Download AWS Glue

Author: t | 2025-04-24

Data protection in AWS Glue. Identity and access management for AWS Glue. Using AWS Glue with AWS Lake Formation for fine-grained access control. Using Amazon S3 Access Grants with AWS Glue. Logging and monitoring in AWS Glue. Compliance validation for AWS Glue. Resilience in AWS Glue. Infrastructure security in AWS Glue In this section, we will go through some of the most important and commonly used features of the AWS Glue Catalog. Prerequisites for AWS Glue Catalog Tables. Steps for Creating AWS Glue Catalog Tables. Download Data Set to use to create AWS Glue Catalog Tables. Upload data to s3 to crawl using AWS Glue Crawler to create required AWS Glue

AWS Glue versions - AWS Glue

Instances. Although the Copy command is for fast loading it will work at its best when all the slices of nodes equally participate in the copy command Download the Guide to Select the Right Data Warehouse Learn the key factors you should consider while selecting the right data warehouse for your business. Below is an example:copy table from 's3:///load/key_prefix' credentials 'aws_access_key_id=;aws_secret_access_key=' Options;You can load multiple files in parallel so that all the slices can participate. For the COPY command to work efficiently, it is recommended to have your files divided into equal sizes of 1 MB – 1 GB after compression.For example, if you are trying to load a file of 2 GB into DS1.xlarge cluster, you can divide the file into 2 parts of 1 GB each after compression so that all the 2 slices of DS1.xlarge can participate in parallel.Please refer to AWS documentation to get the slice information for each type of Redshift node.Using Redshift Spectrum, you can further leverage the performance by keeping cold data in S3 and hot data in the Redshift cluster. This way you can further improve your performance.In case you are looking for a much easier and seamless means to load data to Redshift, you can consider fully managed Data Integration Platforms such as Hevo. Hevo helps load data from any data source to Redshift in real-time without having to write any code.Athena – Ease of Data ReplicationSince Athena is an Analytical query service, you do not have to move the data into Data Warehouse. You can directly query your data over S3 and this way you do not have to worry about node management, loading the data, etc.Data Storage Formats Supported by Redshift and AthenaRedshift data warehouse only supports structured data at the node level. However, Redshift Spectrum tables do also support other storage formats ie. parquet, orc, etc.On the other hand, Athena supports a large number of storage formats ie. parquet, orc, Avro, JSON, etc. It also has a feature called Glue classifier. Athena is well integrated with AWS Glue. Athena table DDLs can be generated automatically using Glue crawlers

AWS CloudFormation for AWS Glue - AWS Glue - docs.aws

Travel operations (SELECT, CREATE, CLONE, UNDROP, etc.) to be performed on it. All Snowflake accounts have a default retention period of 1 day (24 hours). By default, the data retention period for standard objectives is 1 day, while for enterprise editions and higher accounts, it is 0 to 90 days. 6. Explain what is fail-safe. Snowflake offers a default 7-day period during which historical data can be retrieved as a fail-safe feature. Following the expiration of the Time Travel data retention period, the fail-safe default period begins. Data recovery through fail-safe is performed under best-effort conditions, and only after all other recovery options have been exhausted. Snowflake may use it to recover data that has been lost or damaged due to extreme operational failures. It may take several hours to several days for Fail-safe to complete data recovery. 7. Can you explain how Snowflake differs from AWS (Amazon Web Service)? Cloud-based data warehouse platforms like Snowflake and Amazon Redshift provide excellent performance, scalability, and business intelligence tools. In terms of core functionality, both platforms provide similar capabilities, such as relational management, security, scalability, cost efficiency, etc. There are, however, several differences between them, such as pricing, user experience and deployment options. There is no maintenance required with Snowflake as it is a complete SaaS (Software as a Service) offering. In contrast, AWS Redshift clusters require manual maintenance.The Snowflake security model uses always-on encryption to enforce strict security checks, while Redshift uses a flexible, customizable approach.Storage and computation in Snowflake are completely independent, meaning the storage costs are approximately the same as those in S3. In contrast, AWS bypasses this problem with a Red Shift spectrum and lets you query data that is directly available in S3. Despite this, it is not flawless like Snowflake. 8. Could AWS glue connect to Snowflake? Yes, you can connect the Snowflake to AWS glue. AWS glue fits seamlessly into Snowflake as a data warehouse service and presents a comprehensive managed environment. Combining these two solutions makes data ingestion and transformation easier and more flexible. 9. Explain how data compression works in Snowflake and write its advantages. An important aspect of data compression is the encoding, restructuring, or other modifications necessary to minimize its size. As soon as we input data into Snowflake, it is systematically compacted (compressed). Compressing and storing the data in Snowflake is achieved through modern data compression algorithms. What makes snowflake so great is that it charges customers by the size of their data after compression, not by the exact data. Snowflake Compression has the following advantages: Compression lowers storage costs compared with original cloud storage.On-disk caches do not incur storage costs.In general, data sharing and cloning involve no storage expenses. 10. Explain Snowflake caching and write its type. Consider an example where a query takes 15 minutes to run or execute. Now, if you were to repeat the same query with the same frequently used data, later on, you would be doing the same work and wasting resources.Alternatively, Snowflake caches

What is AWS Glue? - AWS Glue - docs.aws.amazon.com

In this tutorial, we will develop AWS Simple Storage Service (S3) together with Spring Boot Rest API service to download the file from AWS S3 Bucket. Amazon S3 Tutorial : Create Bucket on Amazon S3 Generate Credentials to access AWS S3 Bucket Spring Boot + AWS S3 Upload File Spring Boot + AWS S3 List Bucket Files Spring Boot + AWS S3 Download Bucket File Spring Boot + AWS S3 Delete Bucket File AWS S3 Interview Questions and Answers What is S3? Amazon Simple Storage Service (Amazon S3) is an object storage service that provides industry-leading scalability, data availability, security, and performance. The service can be used as online backup and archiving of data and applications on Amazon Web Services (AWS). AWS Core S3 Concepts In 2006, S3 was one of the first services provided by AWS. Many features have been introduced since then, but the core principles of S3 remain Buckets and Objects. AWS BucketsBuckets are containers for objects that we choose to store. It is necessary to remember that S3 allows the bucket name to be globally unique. AWS ObjectsObjects are the actual items that we store in S3. They are marked by a key, which is a sequence of Unicode characters with a maximum length of 1,024 bytes in UTF-8 encoding. Prerequisites First Create Bucket on Amazon S3 and then Generate Credentials(accessKey and secretKey) to access AWS S3 bucket Take a look at our suggested posts: Let's start developing AWS S3 + Spring Boot application. Create Spring. Data protection in AWS Glue. Identity and access management for AWS Glue. Using AWS Glue with AWS Lake Formation for fine-grained access control. Using Amazon S3 Access Grants with AWS Glue. Logging and monitoring in AWS Glue. Compliance validation for AWS Glue. Resilience in AWS Glue. Infrastructure security in AWS Glue

Granting AWS managed policies for AWS Glue - AWS Glue

Infrastructure. Athena query DDLs are supported by Hive and query executions are internally supported by Presto Engine. Athena only supports S3 as a source for query executions. Athena supports almost all the S3 file formats to execute the query. Athena is well integrated with AWS Glue Crawler to devise the table DDLsRedshift Vs Athena ComparisonFeature ComparisonAmazon Redshift FeaturesRedshift is purely an MPP data warehouse application service used by the Analyst or Data warehouse engineer who can query the tables. The tables are in columnar storage format for fast retrieval of data. You can watch a short intro on Redshift here:Data is stored in the nodes and when the Redshift users hit the query in the client/query editor, it internally communicates with Leader Node. The leader node internally communicates with the Compute node to retrieve the query results. In Redshift, both compute and storage layers are coupled, however in Redshift Spectrum, compute and storage layers are decoupled.Athena FeaturesAthena is a serverless analytics service where an Analyst can directly perform the query execution over AWS S3. This service is very popular since this service is serverless and the user does not have to manage the infrastructure. Athena supports various S3 file-formats including CSV, JSON, parquet, orc, and Avro. Along with this Athena also supports the Partitioning of data. Partitioning is quite handy while working in a Big Data environmentRedshift Vs Athena – Feature Comparison TableFeature TypeRedshiftAthenaManaged or ServerlessManaged ServiceServerlessStorage TypeOver Node (Can leverage S3 for Spectrum)Over S3Node typesDense Storage or Dense ComputeNAMostly used forStructured DataStructured and UnstructuredInfrastructureRequires Cluster to manageAWS Manages the infrastructureQuery FeaturesData distributed across nodesPerformance depends on the query hit over S3 and partitionUDF SupportYesNoStored Procedure supportYesNoMaintenance of cluster neededYesNoPrimary key constraintNot enforcedData depends upon the values present in S3 filesData Type supportsLimited support but higher coverage with SpectrumWide variety of supportAdditional considerationCopy commandNode typeVacuumStorage limitLoading partitionsLimits on the number of databasesQuery timeoutExternal schema conceptRedshift Spectrum Shares the same catalog with Athena/GlueAthena/Glue Catalog can be used as Hive Metastore or serve as an external schema for Redshift SpectrumScope of ScalingBoth Redshift and Athena have an internal scaling mechanism.Get the best

What is AWS Glue and use cases of AWS Glue?

Is it recommended for?IT Glue is ideal for MSPs and businesses looking for a comprehensive documentation management and credential management solution with robust security features like SOC 2 compliance.Pros:It is a Self Service PortalIT Glue helps save timeProvides Relationship MappingProvides support systems for MSPsIT Glue comprises a secure password vaultSyncs with Active DirectorySupports access trackingOffers various templatesDocumentation ManagementCredential ManagementAdds TransparencyProvides collaboration in real-timeVersion control featuresHelps in tracking changes made to the documentCons:Exploring IT Glue’s features, options and add-ons can be time consumingWebsite Link: Passbolt CloudPassbolt is a password manager available on-premises and as a cloud service. It provides enhanced security to all company resources such as servers, applications, networks, and more. Comparing the two versions, the cloud version is slightly better as it helps eliminate passwords from premises before any mishap takes place. One can also create user accounts using the Passbolt console. The powerful tool supports various features, such as end-to-end encryption, two-factor authentication, etc. It also helps automate passwords using the JSON API.Key Features:Deployment optionsTwo-factor authenticationTeam password sharingWhy do we recommend it?Passbolt Cloud is recommended for its end-to-end encryption and open security standards. It provides enhanced security for company resources and supports password automation using the JSON API.Who is it recommended for?Passbolt is best suited for teams and DevOps environments looking for a secure, open-source password manager that supports multi-factor authentication and provides flexible deployment options.Pros:Supports end-to-end encryptionIt is a self-hosted softwareA fully open sourceProvides Enhanced securityWorks great with Teams & DevOpsFollows open security standardsAutomate passwords using JSON APIFree Community Version is availableOn-premises installations are freeMulti-factor authentication supportCons:A 30-day trial period is not enoughUses Google and AWS servers for fully hosted plansWebsite Link: DashlaneDashlane is a cloud-based software that provides a password manager for personal use. The software helps store all the user information in an encrypted vault accessible through any device or location.Key Features:Zero-knowledge encryptionPassword generatorPassword policy enforcementWhy do we recommend it?Dashlane is recommended for its user-friendly interface, strong security features like 256-bit AES encryption and biometric authentication, and compatibility across multiple platforms. It also offers dark web monitoring and secure password sharing.You can get access to

Building a Data Lake on AWS with AWS Glue, Glue

OutputStream.write(buffer, 0, len); } return outputStream; } catch (IOException ioException) { logger.error("IOException: " + ioException.getMessage()); } catch (AmazonServiceException serviceException) { logger.info("AmazonServiceException Message: " + serviceException.getMessage()); throw serviceException; } catch (AmazonClientException clientException) { logger.info("AmazonClientException Message: " + clientException.getMessage()); throw clientException; } return null; }} RestAPI - Download file From AWS S3 Create the RestController class to download the file from AWS S3 bucket. package com.techgeeknext.springbootawss3.controller;import com.techgeeknext.springbootawss3.service.S3BucketStorageService;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.http.HttpHeaders;import org.springframework.http.MediaType;import org.springframework.http.ResponseEntity;import org.springframework.web.bind.annotation.*;import java.io.ByteArrayOutputStream;@RestControllerpublic class S3BucketStorageController { @Autowired S3BucketStorageService service; @GetMapping(value = "/download/{filename}") public ResponseEntitybyte[]> downloadFile(@PathVariable String filename) { ByteArrayOutputStream downloadInputStream = service.downloadFile(filename); return ResponseEntity.ok() .contentType(contentType(filename)) .header(HttpHeaders.CONTENT_DISPOSITION, "attachment; filename="" + filename + """) .body(downloadInputStream.toByteArray()); } private MediaType contentType(String filename) { String[] fileArrSplit = filename.split("\\."); String fileExtension = fileArrSplit[fileArrSplit.length - 1]; switch (fileExtension) { case "txt": return MediaType.TEXT_PLAIN; case "png": return MediaType.IMAGE_PNG; case "jpg": return MediaType.IMAGE_JPEG; default: return MediaType.APPLICATION_OCTET_STREAM; } }} Test AWS S3 operations Now, run the Spring Boot application. Upload File on AWS S3 Bucket Use POST method with url select file and provide filename. Verify on AWS S3 Bucket. List all Files from AWS S3 Bucket Use GET method with url Download Files from AWS S3 Bucket Use GET method with url Download Source Code The full source code for this article can be found on below. Download it here - Spring Cloud: AWS S3 Example. Data protection in AWS Glue. Identity and access management for AWS Glue. Using AWS Glue with AWS Lake Formation for fine-grained access control. Using Amazon S3 Access Grants with AWS Glue. Logging and monitoring in AWS Glue. Compliance validation for AWS Glue. Resilience in AWS Glue. Infrastructure security in AWS Glue In this section, we will go through some of the most important and commonly used features of the AWS Glue Catalog. Prerequisites for AWS Glue Catalog Tables. Steps for Creating AWS Glue Catalog Tables. Download Data Set to use to create AWS Glue Catalog Tables. Upload data to s3 to crawl using AWS Glue Crawler to create required AWS Glue