To my disappointment, it turns out materialized views can't reference external tables ( Amazon Redshift Limitations and Usage Notes ). SELECT ' CREATE EXTERNAL TABLE ' + quote_ident(schemaname) + '. ' In some circumstances, this action may be preferable to writing the data to a physical table. Setting up Amazon Redshift Spectrum requires creating an external schema and tables. This is very confusing, and I spent hours trying to figure out this. Amazon Redshift is a fully managed, distributed relational database on the AWS cloud. If you are new to the AWS RedShift database and need to create schemas and grant access you can use the below SQL to manage this process. For a full list of every user - table permission status, simply delete the entire WHERE clause. Example. when creating a view that reference an external table, and not specifying the "with no schema binding" clause, the redshift returns a success message but the view is not created. The most useful object for this task is the PG_TABLE_DEF table, which as the name implies, contains table definition information. Redshift sort keys can be used to similar effect as the Databricks Z-Order function. This query returns list of non-system views in a database with their definition (script). In this article, we will check one of the administrator tasks, generate Redshift view or table DDL using System Tables. Amazon Redshift retains a great deal of metadata about the various databases within a cluster and finding a list of tables is no exception to this rule. Similarly, to view the permissions of a specific user on a specific table, simply change the bold user name and table name to the user and table of interest on the following code. ... Generates a permanent, named view, containing the SQL generated by all the input tables up to the Create View component. Creating views on your tables is a great way of organizing your analysis. You can use the Amazon Athena data catalog or Amazon EMR as a “metastore” in which to create an external schema. Setting Up Schema and Table Definitions. Amazon Redshift adds materialized view support for external tables. 1. Amazon will manage the hardware’s and your only task is to manage databases that you create as a result of your project. attached article on that issue Along with federated queries, I was thinking it'd be a great way to easily combine data from S3 and Aurora PostgreSQL into Redshift, and unload into S3, without writing a Glue job. Query select table_schema as schema_name, table_name as view_name, view_definition from information_schema.views where table_schema not in ('information_schema', 'pg_catalog') order by schema_name, view_name; Especially in OLAP systems like Amazon Redshift, the analysis usually performed is quite complex and using views is a great way of organizing long queries into smaller parts.. my_schema_name with your schema name create table user ( id int , phone_number int, primary key(id)) but since Redshift does not enforce this constraints, primary key accepts duplicate values. With this enhancement, you can create materialized views in Amazon Redshift that reference external data sources such as Amazon S3 via Spectrum, or data in Aurora or RDS PostgreSQL via federated queries. Amazon Redshift Utils contains utilities, scripts and view which are useful in a Redshift environment - awslabs/amazon-redshift-utils. 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