![]() ![]() In order for your consumer cluster to see and use data share created in previous steps, you will need to run the GRANT permission and you will also need the cluster namespace GUID of your consumer cluster. Once you have added all the objects you wish to share to data share, you should then configure permissions. In case you wish to remove some of the tables from your data share, you can do this by running the statement below:ĪLTER DATASHARE ReportingDatashare REMOVE TABLE schema_name.table_name If you want to share all objects within one schema you can run:ĪLTER DATASHARE SalesDatashare ADD ALL TABLES IN SCHEMA reporting_datamart Note: You always start by first adding schemas you will share and then tables and views.Ģ.ĚLTER DATASHARE ReportingDatashare ADD SCHEMA reporting_datamart ģ.ĚLTER DATASHARE ReportingDatashare ADD TABLE reporting_datamart.sales Second step is to add all the schemas tables and views you want to share with the other cluster, the consumer cluster. This process starts on your Production cluster where you need to first create the data share. With your new consumer cluster up and running, you can start with data sharing setup. This will give you a bigger number of data slices for a much better performance when it comes to reading the data. ![]() If your new cluster needs to be smaller than your current cluster, create the new cluster the same size as your production and then use elastic resize to go down to the number of nodes you need. Analyze your current workload and users that will move to the new cluster while also analyzing any of the current issues that you would like to eliminate by this move.Ĭonsider this when creating your new cluster: This information should already be available to you in your current production cluster. You can make this estimation based on the system that will use this shared cluster as well as the number of users you will have. Now we can start with the actual setup and configuration of your shared cluster.įirst thing you need to do is estimate the size of the new cluster. This will have security implications for your environment. You should use this only within the same AWS account, otherwise you will have to make your PROD cluster publicly accessible in order for it to work cross-accounts.This means that you can’t modify any of the data that is made available to you via data sharing. ![]() This is because RA3 clusters use managed storage and therefore can share their data with other clusters. You can only utilize this feature if your Redshift is running on an RA3 cluster type.Although this is a feature that AWS provides and markets as very simple to use, there are a few things you need to know to set it up and configure correctly, and this article aims to explain how to do so properly How to Set up Data Sharingīefore configuring your shared cluster, here are a few things to consider: Amazon Data Sharing is now generally available and with this feature users can display data created in one cluster to multiple other clusters without any data movement or replication systems you need to buy and set up. Additionally, when it comes to accurate testing, users often have to move data themselves or announce well ahead when they will need that data so that DBAs can prepare a testing environment for them.įinally, AWS has come up with a solution. Within a classic Data Warehouse, Data Sharing can be time consuming, stressful and often dependent on DBAs additional tooling. Every organization has multiple teams – departments which often have to share data in order to promote unified and accurate decisions about their product or services. ![]()
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