Here's your Data + AI Summit 2024 - Warehousing & Analytics recap as you use intelligent data warehousing to improve performance and increase your organization’s productivity with analytics, dashboards and insights. Keynote: Data Warehouse presente...
Databricks SQL provides a simple experience for SQL users who want to run quick ad-hoc queries on their data lake, create multiple visualization types to explore query results from different perspectives, and build and share dashboards.
DBSQL supports the following types of query caching which can help with the query performance -1). Databricks SQL UI caching2). Query results caching3). Delta cachingPlease check here for details -https://docs.databricks.com/sql/admin/query-caching.h...
You can use scheduled query executions to keep your dashboards updated or to enable routine alerts. By default, your queries do not have a schedule. Please refer to the following link to look at the details of how to schedule a query - https://docs.d...
DBSQL supports the following types of query caching which can help with the query performance - 1). Databricks SQL UI caching2). Query results caching3). Delta cachingPlease check here for details - https://docs.databricks.com/sql/admin/query-caching...
Are there workarounds that would allow multiple people to edit the same dashboard? I understand that "can edit" permission is on the roadmap but is there anything else they can do in the meantime to collaborate? Is it possible to disable access contr...
How would Multi Cluster Load Balancer handle JDBC requests? Does a new cluster spin up when ~10 connections are hit or is this unique to # active users?
I see that cluster sizes are mentioned here https://docs.databricks.com/sql/admin/sql-endpoints.html#cluster-size but I would like to know when to pick what type of cluster (data size/ users/ concurrency) without having to do too much trial and error...
I have two jars with the same class name. It works fine on yarn. When trying to run these jars on the Databricks cluster, I run into issues. Why Databricks is having this limitation?
When you run the jobs in Yarn, those are 2 different applications getting submitted on Yarn. Hence each application will have a separate Spark driver JVM's. In Databricks, a cluster has one JVM for the Spark driver. When applications with the same na...
