May 22, 2022

Top 20 AWS Data Pipeline Interview Questions and Answers


AWS Data Pipeline is a web service that enables you to process and move data between AWS computing and storage services, as well as on-premises data sources, at predetermined intervals. You may use AWS Data Pipeline to frequently access your data, transform and analyse it at scale, and efficiently send the results to AWS services like Amazon S3, Amazon RDS, Amazon DynamoDB, and Amazon EMR.

AWS Data Pipeline makes it simple to build fault-tolerant, repeatable, and highly available data processing workloads. You won't have to worry about resource availability, inter-task dependencies, retrying temporary failures or timeouts in individual tasks, or setting up a failure notification system. Data that was previously locked up in on-premises data silos can also be moved and processed using AWS Data Pipeline.

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Ques. 1): What is a pipeline, exactly?


A pipeline is an AWS Data Pipeline resource that defines the chain of data sources, destinations, and preset or custom data processing activities that are necessary to run your business logic.

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Ques. 2): What can I accomplish using Amazon Web Services Data Pipeline?


You can quickly and simply construct pipelines using AWS Data Pipeline, which eliminates the development and maintenance effort necessary to manage your daily data operations, allowing you to focus on creating insights from that data. Simply configure your data pipeline's data sources, timetable, and processing tasks. AWS Data Pipeline manages the execution and monitoring of your processing tasks on a fault-tolerant, highly reliable infrastructure. AWS Data Pipeline also has built-in activities for typical tasks like moving data between Amazon S3 and Amazon RDS and executing a query on Amazon S3 log data to make your development process even easier.

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Ques. 3): How do I install a Task Runner on my on-premise hosts?


You can install the Task Runner package on your on-premise hosts using the following steps:

Download the AWS Task Runner package.

Create a configuration file that includes your AWS credentials.

Start the Task Runner agent via the following command:

java -jar TaskRunner-1.0.jar --config ~/credentials.json --workerGroup=[myWorkerGroup]

Set the activity to execute on [myWorkerGroup] when defining it so that it may be dispatched to the previously installed hosts.

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Ques. 4): What resources are used to carry out activities?


AWS Data Pipeline actions are carried out on your own computing resources. AWS Data Pipeline–managed and self-managed computing resources are the two categories. AWS Data Pipeline–managed resources are Amazon EMR clusters or Amazon EC2 instances that are launched only when they're needed by the AWS Data Pipeline service. You can manage resources that run longer and can be any resource that can execute the AWS Data Pipeline Java-based Task Runner (on-premise hardware, a customer-managed Amazon EC2 instance, etc.).

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Ques. 5): Is it possible for me to run activities on on-premise or managed AWS resources?


Yes. AWS Data Pipeline provides a Task Runner package that may be deployed on your on-premise hosts to enable performing operations utilising on-premise resources. This package polls the AWS Data Pipeline service for work to be done on a regular basis. AWS Data Pipeline will issue the proper command to the Task Runner when it's time to conduct a certain action on your on-premise resources, such as executing a DB stored procedure or a database dump. You may assign many Task Runners to poll for a specific job to guarantee that your pipeline operations are highly available. If one Task Runner is unavailable, the others will simply take up its duties.

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Ques. 6): Is it possible to manually restart unsuccessful activities?


Yes. By changing the status of a group of completed or unsuccessful actions to SCHEDULED, you can restart them. This may be done using the UI's Rerun button or by changing their status via the command line or API. This will trigger a re-check of all activity dependencies, as well as the execution of further activity attempts. Following successive failures, the Activity will attempt the same number of retries as before.

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Ques. 7): What happens if an activity doesn't go as planned?


If all of an activity's activity attempts fail, the activity fails. An activity retries three times by default before failing completely. The number of automated retries can be increased to ten, but the technology does not enable endless retries. After an activity's tries have been exhausted, it will trigger any preset onFailure alarms and will not attempt to run again until you explicitly issue a rerun command using the CLI, API, or console button.

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Ques. 8): What is a schedule, exactly?


Schedules specify when your pipeline actions take place and how often the service expects your data to be provided. Every schedule must specify a start date and a frequency, such as every day at 3 p.m. beginning January 1, 2013. The AWS Data Pipeline service does not execute any actions after the end date specified in the schedule. When you link a timetable to an activity, the activity runs on that schedule. You notify the AWS Data Pipeline service that you want the data to be updated on that schedule when you connect a schedule with a data source. For example, if you define an Amazon S3 data source with an hourly schedule, the service expects that the data source contains new files every hour.

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Ques. 9): What is a data node, exactly?


A data node is a visual representation of your company's information. A data node, for example, can point to a specific Amazon S3 route. AWS Data Pipeline has an expression language that makes it simple to refer to data that is created often. For example, you may specify s3:/example-bucket/my-logs/logdata-#scheduledStartTime('YYYY-MM-dd-HH').tgz as your Amazon S3 data format.

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Ques. 10): Does Data Pipeline supply any standard Activities?


Yes, AWS Data Pipeline provides built-in support for the following activities:

CopyActivity: This activity can copy data between Amazon S3 and JDBC data sources, or run a SQL query and copy its output into Amazon S3.

HiveActivity: This activity allows you to execute Hive queries easily.

EMRActivity: This activity allows you to run arbitrary Amazon EMR jobs.

ShellCommandActivity: This activity allows you to run arbitrary Linux shell commands or programs.


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Ques. 11): Is it possible to employ numerous computing resources on the same pipeline?


Yes, just construct numerous cluster objects in your definition file and use the runsOn attribute to associate the cluster to use for each activity. This enables pipelines to use a mix of AWS and on-premise resources, as well as a mix of instance types for their activities – for example, you might want to use a t1.micro to run a quick script cheaply, but later on the pipeline might have an Amazon EMR job that requires the power of a cluster of larger instances.

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Ques. 12): What is the best way to get started with AWS Data Pipeline?


Simply navigate to the AWS Management Console and choose the AWS Data Pipeline option to get started with AWS Data Pipeline. You may then use a basic graphical editor to design a pipeline.

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Ques. 13): What is a precondition?


A readiness check that may be coupled with a data source or action is known as a precondition. If a data source contains a precondition check, that check must pass before any operations that use the data source may begin. If an activity contains a precondition, the precondition check must pass before the activity may be executed. This is handy if you're performing a computationally intensive activity that shouldn't run unless certain requirements are satisfied.

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Ques. 14): Does AWS Data Pipeline supply any standard preconditions?


Yes, AWS Data Pipeline provides built-in support for the following preconditions:

DynamoDBDataExists: This precondition checks for the existence of data inside a DynamoDB table.

DynamoDBTableExists: This precondition checks for the existence of a DynamoDB table.

S3KeyExists: This precondition checks for the existence of a specific AmazonS3 path.

S3PrefixExists: This precondition checks for at least one file existing within a specific path.

ShellCommandPrecondition: This precondition runs an arbitrary script on your resources and checks that the script succeeds.

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Ques. 15): Will AWS Data Pipeline handle my computing resources and provide and terminate them for me?


Yes, compute resources will be supplied when the first activity that utilises those resources for a planned time is ready to begin, and those instances will be terminated when the last activity that uses those resources has concluded successfully or failed.

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Ques. 16): What distinguishes AWS Data Pipeline from Amazon Simple Workflow Service?


While both services allow you to track your execution, handle retries and errors, and conduct arbitrary operations, AWS Data Pipeline is designed to help you with the stages that are prevalent in most data-driven processes. For example, actions may be executed only once their input data fulfils certain readiness requirements, data can be readily copied between multiple data stores, and chained transformations can be scheduled. Because of this narrow emphasis, Data Pipeline process definitions may be generated quickly and without coding or programming skills.

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Ques. 17): What is an activity, exactly?


As part of a pipeline, AWS Data Pipeline will initiate an activity on your behalf. EMR or Hive tasks, copies, SQL queries, and command-line scripts are all examples of activities.

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Ques. 18): Is it possible to create numerous schedules for distinct tasks inside a pipeline?


Yes, just construct numerous schedule objects in your pipeline definition file and use the schedule field to connect the selected schedule with the appropriate activity. This enables you to create a pipeline in which log files are stored in Amazon S3 every hour, for example, to drive the production of an aggregate report once per day.

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Ques. 19): Is there a list of sample pipelines I can use to get a feel for AWS Data Pipeline?


Yes, our documentation includes sample workflows. In addition, the console includes various pipeline templates to help you get started.

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Ques. 20): Is there a limit to how much I can fit into a single pipeline?


Each pipeline you construct can have up to 100 items by default.


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