AWS Big Data Blog
From centralized architecture to decentralized architecture: How data sharing fine-tunes Amazon Redshift workloads
Amazon Redshift is a fast, petabyte-scale cloud data warehouse delivering the best price-performance. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Today, tens of thousands of customers run business-critical workloads on Amazon Redshift. With the significant growth of data for big […]
Configure Hadoop YARN CapacityScheduler on Amazon EMR on Amazon EC2 for multi-tenant heterogeneous workloads
Apache Hadoop YARN (Yet Another Resource Negotiator) is a cluster resource manager responsible for assigning computational resources (CPU, memory, I/O), and scheduling and monitoring jobs submitted to a Hadoop cluster. This generic framework allows for effective management of cluster resources for distributed data processing frameworks, such as Apache Spark, Apache MapReduce, and Apache Hive. When […]
Build a resilient Amazon Redshift architecture with automatic recovery enabled
Amazon Redshift provides resiliency in the event of a single point of failure in a cluster, including automatically detecting and recovering from drive and node failures. The Amazon Redshift relocation feature adds an additional level of availability, and this post is focused on explaining this automatic recovery feature. When the cluster relocation feature is enabled […]
Amazon EMR on EKS gets up to 19% performance boost running on AWS Graviton3 Processors vs. Graviton2
Amazon EMR on EKS is a deployment option that enables you to run Spark workloads on Amazon Elastic Kubernetes Service (Amazon EKS) easily. It allows you to innovate faster with the latest Apache Spark on Kubernetes architecture while benefiting from the performance-optimized Spark runtime powered by Amazon EMR. This deployment option elects Amazon EKS as […]
AWS Glue Python shell now supports Python 3.9 with a flexible pre-loaded environment and support to install additional libraries
AWS Glue is the central service of an AWS modern data architecture. It is a serverless data integration service that allows you to discover, prepare, and combine data for analytics and machine learning. AWS Glue offers you a comprehensive range of tools to perform ETL (extract, transform, and load) at the right scale. AWS Glue […]
Build a pseudonymization service on AWS to protect sensitive data: Part 1
According to an article in MIT Sloan Management Review, 9 out of 10 companies believe their industry will be digitally disrupted. In order to fuel the digital disruption, companies are eager to gather as much data as possible. Given the importance of this new asset, lawmakers are keen to protect the privacy of individuals and […]
How NerdWallet uses AWS and Apache Hudi to build a serverless, real-time analytics platform
This is a guest post by Kevin Chun, Staff Software Engineer in Core Engineering at NerdWallet. NerdWallet’s mission is to provide clarity for all of life’s financial decisions. This covers a diverse set of topics: from choosing the right credit card, to managing your spending, to finding the best personal loan, to refinancing your mortgage. […]
Introducing AWS Glue Flex jobs: Cost savings on ETL workloads
AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. You can use AWS Glue to create, run, and monitor data integration and ETL (extract, transform, and load) pipelines and catalog your assets across multiple data stores. Typically, these […]
Forwood Safety uses Amazon QuickSight Q to extend life-saving safety analytics to larger audiences
This is a guest post by Faye Crompton from Forwood Safety. Forwood provides fatality prevention solutions to organizations across the globe. At Forwood Safety, we have a laser focus on saving lives. Our solutions, which provide full content and proven methodology via verification tools and analytical capabilities, have one purpose: eliminating fatalities in the workplace. […]
Design patterns to manage Amazon EMR on EKS workloads for Apache Spark
Amazon EMR on Amazon EKS enables you to submit Apache Spark jobs on demand on Amazon Elastic Kubernetes Service (Amazon EKS) without provisioning clusters. With EMR on EKS, you can consolidate analytical workloads with your other Kubernetes-based applications on the same Amazon EKS cluster to improve resource utilization and simplify infrastructure management. Kubernetes uses namespaces to provide isolation between […]