![]() ![]() You can provide a Redshift password as a base64 encoded KMS encrypted string in most tool configurations, or alternatively you can use. This project includes a number of detailed investigations into various types of Redshift edge cases, nuances, and workload scenarios. This utility can be used to send periodic notifications based on the WLM query monitoring rule actions taken for your unique workload and rules configuration. This project enables a scheduled Lambda function to pull records from the QMR action system log table (stl_wlm_rule_action) and publish them to an SNS topic. Documentation is available WLM Query Monitoring Rule (QMR) Action Notification Utility The automatic capture and management of cluster snapshots is handled by AWS. By using a Lambda function scheduled via a CloudWatch Event ( ), you can ensure that these valuable utilities run automatically and keep your Redshift cluster running well. #Redshift vacuum codeThis project includes code that is able to run the Amazon Redshift Utilities via AWS Lambda. One that replays at a arbitrary concurrency and other that tries to reproduce the original cadence of work. ![]() It reads the user activity log files (when audit is enabled) and generates sql files to be replayed. The Simple Replay Utility helps you to collect and replay cluster workloads. This utility is intended to be used as part of an ongoing scheduled activity, for instance run as part of a Data Pipeline Shell Activity ( ). It then automatically imports the data into the configured Redshift Cluster, and will cleanup S3 if required. It exports data from a source cluster to a location on S3, and all data is encrypted with Amazon Key Management Service. The Redshift Unload/Copy Utility helps you to migrate data between Redshift Clusters or Databases. The DDL to set up the databases, including COPY utility commands to load the data from a public S3 directory, as well as the queries for both single user and multi-user throughput testing are provided. The Cloud DW Benchmark consists of a set of workloads used to characterize and study the performance of Redshift running a variety of analytic queries. Regular maintenance/housekeeping activities, when there are less database activities (quiet period). This script can be scheduled to run VACUUM and ANALYZE as part of ![]() Stats off and size of the table and system alerts from stl_explain & stl_alert_event_log.īy turning on/off '-analyze-flag' and '-vacuum-flag' parameters, you can run it as 'vacuum-only' This Utility AnalyzesĪnd Vacuums table(s) in a Redshift Database schema, based on certain parameters like unsorted, When run, it will analyze or vacuum an entire schema or individual tables. The Redshift Analyze Vacuum Utility gives you the ability to automate VACUUM and ANALYZE operations. The ANALYZE COMPRESSION ( ) command is used to determine if any of the columns in the table require updating, and if so a script is generated to convert to the optimal structure. When run, it will analyze an entire schema or individual tables. The Redshift Column Encoding Utility gives you the ability to apply optimal Column Encoding to an established Schema with data already loaded. These tables may require having the column encoding updated at some point. Other tables may be loaded via Extract/Load/Transform/Load (ELT) processes, and When the COPY command ( ) is used to load data into a table, column encoding will be analyzed and applied by default. That database tables have the correct Column Encoding applied ( ).Ĭolumn Encoding specifies which algorithm is used to compress data within a column, and is chosen on the basis of the datatype, the unique number of discrete values in the column, and so on. In order to get the best performance from your Redshift Database, you must ensure Your Cluster or just to use as examples Column Encoding Utility In the StoredProcedures directory, you will find a collection of stored procedures for managing Your Cluster, generating Schema DDL, and. In the AdminViews directory, you will find a collection of views for managing In the AdminScripts directory, you will find a collection of utilities for running That will assist you in getting the best performance possible from Amazon Redshift. This GitHub provides a collection of scripts and utilities That uses columnar storage to minimise IO, provide high data compression rates,Īnd offer fast performance. Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse solution ![]()
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