6. How do I create and delete a cluster in AWS redshift ?
Sign in to the AWS Management Console and open the Amazon Redshift console at https://console.aws.amazon.com/redshift/.
On the navigation menu, choose CLUSTERS. The clusters for your account in the current AWS Region are listed. A subset of properties of each cluster is displayed in columns in the list. If you don’t have any clusters, choose Create cluster to create one.
Choose the cluster name in the list to view more details about a cluster.
7. How do I load data into my Amazon Redshift data warehouse?
You can load data into Amazon Redshift from a range of data sources including Amazon S3, Amazon DynamoDB, Amazon EMR, AWS Glue, AWS Data Pipeline and or any SSH-enabled host on Amazon EC2 or on-premises.
8. What is Manifest file in redshift ?
In some cases, you might need to load files with different prefixes, for example from multiple buckets or folders. In others, you might need to exclude files that share a prefix. In these cases, you can use a manifest file. A manifest file explicitly lists each load file and its unique object key. You use a manifest file to load the PART table later in this tutorial.
9. How to get data from redshift to AWS S3 ?
Use Redshift UNLOAD command. Unloading data to Amazon S3. Amazon Redshift splits the results of a select statement across a set of files, one or more files per node slice, to simplify parallel reloading of the data. Alternatively, you can specify that UNLOAD should write the results serially to one or more files by adding the PARALLEL OFF option. Unloads the result of a query to one or more text or Apache Parquet files on Amazon S3, using Amazon S3 server-side encryption (SSE-S3). You can also specify server-side encryption with an AWS Key Management Service key (SSE-KMS) or client-side encryption with a customer-managed key (CSE-CMK).
10. How do we execute sql file on Redshift?
Users can do this by using a Python script running on an EC2 to set up a JDBC connection to Redshift. After this, the user requires to execute the queries in the SQL file.