#Redshift space by db how to#
#Redshift space by db full#

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.

#Redshift space by db how to#

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. Redshift is all about packing in large data but you need to use its systems well.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. Redshift should do this automatically now but it can be disabled and happens when there is low activity on the cluster which for some clusters is never.Īdditional thing to check is if the table is well distributed as being poorly distributed can increase dead space as well as impact your query performance. 'VACUUM ' will compact the table to remove this dead space (or 'VACUUM DELETE ONLY ' if you are worried about the sorting time of the table).

This can lead to a lot of dead space in the table.

#Redshift space by db full#

If you have a process that adds data incrementally to the table the last block is likely partially full but the next write will start a new block. Once a block is written it is not updated, only replaced. Second I'd want to make sure that there isn't a lot of 'dead space' in the table. I'd used the data type that is best for the work and leave the space savings up to compression. Changing the data type from float to some decimal representation will likely not save much space ONCE they are compressed. This report will also give you some idea about how much space could be saved. As one commenter noted a surrogate integer may be best and that is one of the compression (encoding) modes that may be recommended. Run ANALYZE COMPRESSION and get a report of what compression will be the best for your data. There are only a few cases where storing raw data on disk is a win (sort key - usually second or third keys). Best advice is to compress everything especially data columns. There are several ways that table space can be reclaimed.įirst is compression (encoding) which you are looking at.