Manual ApproachWe can Update SQL Warehouse manually in Databricks.Click SQL Warehouses in the sidebarIn Advanced optionsWe can find Unity Catalog toggle button there! While Updating Existing SQL Warehouse in Azure to enable unity catalog using terraf...
Hello,I'm wondering if there's a method or workaround to execute JDBC table queries in a similar manner to other cluster types. Currently, attempting to do so results in an error stating that only text-based files (such as JSON, Parquet, Delta, etc.)...
Could you explain more what you are trying to achieve ?
We have created a Unity Catalog instance on top of our Lakehouse (built entirely with Azure Databricks). We are using Power BI to develop and serve our analytics and reporting needs. I've granted the "Account Users" group the appropriate privileges f...
Thanks for explaining this! This doesn't do exactly what I was hoping—it doesn't block all access to the workspace. Users can still login and access their own workspace and run SQL queries, explore the catalog, etc. But they ARE blocked from accessin...
I have an on-premises Power BI Report Server that uses the Simba Spark ODBC Driver (2.8) to connect to Databricks. It can connect to a serverless warehouse successfully and run its queries, but it never seems to disconnect the session, and so the war...
Hi,As a formal requirement in my project I need to keep original, raw (mainly CSVs and XMLs) files on the lake. Later on they are being ingested into Delta format backed medallion stages, bronze, silver, gold etc.From the audit, operations and discov...
In relational data warehouse systems it was best practise to represent date values as YYYYMMDD integer type values in tables. Date comparison could be done easily without using date-functions and with low performance impact.Is this still the recomme...
Hi @DataFarmer I Databricks I will advise you to use date type instead of int, this will make your life much simpler while working on the date type data.
When trying to connect to a SQL warehouse using the JDBC connector with Spark the below error is thrown. Note that connecting directly to a cluster with similar connection parameters works without issue, the error only occurs with SQL Warehouses.py4j...
Same error here, I am trying to save spark dataframe to Delta lake using JDBC driver and pyspark using this code:#Spark session spark_session = SparkSession.builder \ .appName("RCT-API") \ .config("spark.metrics.namespace", "rct-a...
I have taken a free subscription to azure databricks, but when try to create 2x small warehouse clusture, getting below error, help appreciated.
Can somebody please answer this? I'm having the same issue.
In order to create a ci/cd pipeline to deliver dashboards (here monitoring), how to export / import a dashboard created in databricks sql dashboard from one workspace to another?Thanks
Recommendation is to update your legacy dashboard to Lakeview and then leverage built in export/import support.
Hi Is there a command you could use to list all computes configured in your workspace (active and non-active). This would be really helpful for anyone managing the platfrom to pull all the meta data (tags ,etc) and quickly evaluate all the configura...
@Kaizen You've got three ways of doing this:- Using REST API (https://docs.databricks.com/api/workspace/clusters/list),- Using CLI (https://github.com/databricks/cli/blob/main/docs/commands.md#databricks-clusters-list---list-all-clusters)- Using Pyth...
Team,I did setup a SQL Warehouse Cluster to support request from Mobile devices through REST API. I read through the documentation of concurrent query limit which is 10. But in my scenario I had 5 small clusters and the query monitoring indicated the...
Hi @Ramakrishnan83, Databricks SQL does indeed support concurrent read requests. However, the exact definition of concurrency can vary based on the cluster configuration and workload.By default, Databricks limits the number of concurrent queries per...
Is there any business use-case where profile_metrics and drift_metrics are used by Databricks customers.If so,kindly provide the scenario where to leverage this feature e.g data lineage,table metadata updates.
hey @pankaj2264. both profile metric and drift metric tables are created and used by Lakehouse monitoring to assess the performance of your model and data over time or relative to a baseline table. you can find all the relevant information here Intro...
Hi,Is it possible to convert existing delta table with partition having data to clustering? If so can you please suggest the steps required? I tried and searched but couldn't find any. Is it that liquid clustering can be done only for new Delta table...
Does Liquid Clustering accepts Merge or How Upsert can be done efficiently with Liquid clustered delta table
I wrote simple code:from pyspark.sql import SparkSession from pyspark.sql.window import Window from pyspark.sql.functions import row_number, max import pyspark.sql.functions as F streaming_data = spark.read.table("x") window = Window.partitionBy("BK...
Hi,In my opinion the result is correctWhat needs to be noted in the result is that it is sorted by the "Onboarding_External_LakehouseId" column so if there is "BK_AccountApplicationId" with the same code, it will be partitioned into 2 row_numbersJust...
Hi!I receive three streams from a postgres CDC. These 3 tables, invoices users and products, need to be joined. I want to use a left join with respect the invoices stream. In order to compute correct results and release old states, I use watermarks a...
Hi @jcozar, It seems you’re encountering an issue with multiple event time columns in your Spark Structured Streaming join. Let’s break down the problem and find a solution. Event Time Columns: In Spark Structured Streaming, event time is crucia...
