AWS Redshift Interview Questions and Answers

[2023] AWS Redshift Interview Questions and Answers

Get prepared for your AWS Redshift interview with these top questions and answers. 

AWS Redshift Interview Questions

Q1: What is Redshift in AWS?

Q2: What are the benefits of using AWS Redshift?

Q3. What is a AWS Redshift Cluster?

Q4. Is Amazon Redshift a Relational Database?

Q5. Is AWS Redshift fully managed?

Q6. Features of Amazon Redshift

Q7. Why Amazon Redshift Rocks as a Data Warehouse?

Q8. What is materialized views in Redshift?

Q9. What are top features of Redshift?

Q10. What is a data warehouse and how does AWS Redshift helps?

Q11. How Amazon Redshift apply Pricing?

Q12. What is Redshift Spectrum?

Q13. What is Amazon Redshift managed storage?

Q14. How does Amazon Redshift simplify data warehouse management?

Q15. What are Database Querying Options available in Amazon Redshift?

Q16. How you manage security in Amazon Redshift?

Q17. What are different option of monitoring in Amazon Redshift?

Q18. What are Cluster Snapshots in Amazon Redshift?

Q19. What are Limits per Region in Amazon Redshift?

Q20. What are the limitations of Amazon Redshift?

Q21. Which query language is used by Amazon Redshift?

Q22. Explain the architecture of Amazon Redshift?

Q23. List some Pros and Cons of Amazon Redshift?

Q24. What problems have you faced while working with Amazon Redshift?

Q25. What are cluster in Redshift? How do I create and delete a cluster in AWS redshift ?

Q26. What is Amazon Redshift ODBC?

Q27. How to connect a private Redshift cluster?

Q28. How to Stop/Start Redshift cluster?

Q29. How to alter column data type in Amazon Redshift ?

Q30. What is AQUA for Amazon Redshift?

Q31. Which node types support AQUA?

Q32. What are the limitations of Amazon Redshift?

Q33. Can you explain what an Amazon Redshift cluster consists of?

Q34. How does the architecture of a Redshift Cluster work?

Q35. What are COPY commands in AWS Redshift?

Q36. Is Redshift similar to RDS?

Q37. What is  Redshift Enhanced VPC Routing?

Q38. How do we load data into Redshift?

Q39. What data formats does Redshift Spectrum support?

Q40. How do you handle data replication and backup in Amazon Redshift?

Q41. Why use an AWS Data Pipeline to load CSV into Redshift? And How?

Q42. How are Amazon RDS, DynamoDB, and Redshift different?

Q43. What is Amazon Redshift managed storage?

Q44. How do I use Amazon Redshift’s managed storage?

Q45. What is Amazon Redshift Serverless?

Q46. What are the benefits of using Amazon Redshift Serverless?

Q47. Does Amazon Redshift support single sign-on?

Q48: Does Amazon Redshift support multi-factor authentication (MFA)?

Q49. What happens to my data warehouse cluster availability and data durability if my data warehouse cluster’s Availability Zone (AZ) has an outage?

Q50. How can I run queries from Redshift for the data stored in the AWS Data Lake?

 

Q1: What is Redshift in AWS?

Amazon Web Service(AWS) Redshift is a fully managed big data warehouse service in the cloud that is rapid and potent enough to process and manage data in the range of exabytes. Redshift is built to handle large-scale data sets and database migrations by the company ParAccel (later acquired by Actian). It uses massive parallel processing (MPP) technology and provides a cost-effective and efficient data solution. The famous usage of Redshift is acquiring the latest insight for business and customers.

 

Q2: What are the benefits of using AWS Redshift?

AWS Redshift has below main benefits compare to other options :

  1. AWS Redshift is easy to operation : you can find an choice to build a cluster in the AWS Redshift Console. Only press and leave the rest on the Redshift computer program. Just complete the correct information and start the cluster. The cluster is now ready to be used, for example to control, track and scale Redshift.
  2. Cost Effective: Because there is no need to set up, the cost of this warehouse is reduced to 1/10th.
  3. Scaling of Warehouse is very easy: You just have to resize the cluster size by increasing the number of compute nodes.
  4. High performance: It uses such techniques such as column storage and large simultaneous processing techniques to produce high efficiency and responsiveness times.

 

Q3. What is a AWS Redshift Cluster?

Each Amazon Redshift data warehouse contains a collection of computing resources (nodes) organized in a cluster. Each Redshift cluster runs its own Redshift engine and contains at least one database.

 

Q4. Is Amazon Redshift a Relational Database?

Redshift is Amazon’s analytics database and is designed to crunch large amounts of data as a data warehouse. Those interested in Redshift should know that it consists of clusters of databases with dense storage nodes, and allows you to even run traditional relational databases in the cloud.

 

Q5. Is AWS Redshift fully managed?

Redshift is a fully managed cloud data warehouse. It has the capacity to scale to petabytes, but lets you start with just a few gigabytes of data. Leveraging Redshift, you can use your data to acquire new business insights.

 

Q6. Features of Amazon Redshift

Following are the features of Amazon Redshift −

  1. Supports VPC − The users can launch Redshift within VPC and control access to the cluster through the virtual networking environment.
  2. Encryption − Data stored in Redshift can be encrypted and configured while creating tables in Redshift.
  3. SSL − SSL encryption is used to encrypt connections between clients and Redshift.
  4. Scalable − With a few simple clicks, the number of nodes can be easily scaled in your Redshift data warehouse as per requirement. It also allows to scale over storage capacity without any loss in performance.
  5. Cost-effective − Amazon Redshift is a cost-effective alternative to traditional data warehousing practices. There are no up-front costs, no long-term commitments and on-demand pricing structure.

 

Q7. Why Amazon Redshift Rocks as a Data Warehouse?

  1. Ease of Use It’s hard to overstate the ease of use with Redshift. Due to the similarities between Amazon Redshift’s relational database structure and the household SQL-based commands that can be operated upon, administrators will find ramp-up and adoption are quickly facilitated though familiar best practices in SQL. Queries are distributed and parallelized to easily scale an Amazon Redshift data warehouse cluster up or down with a few clicks in the Amazon AWS Management Console or with a single API call. Amazon Redshift automates the common administrative tasks to help manage, monitor, and scale your data warehouse with push-button simplicity. This eliminates the undifferentiated heavy lifting commonly faced in managing a data warehouse and effectively liberates one to focus on the analytics and core business needs.
  2. Cost-efficiency We wrote an entire guide to Redshift’s pricing model, which we highly recommend you check out, but suffice to say that the cost of running Amazon Redshift has some clear advantages in the market. Compared to more traditional, legacy data warehouses, Amazon Redshift provides a blend of both entry-level affordability and massive cost-efficiency at scale. You can have an unlimited number of users doing unlimited analytics on all your data for just $1,000 per terabyte per year. Amazon Redshift’s columnar-based architecture for query optimization inherently reduces I/O load to return results in seconds and improve costs. With flexible pricing to run your Amazon Redshift cluster either as an on-demand instance or on reserved instances paid up-front with added discounts, organizations get the benefit of planning their spend in a holistic context with their overall analytics and business needs.
  3. Ease of Configuration and Management Overcoming price hurdles is one thing, but when it comes to setup, Amazon Redshift provides significant efficiency and performance gains to the daily DevOps workflow. Whether you’re new or a veteran on Amazon AWS, you’ll find that provisioning is remarkably simple as Amazon Redshift automatically handles many of the time-consuming aspects of managing your own data warehouse. Once schema and definitions are set, Amazon Redshift manages provisioning, configuration, and patching. Data durability and availability are assured as well via automatic replication and backup through Amazon S3. Scaling is simplified by simply adding or removing nodes with just a single API call or through the Amazon AWS management console.
  4. Synergy – Benefits of The Amazon AWS Ecosystem If you’re already using Amazon AWS, then there are considerable synergies with running Amazon Redshift adjacent to other services, ranging from speed and cost of deployment to scalability and innovation. For example, Amazon Redshift’s Spectrum application can be leveraged against services like S3 to run queries against exabytes of data and store highly structured, frequently accessed data on Amazon Redshift local disks, keep vast amounts of unstructured data in an Amazon S3 “data lake”, and query seamlessly across both.

 

Q8. What is materialized views in Redshift?

A precomputed result set is stored in a materialised view, which is based on a SQL query over one or more base tables. You may query a materialised view using SELECT queries in the same way how you can query other tables or views in the database.

 

Q9. What are top features of Redshift?

  • Redshift uses columnar storage, data compression, and zone maps to reduce the amount of I/O needed to perform queries.
  • It uses a massively parallel processing data warehouse architecture to parallelize and distribute SQL operations.
  • Redshift uses machine learning to deliver high throughput based on your workloads.
  • Redshift uses result caching to deliver sub-second response times for repeat queries.
  • Redshift automatically and continuously backs up your data to S3. It can asynchronously replicate your snapshots to S3 in another region for disaster recovery.

 

Q10. What is a data warehouse and how does AWS Redshift helps?

A data warehouse is designed as a warehouse where the data from the systems and other sources generated by the organization are collected and processed.

At high level data warehouse has three-tier architecture:

  • In the bottom tier, we have the tools which cleanse and collect the data.
  • In the middle level, we have tools to transform the data using the Online Analytical Processing Server.
  • At the top level, we have different tools where data analysis and data mining are carried out at the front end.
  • As data growing continuously in an organization and the company constantly has to update its expensive storage servers. Here AWS Redshift is generated in the cloud-based warehouses offered by Amazon where businesses store their data.

 

Q11. How Amazon Redshift apply Pricing?

Amazon Redshift Pricing

You pay for the number of bytes scanned by RedShift Spectrum

You pay a per-second billing rate based on the type and number of nodes in your cluster.

You can reserve instances by committing to using Redshift for a 1 or 3 year term and save costs.

 

Q12. What is Redshift Spectrum?

RedShift Spectrum :

  • Enables you to run queries against exabytes of data in S3 without having to load or transform (ETL) any data.
  • Redshift Spectrum doesn’t use Enhanced VPC Routing.
  • If you store data in a columnar format, Redshift Spectrum scans only the columns needed by your query, rather than processing entire rows.
  • If you compress your data using one of Redshift Spectrum’s supported compression algorithms, less data is scanned.
  • Redshift Spectrum scales up to thousands of instances if needed, so queries run fast, regardless of the size of the data.

 

Q13. What is Amazon Redshift managed storage?

Amazon Redshift managed storage is available with RA3 node types which allows you to scale which pay for computing and storing separately so that you can configure your cluster based on your computing needs.

It automatically uses high-performance SSD-based local storage as a Tier-1 cache and takes advantage of optimizations such as data block temperature, data block age and workload patterns to deliver high performance while scaling storage automatically to Amazon S3 as required without requiring action.

 

Q14. How does Amazon Redshift simplify data warehouse management?

Amazon Redshift handles the work necessary to set up , run and scale a data center.

It providing infrastructure power, automating on-going administrative tasks such as backup and patching, and monitoring nodes and drives to recover from failures. For Redshift Spectrum, Amazon Redshift handles all the computing infrastructure, load balancing, planning, scheduling and execution of your queries for data stored in Amazon S3.

 

Q15. What are Database Querying Options available in Amazon Redshift?

Database Querying Options :

Connect to your cluster through a SQL client tool using standard ODBC and JDBC connections.

Connect to your cluster and run queries on the AWS Management Console with the Query Editor.

 

Q16. How do you manage security in Amazon Redshift?

Security :

  • By default, an Amazon Redshift cluster is only accessible to the AWS account that creates the cluster.
  • Use IAM to create user accounts and manage permissions for those accounts to control cluster operations.
  • If you are using the EC2-VPC platform for your Redshift cluster, you must use VPC security groups.
  • If you are using the EC2-Classic platform for your Redshift cluster, you must use Redshift security groups.
  • When you provision the cluster, you can optionally choose to encrypt the cluster for additional security. Encryption is an immutable property of the cluster.
  • Snapshots created from the encrypted cluster are also encrypted.

 

Q17. What are different option of monitoring in Amazon Redshift?

Monitoring :

  • Use the database audit logging feature to track information about authentication attempts, connections, disconnections, changes to database user definitions, and queries run in the database. The logs are stored in S3 buckets.
  • Redshift tracks events and retains information about them for a period of several weeks in your AWS account.
  • Redshift provides performance metrics and data so that you can track the health and performance of your clusters and databases. It uses CloudWatch metrics to monitor the physical aspects of the cluster, such as CPU utilization, latency, and throughput.
  • Query/Load performance data helps you monitor database activity and performance.
  • When you create a cluster, you can optionally configure a CloudWatch alarm to monitor the average percentage of disk space that is used across all of the nodes in your cluster, referred to as the default disk space alarm.

 

Q18. What are Cluster Snapshots in Amazon Redshift?

Cluster Snapshots :

  • Point-in-time backups of a cluster. There are two types of snapshots: automated and manual. Snapshots are stored in S3 using SSL.
  • Redshift periodically takes incremental snapshots of your data every 8 hours or 5 GB per node of data change.
  • Redshift provides free storage for snapshots that is equal to the storage capacity of your cluster until you delete the cluster. After you reach the free snapshot storage limit, you are charged for any additional storage at the normal rate.
  • Automated snapshots are enabled by default when you create a cluster. These snapshots are deleted at the end of a retention period, which is one day, but you can modify it. You cannot delete an automated snapshot manually.
  • By default, manual snapshots are retained indefinitely, even after you delete your cluster.
  • You can share an existing manual snapshot with other AWS accounts by authorizing access to the snapshot.
  • You can configure Amazon Redshift to automatically copy snapshots (automated or manual) for a cluster to another AWS Region. For automated snapshots, you can also specify the retention period to keep them in the destination AWS Region. The default retention period for copied snapshots is seven days.
  • If you store a copy of your snapshots in another AWS Region, you can restore your cluster from recent data if anything affects the primary AWS Region. You can configure your cluster to copy snapshots to only one destination AWS Region at a time.

 

Q19. What are Limits per Region in Amazon Redshift?

  • The maximum number of tables is 9,900 for large and xlarge cluster node types and 20,000 for 8xlarge cluster node types.
  • The number of user-defined databases you can create per cluster is 60.
  • The number of concurrent user connections that can be made to a cluster is 500.
  • The number of AWS accounts you can authorize to restore a snapshot is 20 for each snapshot and 100 for each AWS KMS key.

 

Q20. What are the limitations of Amazon Redshift?

Some limitations of Amazon Redshift are as follows: Amazon Redshift imposes a limit on the number of tables that you can create in a cluster by node type. An Amazon Redshift table cannot have more than 1,600 columns.

 

Q21. Which query language is used by Amazon Redshift?

SQL (Structured Query Language) is used by Amazon Redshift. 

 

Q22. Explain the architecture of Amazon Redshift?

An Amazon Redshift data repository is a business-class relational database query and administration system. It provides connection of clients with a great number of applications including reporting, business intelligence (BI) and analytics tools.

Amazon Redshift has great storage and excellent query performance with an aggregation of column data storage, massively parallel processing, targeted data compression encoding schemes. It is all about the architecture of Redshift system architecture.

 

Q23. List some Pros and Cons of Amazon Redshift?

Pros of Amazon Redshift:

  • It offers network isolation.
  • It offers result caching.
  • It integrates with third-party tools.
  • It offers a consistent backup for your data.

Cons of Amazon Redshift:

  • It does not work as a live app database.
  • It is a little behind the times with its Postgre setup.
  • Your performance levels decrease as the clusters increase.
  • There are no stored procedures available to you in Amazon Redshift.

 

Q24. What problems have you faced while working with Amazon Redshift?

Majority of the people facing the problem of the queries which are very slow and take a lot of time answering it.

Another problem that is seemed is on the dashboard. The dashboard is too slow.

Another problem in the Amazon Redshift is “black box”. It is very difficult to observe ‘what’s going on’.

 

Q25. What are cluster in Redshift? How do I create and delete a cluster in AWS redshift ?

Computing resources in Amazon Redshift data warehouse are called nodes which are further arranged in a group known as a cluster.

This cluster contains at least one database and it works on Amazon Redshift engine.

To create a Cluster, you have to follow these steps: –

  • The very first step to create a cluster is open the Amazon ECS console by using this link https://console.aws.amazon.com/ecs/.
  • After that, you need to select the region to use which you can find from the navigation bar.
  • When it is done, select cluster in the navigation panel.
  • Then, select Create Cluster can be seen on the Cluster page.
  • At last, you should select the selection compatibility which might be networking, EC2 Linux+ networking or EC2 window + networking.

To delete a cluster in AWS, follow these steps: –

  • The very first step to delete a cluster is to need you to open the Amazon Redshift console by using this link https://aws.amazon.com/redshift/.
  • After that, select the Cluster which you want to remove from the navigation panel
  • When it is done, on the Configuration tab of the cluster details page and then select Cluster, and after that select Delete option.
  • Before going through the end, you need to do some final steps one of the following in the Delete Cluster dialog box.
  • You must choose YES to remove the cluster in creating a snapshot and then take the last snapshot. And then you give the name to that snapshot. And finally, select the delete option.Or you can do choose NO to delete in creating a snapshot without the taking final snapshot and then select the delete option.

 

Q26. What is Amazon Redshift ODBC?

The Amazon Redshift ODBC Driver allows you to connect with live Amazon Redshift data, directly from applications that support ODBC connectivity. It is also helpful to read, write, and update Amazon Redshift data through a standard ODBC Driver interface.

 

Q27. How to connect a private Redshift cluster?

By selecting the option NO, you access for your private IP address within the VPC. Bu doing this, you execute the public IP address. Now, the way of its accessing is through the VPC.

One more method most of the people use to connect to a private database is by using the port forwarding by a Bastion server.

 

Q28. How to Stop/Start Redshift cluster?

You can Start the Redshift cluster by using the following steps:

In the Redshift Snapshots, select the snapshot of the cluster that you want to restore.

Select the Restore option on the Dropdown “Actions” Snapshot menu.

Complete the configuration details, then click the “Restore” button at the bottom right.

You can Stop the Redshift cluster by using the following steps:

  • Select the cluster you want to stop from the AWS Console.
  • Select the “Delete” option on the Dropdown “Cluster” menu.
  • Enter the Snapshot name.
  • Click on Stop.

 

Q29. How to alter column data type in Amazon Redshift ?

Following the command to alter the column data type in Amazon Redshift-

ALTER COLUMN column_name TYPE new_data_type

 

Q30. What is AQUA for Amazon Redshift?

Advanced Query Accelerator(AQUA) is a hardware-accelerated cache which enables redshift for running up to 10x faster than any other enterprise cloud data warehouse.All the data in warehousing architecture with centralized storage requiring data be moved to compute clusters for processing.AQUA is used in bringing the compute to storage by doing a substantial share of data processing in-place on the innovative cache.

 

Q31. Which node types support AQUA?

Nodes supported by AQUA are :

RA3 .16XL

RA3 .4XL

 

Q32. What are the limitations of Amazon Redshift?

Redshift limitations are on the number of tables that we can create in a cluster by node type.

An Amazon Redshift table can’t have more than 1600 columns.

 

Q33. Can you explain what an Amazon Redshift cluster consists of?

A Redshift cluster consists of a leader node and one or more compute nodes. The leader node is responsible for managing client connections and handling queries. The compute nodes are responsible for storing data and processing queries.

 

Q34. How does the architecture of a Redshift Cluster work?

A Redshift cluster is composed of a leader node and one or more compute nodes. The leader node is responsible for managing client connections and executing queries. The compute nodes are responsible for storing data and processing queries. Each compute node is attached to two slices of storage, one for active data and one for backup data.

 

Q35. What are COPY commands in AWS Redshift?

COPY commands are used to load data into an Amazon Redshift table from either data files or Amazon DynamoDB tables. You can also use COPY commands to unload data from an Amazon Redshift table into data files.

 

Q36. Is Redshift similar to RDS?

Redshift is a heavily version of PostgreSQL, it’s not used for OLTP. OLTP  is online transaction processing. So Redshift is not a replacement for RDS. Redshift is OLAP, OLAP stands for online analytical processing. That means that Redshift is used for analytics and data warehousing.

 

Q37. What is  Redshift Enhanced VPC Routing?

If you enable Redshift Enhanced VPC Routing feature , all the COPY of data from whatever storage you want into Redshift, or UNLOAD from Redshift back to S3 , goes through VPC which gives you enhanced security and maybe better performance as well as your data doesn’t go over the public internet.

 

Q38. How do we load data into Redshift?

Data is loaded from S3, DynamoDB, DMS and Read Replicas in RDS for example, when you have a RBS database but you want to do analytics on it to create a read replica, to pull that data from the read replica into Redshift and to do the analytics into Redshift.

 

Q39. What data formats does Redshift Spectrum support?

Redshift Spectrum currently supports for Avro, CSV, Grok, Ion, JSON, ORC, Parquet, RCFile, RegexSerDe, SequenceFile and Tex.

 

Q40. How do you handle data replication and backup in Amazon Redshift?

Data replication and backup in Amazon Redshift is handled through a combination of automated and manual processes.

Automated Processes:

  1. Automated Snapshots: Amazon Redshift automatically takes snapshots of your cluster at regular intervals. These snapshots are stored in Amazon S3 and can be used to restore your cluster to a previous state.
  2. Automated Backups: Amazon Redshift also provides automated backups of your data. These backups are stored in Amazon S3 and can be used to restore your cluster to a previous state.

Manual Processes:

  1. Manual Snapshots: You can manually take snapshots of your cluster at any time. These snapshots are stored in Amazon S3 and can be used to restore your cluster to a previous state.
  2. Manual Backups: You can also manually back up your data. These backups are stored in Amazon S3 and can be used to restore your cluster to a previous state.

Overall, Amazon Redshift provides a robust set of automated and manual processes for data replication and backup. This ensures that your data is always safe and secure.

 

Q41. Why use an AWS Data Pipeline to load CSV into Redshift? And How?

AWS Data Pipeline facilitates the extraction and loading of CSV(Comma Separated Values) files. Using AWS Data Pipelines for CSV loading eliminates the stress of putting together a complex ETL system. It offers template activities to perform DML(data manipulation) tasks efficiently.

To load the CSV file, we must copy the CSV data from the host source and paste that into Redshift via RedshiftCopyActivity.

Q42. How are Amazon RDS, DynamoDB, and Redshift different?

Below are the major differences:

Database Engine: The available Amazon RDS engines include Oracle, MySQL, SQL Server, PostgreSQL, etc., while the DynamoDB engine is NoSQL, and Amazon Redshift supports the Redshift(adapted PostgreSQL) as a database engine.

Data Storage: RDS facilitates 6 terabytes per instance, Redshift supports 16 terabytes per instance, and DynamoDB provides unlimited storage.

Major Usage: RDS is used for traditional databases, while Redshift is famous for data warehousing DynamoDB is the database for dynamically modified data.

Multi-Availability Zone Replication: RDS acts as an additional service while Multi-AZ replication for Redshift is Manual and for DynamoDB is Built-in.

 

Q43. What is Amazon Redshift managed storage?

 

Amazon Redshift managed storage is available with serverless and RA3 node types and lets you scale and pay for compute and storage independently so you can size your cluster based only on your compute needs. It automatically uses high-performance SSD-based local storage as tier-1 cache and takes advantage of optimizations such as data block temperature, data block age, and workload patterns to deliver high performance while scaling storage automatically to Amazon S3 when needed without requiring any action.

 

Q44. How do I use Amazon Redshift’s managed storage?

If you are already using Amazon Redshift Dense Storage or Dense Compute nodes, you can use Elastic Resize to upgrade your existing clusters to the new compute instance RA3. Amazon Redshift Serverless and clusters using the RA3 instance automatically use Redshift-managed storage to store data. No other action outside of using Amazon Redshift Serverless or RA3 instances is required to use this capability.

 

Q45. What is Amazon Redshift Serverless?

Amazon Redshift Serverless is a serverless option of Amazon Redshift that makes it more efficient to run and scale analytics in seconds without the need to set up and manage data warehouse infrastructure. With Redshift Serverless, any user—including data analysts, developers, business professionals, and data scientists—can get insights from data by simply loading and querying data in the data warehouse.

 

Q46. What are the benefits of using Amazon Redshift Serverless?

If you don’t have data warehouse management experience, you don’t have to worry about setting up, configuring, managing clusters or tuning the warehouse. You can focus on deriving meaningful insights from your data or delivering on your core business outcomes through data. You pay only for what you use, keeping costs manageable. You continue to benefit from all of Amazon Redshift’s top-notch performance, rich SQL features, seamless integration with data lakes and operational data warehouses, and built-in predictive analytics and data sharing capabilities. If you need fine-grained control of your data warehouse, you can provision Redshift clusters.

 

Q47. Does Amazon Redshift support single sign-on?

Yes. Customers who want to use their corporate identity providers such as Microsoft Azure Active Directory, Active Directory Federation Services, Okta, Ping Federate, or other SAML compliant identity providers can configure Amazon Redshift to provide single sign-on. You can sign on to Amazon Redshift cluster with Microsoft Azure Active Directory (AD) identities. This allows you to be able to sign on to Redshift without duplicating Azure Active Directory identities in Redshift.

 

Q48: Does Amazon Redshift support multi-factor authentication (MFA)?

Yes. You can use multi-factor authentication (MFA) for additional security when authenticating to your Amazon Redshift cluste

 

Q49. What happens to my data warehouse cluster availability and data durability if my data warehouse cluster’s Availability Zone (AZ) has an outage?

If your Amazon Redshift data warehouse is a single-AZ deployment and the cluster’s Availability Zone becomes unavailable, then Amazon Redshift will automatically move your cluster to another AWS Availability Zone (AZ) without any data loss or application changes. To activate this, you must enable the relocation capability in your cluster configuration settings.

 

Q50. How can I run queries from Redshift for the data stored in the AWS Data Lake?

Amazon Redshift Spectrum is a feature of Amazon Redshift that lets you run queries against your data lake in Amazon S3, with no data loading or ETL required. When you issue an SQL query, it goes to the Amazon Redshift endpoint, which generates and optimizes a query plan. Amazon Redshift determines what data is local and what is in Amazon S3, generates a plan to minimize the amount of S3 data that must be read, and requests Amazon Redshift Spectrum workers out of a shared resource pool to read and process data from Amazon S3.

 

In this blog, we have seen some of the important interview questions that can be asked in AWS Redshift interviews.

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Amazon Web Service – AWS Tutorial

AWS Redshift Cheat Sheet

Amazon RedShift – Purpose, Features, Use cases, Redshift Cluster

https://aws.amazon.com/redshift/faqs/