Hi Any body was able to form the query that will give the below result:

We are running range restricted query in our redshift where only the employee_id and business_date keep changing .But we keep seeing in SVL_COMPILE our hourly segment compilation is very high .Most of the queries are getting compiled which is adding additional time to the query.

I have a schema in Redshift with over 12,000 tables. I want to drop the schema, but the operation isn’t completing due to the large number of tables. I can’t even execute a SELECT query, and there’s no permission error; it’s just that the sheer volume of tables is causing issues. How can I resolve this?

I work with a Redshift cluster that receives a lot of routine queries that could be turned into materialized views. I thought enabling auto_mv = true would create materialized views of these queries, but it turns out that this parameter is enabled by default and as such was already enabled on my cluster. How can one enforce the creation of auto-matviews? Is there a requirement of a certain percentage of resources not be used to initiate this process?

I work with a Redshift cluster that receives a lot of routine queries that could be turned into materialized views. I thought enabling auto_mv = true would create materialized views of these queries, but it turns out that this parameter is enabled by default and as such was already enabled on my cluster. How can one enforce the creation of auto-matviews? Is there a requirement of a certain percentage of resources not be used to initiate this process?

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