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Azure Databricks

Azure Databricks is an Apache Spark-based analytics platform optimized for the Microsoft Azure cloud services platform. Designed with the founders of Apache Spark, Databricks is integrated with Azure to provide one-click setup, streamlined workflows, and an interactive workspace that enables collaboration between data scientists, data engineers, and business analysts.

We would love to hear any feedback you have for Azure Databricks.
For more details about Azure Databricks, try our documentation page.

  1. Query Acceleration should support compressed data

    Query Acceleration currently supports csv and json files but not compressed versions of those files. It needs to support compressed data or it won't be usable for big data stores.

    1 vote

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  2. Notebook Isolation to R packages

    We are having a separated environment per Notebook as done in Python would help, the notebook could load all the libraries installed in the cluster by default but if users want to install/update libraries it would stay in the notebook environment. In R notebooks it’s not the case unfortunately. Let´s say Installing a package can introduce breaking changes in the code so imagine your code is not compatible with the library A version 2.0 but your colleagues force the installation of this version in his notebook then your notebook won’t run any more because he installed the version 2.0 not…

    1 vote

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  3. track the user who changes folder name

    It seems that Databricks can not track the user who changes the folder name.

    We need a feature in diagnostic logs/Activity logs to track this information

    1 vote

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  4. Enable RStudio to use Credential Passthrough for ADLS

    RStudio on Azure Databricks is not currently compatible with clusters with credential passthrough enabled - instead authentication must be managed using either access keys or a service principal.

    Enabling credential passthrough would allow users to use the gold-standard in ADLS authentication.

    1 vote

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  5. House Moving Melbourne Business address: 1/11 Anthony drive Mount Waverley VIC, 3149 Australia Phone: 03 9059 1908

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    1 vote

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  6. Kindly give table schema download option

    In Data->Tables

    Kindly give table schema download option . Where we can have Columns and its datatypes in xls or csv

    1 vote

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  7. Request an API to collect the information of how long the active cluster is running

    We need an API to collect the information of how long the active cluster is running.

    1 vote

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  8. Tooltip not reflecting correctly

    While creating a Python job in databricks, the information in the box nearby Type and corresponding tooltip shows either to choose dfbs:/ or S3:/. Although it understandable but at first instance misleading as well.

    1 vote

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  9. Quality Quincy Appliance Repair

    Business Name:
    Quality Quincy Appliance Repair
    Address:
    36 School St #105 Quincy, MA 02169
    Phone Number:
    617-829-9934
    URL:
    https://www.appliancerepairquincy.com
    Description:
    Quality Quincy Appliance Repair is proud to provide washing machine repair, dishwasher repair, refrigerator repair and oven repair in Quincy, Massachusetts. Our customers can rely on us to arrive on-time, find the issue with the appliance ASAP and have all of the parts on hand to fix it that same appointment.
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    1 vote

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  10. 1 vote

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  11. 1 vote

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  12. Include Cluster Policies Permissions to force users to use a policy

    Currently we are only allowed to give permission to users to use a policy or not, but I think it would be useful to allow admins to force users creating interactive clusters to use a specific policy for security purposes or other reasons.

    1 vote

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  13. mlflow package on R for Machine Learning Runtimes

    mlflow should be part of the R packages in the ML runtimes but it's not. And perhaps the mlflow_install() should already have been run/prepared

    1 vote

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  14. Suggestion with a brief explanation

    I was wondering if there was any way to see the required syntax and/or documentation of a method. For example, typing count( I would like to be able to let's say press shift+tab for example and see a popup window where the count() function will be explained as well as the needed parameters if case there is any. Similar to what exists in other IDE.

    1 vote

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  15. Integration with Azure virtual machines

    This is the scenario we faced with a client. Client has massive data(numerous files) on a virtual machine hosted in Azure. To process these files(classify whether they have PII), we decided to use Azure Databricks to run the code. We setup a file share in the windows VM and tried to mount the file share in databricks from the terminal. Now we tried virtual network peering to connect the two networks(windows VM n/w and databricks n/w). This failed, we were unable to ping databricks from windows VM, the pings reached only up to the default gateway of databricks. We thought…

    1 vote

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  16. metadata catalog at schema, table, column level

    we need to capture "business metadata" at the column level
    * Description
    * Internal product family
    * etc.

    The attributes (Description, Internal product family, etc.) should be programmable, i.e. we these should be fields that can be defined by the end user.

    This is particularly important for AT&T having > 90M columns of data across the company, and we would like to document the data in place, vs. via spreadsheets afterwards.

    The only way to do this today is to self define a schema to capture column attributes in the "comments field" , which is clumsy and not directly queryable.

    1 vote

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  17. Databricks runtime End of Support message is not incorporated into Azure Health Advisory

    Databricks runtime End of Support message is not incorporated into Azure Health Advisory. There are only separate document listing there.

    Customer found it hard to maintain the inventory for keeping all Azure resources up-to-date without hitting the issue of end of life/support

    1 vote

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  18. Get system managed identity to cluster nodes when the cluster starts up

    Install azure CLI on the cluster and start using cli commands in the init script (such as authenticating to AAD, authenticate to azure key vault, etc). If the node has an identity then authentication will be easy

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  19. 1 vote

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  20. No exception is thrown back to notebook in case of sql session killed using Spark

    Experiencing a weird issue while fetching data from SQL Server into Databricks.
    Below statement is used to fetch the data
    spark.read.jdbc(jdbcUrl, "EAP.vw_ActiveAssignments", connectionProperties).write.mode(SaveMode.Overwrite).saveAsTable("tms.Assignments")
    In case session gets killed at SQL Server, no exception is thrown back to notebook. Notebook considers it as a successful command and continue executing next.
    Due to partial data pull, the subsequent logic get impacted.

    It seems if we directly use JDBC to read data, exception will be catch immediately once session get killed at SQL. Not sure why it is not the case with Spark SQL.

    Can you please consider fixing this issue on priority.

    1 vote

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