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Redshift

amazon redshift

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Redshift

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  1. AMAZON REDSHIFT

  2. What is Amazon Redshift? Welcome to the Amazon Redshift Cluster Management Guide. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. This enables you to use your data to acquire new insights for your business and customers. The first step to create a data warehouse is to launch a set of nodes, called an Amazon Redshift cluster. After you provision your cluster, you can upload your data set and then perform data analysis queries. Regardless of the size of the data set, Amazon Redshift offers fast query performance using the same SQL-based tools and business intelligence applications that you use today.

  3. REDSHIFT ARCHITECTURE

  4. Clusters and nodes in Amazon Redshift An Amazon Redshift cluster consists of nodes. Each cluster has a leader node and one or more compute nodes. The leader node receives queries from client applications, parses the queries, and develops query execution plans. The leader node then coordinates the parallel execution of these plans with the compute nodes and aggregates the intermediate results from these nodes. It then finally returns the results back to the client applications. Compute nodes execute the query execution plans and transmit data among themselves to serve these queries. The intermediate results are sent to the leader node for aggregation before being sent back to the client applications

  5. BIG TEXT RA3 nodes with managed storage enable you to optimize your data warehouse by scaling and paying for compute and managed storage independently. With RA3, you choose the number of nodes based on your performance requirements and only pay for the managed storage that you use. Size your RA3 cluster based on the amount of data you process daily. You launch clusters that use the RA3 node types in a virtual private cloud (VPC). You can't launch RA3 clusters in EC2-Classic.

  6. DC2 nodes enable you to have compute-intensive data warehouses with local SSD storage included. You choose the number of nodes you need based on data size and performance requirements. DC2 nodes store your data locally for high performance, and as the data size grows, you can add more compute nodes to increase the storage capacity of the cluster. For datasets under 1 TB (compressed), we recommend DC2 node types for the best performance at the lowest price. If you expect your data to grow, we recommend using RA3 nodes so you can size compute and storage independently to achieve improved price and performance. You launch clusters that use the DC2 node types in a virtual private cloud (VPC). You can't launch DC2 clusters in EC2- Classic.

  7. To resize your cluster, use one of the following approaches: Elastic resize – Use it to change the node type, number of nodes, or both. Elastic resize works quickly by changing or adding nodes to your existing cluster. If you change only the number of nodes, queries are temporarily paused and connections are held open, if possible. Typically, elastic resize takes 10–15 minutes. During the resize operation, the cluster is read-only. We recommend using elastic resize whenever possible, because it completes much more quickly than classic resize.

  8. Classic resize – Use it to change the node type, number of nodes, or both. Classic resize provisions a new cluster and copies the data from the source cluster to the new cluster. Choose this option only when you are resizing to a configuration that isn't available through elastic resize, because it takes considerably more time to complete. An example of when to use it is when resizing to or from a single- node cluster. During the resize operation, the cluster is read- only. Classic resize can take several hours to several days, or longer, depending on the amount of data to transfer and the difference in cluster size and computing resources.

  9. Node type details The following tables summarize the node specifications for each node type and size. The headings in the tables have these meanings: vCPU is the number of virtual CPUs for each node. RAM is the amount of memory in gibibytes (GiB) for each node. Default slices per node is the number of slices into which a compute node is partitioned when a cluster is created or resized with classic resize. The number of slices per node might change if the cluster is resized using elastic resize. However the total number of slices on all the compute nodes in the cluster remains the same after elastic resize. When you create a cluster with the restore from snapshot operation, the number of slices of the resulting cluster might change from the original cluster if you change the node type. Storage is the capacity and type of storage for each node. Node range is the minimum and maximum number of nodes that Amazon Redshift supports for the node type and size. Note You might be restricted to fewer nodes depending on the quota that is applied to your AWS account in the selected AWS Region. To request an i b it A R d hift Li it I F

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