestrate Shell and is a scripting language used in DataStage internally by the parallel engine.
21. What are Players?
Players in DataStage are the workhorse processes. They help us perform the parallel processing and are assigned to the operators on each node.
22. What is a collection library in the DataStage?
The collection libraries are the set of operators and are used to collect the partitioned data.
23. What are the types of collectors available in the collection library of DataStage?
The types of collectors available in the collection library are:
- Sortmerg collector
- Roundrobin collector
- Ordered collector
24. How is the source file populated in DataStage?
The source file can be populated using SQL queries and also by using the row generator extraction tool.
Bottomline
We hope that our article containing all the DataStage interview questions and answers helped you prepare for the DataStage Interview. You can take a look at these courses offered by upGrad to increase your knowledge on these topics:
- PG Diploma in Software Development Specialisation in Big Data: This course is created by upGrad in association with IIIT-B to provide individuals with the knowledge they require for software development and cover the knowledge on the management of Big Data.
- PGC in Full Stack Development: This course on full-stack development is created by upGrad and industry professionals from Tech Mahindra to make the individuals capable of solving industry-level challenges and gaining all the skills required to enter and working in the industries.
We at upGrad are always there to help you with your preparation. You can also look at our courses that can help you learn all the industry required skills and techniques to prepare well for your interviews and future job ambitions, as we always say ‘Raho Ambitious.’ These courses have been made by industry experts and experienced academicians to make you capable of becoming proficient in whatever technology and skills you want to learn.
This article originally published on upGrad blog.
