![]() If provided with the value output, it validates the command inputs and returns a sample output JSON for that command. Similarly, if provided yaml-input it will print a sample input YAML that can be used with -cli-input-yaml. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for -cli-input-json. Prints a JSON skeleton to standard output without sending an API request. Do not use the NextToken response element directly outside of the AWS CLI.įor usage examples, see Pagination in the AWS Command Line Interface User Guide. To resume pagination, provide the NextToken value in the starting-token argument of a subsequent command. If the total number of items available is more than the value specified, a NextToken is provided in the command’s output. The total number of items to return in the command’s output. When using -output text and the -query argument on a paginated response, the -query argument must extract data from the results of the following query expressions: Clusters You can disable pagination by providing the -no-paginate argument. Multiple API calls may be issued in order to retrieve the entire data set of results. If both tag keys and values are omitted from the request, clusters are returned regardless of whether they have tag keys or values associated with them.ĭescribe-clusters is a paginated operation. For example, if you have owner and environment for tag keys, and admin and test for tag values, all clusters that have any combination of those values are returned. If you specify both tag keys and tag values in the same request, Amazon Redshift returns all clusters that match any combination of the specified keys and values. For more information about managing clusters, go to Amazon Redshift Clusters in the Amazon Redshift Cluster Management Guide. ![]() You can easily shred the semi-structured data by creating materialized views and can achieve orders of magnitude faster analytical queries, while keeping the materialized views automatically and incrementally maintained.Returns properties of provisioned clusters including general cluster properties, cluster database properties, maintenance and backup properties, and security and access properties. PartiQL features that facilitate ELT include schemaless semantics, dynamic typing and type introspection abilities in addition to its navigation and unnesting. Furthermore, data engineers can achieve simplified and low latency ELT (Extract, Load, Transform) processing of the inserted semi-structured data directly in their Redshift cluster without integration with external services. This enables new advanced analytics through ad-hoc queries that discover combinations of structured and semi-structured data. ![]() PartiQL allows access to schemaless and nested SUPER data via efficient object and array navigation, unnesting, and flexibly composing queries with classic analytic operations such as JOINs and aggregates. ![]() ![]() PartiQL is an extension of SQL that is adopted across multiple AWS services. Amazon Redshift supports the parsing of JSON data into SUPER and up to 5x faster insertion of JSON/SUPER data in comparison to inserting similar data into classic scalar columns. The generic data type SUPER is schemaless in nature and allows for storage of nested values that could consist of Redshift scalar values, nested arrays or other nested structures. ![]()
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