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Data Engineering
Join discussions on data engineering best practices, architectures, and optimization strategies within the Databricks Community. Exchange insights and solutions with fellow data engineers.
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Forum Posts

Gecofer
by Contributor II
  • 1378 Views
  • 2 replies
  • 1 kudos

Resolved! Inconsistent query results between dbt ETL run and SQL editor in Databricks

Hi everyone,I’m running into a strange issue in one of my ETL pipelines using dbt on Databricks, and I’d appreciate any insights or ideas. I have a query that is part of my dbt model. When I run the ETL process, the results from this query are incorr...

  • 1378 Views
  • 2 replies
  • 1 kudos
Latest Reply
Gecofer
Contributor II
  • 1 kudos

Hi @Isi Thanks so much for your insight!It turned out to be a combination of the two things you mentioned:There was a data masking policy applied to one of the columns, and while I had permissions to view the unmasked data, the service principal runn...

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Debashisrajib
by New Contributor II
  • 907 Views
  • 1 replies
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Resolved! 65 technical questions.

I recently gave Databricks Data Engineer professional exam and I got really lengthy 65 technical questions. These questions are different from statistical questions.65 lengthy technical questions for 120 minutes is too much and this number is not men...

  • 907 Views
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Latest Reply
Advika
Community Manager
  • 0 kudos

Hello @Debashisrajib! I’m sorry to hear that.As outlined in the exam details on Webassessor, Databricks certification exams include 60 scored questions, along with additional unscored questions that appear like regular ones but do not affect your fin...

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Abhimanyu
by Databricks Partner
  • 1170 Views
  • 2 replies
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Why does df.dropna(how="all") fail when there is a . in a column name?

I'm working in a Databricks notebook and using Spark to query a Delta table. Here's the code I ran: df = spark.sql("select * from catalog.schema.table") df = df.dropna(how="all") display(df)This works fine unless the DataFrame has a column name that ...

  • 1170 Views
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MujtabaNoori
New Contributor III
  • 0 kudos

Hi @Abhimanyu ,Yeah Actually in spark, '.'(dot) in columns is used for StructType by which the nested object can be accessed.But definitely You can rename thE columns dynamically whichever has '.' in it.Attached few screenshots for your reference tha...

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chsoni12
by New Contributor II
  • 1273 Views
  • 1 replies
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Resolved! Limitation in Managed Volumes Recovery — UNDROP Should Be Supported

Hello Databricks Community,While reviewing the Databricks official documentation and performing a POC on managed volumes, I observed that volumes cannot be recovered using the UNDROP command if accidentally deleted — unlike managed tables.Technically...

Data Engineering
@databricks
  • 1273 Views
  • 1 replies
  • 0 kudos
Latest Reply
Vidhi_Khaitan
Databricks Employee
  • 0 kudos

Thank you for highlighting this issue!Databricks is already working on implementing this in the future.

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farazahmad372
by New Contributor II
  • 2711 Views
  • 3 replies
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TypeError: 'JavaPackage' object is not callable

from pyspark.sql import *if __name__ == "__main__": spark = SparkSession.builder \ .appName("hello Spark") \ .master("local[2]") \ .getOrCreate() data_list = [("Ravi",28), ("David",45), ("Abd...

  • 2711 Views
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nikhilj0421
Databricks Employee
  • 0 kudos

@farazahmad372 May I know the DBR version and type of cluster?Are you using serverless?  

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adurand-accure
by Databricks Partner
  • 3733 Views
  • 5 replies
  • 2 kudos

Serverless job error - spark.rpc.message.maxSize

Hello, I am facing this error when moving a Workflow to serverless modeERROR : SparkException: Job aborted due to stage failure: Serialized task 482:0 was 269355219 bytes, which exceeds max allowed: spark.rpc.message.maxSize (268435456 bytes). Consid...

  • 3733 Views
  • 5 replies
  • 2 kudos
Latest Reply
adurand-accure
Databricks Partner
  • 2 kudos

Hello PiotrMi,We found out that the problem was caused by a collect() and managed to fix it by changing some codeThanks for your quick repliesBest regards,Antoine 

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SakthiGanesh
by New Contributor II
  • 2902 Views
  • 1 replies
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Unable to run python script from Azure DevOps git repo in Databricks Workflow job

Hi, I'm getting an issue while running a python script from Azure DevOps git repo in Databricks Workflow job task. The error stating internal commit path issue. But I referred the Source as Azure DevOps Services and I gave the branch name when settin...

  • 2902 Views
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Latest Reply
niteshm
New Contributor III
  • 0 kudos

@SakthiGanesh This is a known type of issue when running Databricks Workflows with Azure DevOps Git-backed repos.Did you try, Workspace Path Instead of Internal Git Path?If possible, use a .ipynb notebook-based task rather than a raw .py script, note...

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AgusBudianto
by Contributor
  • 2402 Views
  • 8 replies
  • 1 kudos

Resolved! Is it possible for Store Procedure to be in Unity Catalog Dataricks

I got information that the latest release of Unity Catalog already supports Store Procedure, but I have searched from several sources that Unity catalog does not support Store Procedure, according to the following post: https://community.databricks.c...

  • 2402 Views
  • 8 replies
  • 1 kudos
Latest Reply
Louis_Frolio
Databricks Employee
  • 1 kudos

Yes, you can attend virtually and it is free. What I don't know is what is free. I believe the keynotes are free and some sessions.  You should definitely register and check it out.

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7 More Replies
CJOkpala
by New Contributor II
  • 1624 Views
  • 4 replies
  • 1 kudos

Databricks DLT execution issue

I am having an issue when trying to do a full refresh of a DLT pipeline. I am getting the following error below: com.databricks.sql.managedcatalog.UnityCatalogServiceException: [RequestId=97d4fe52-b185-4757-b0b1-113cb96ae0bb ErrorClass=TABLE_ALREADY_...

CJOkpala_0-1748441402775.png CJOkpala_0-1748426421678.png
  • 1624 Views
  • 4 replies
  • 1 kudos
Latest Reply
nikhilj0421
Databricks Employee
  • 1 kudos

Are you facing the same issue, If you give a different name in the dlt decorator for the table? 

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oneill
by New Contributor II
  • 4663 Views
  • 3 replies
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SQL - Dynamic overwrite + overwrite schema

Hello,Let say we have an empty table S that represents the schema we want to keepABCDEWe have another table T partionned by column A with a schema that depends on the file we have load into. Say :ABCF1b1c1f12b2c2f2Now to make T having the same schema...

  • 4663 Views
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Latest Reply
oneill
New Contributor II
  • 0 kudos

Hi, thanks for the reply. I've already looked at the documentation on this point, which actually states that dynamic overwrite doesn't work with schema overwrite, while the instructions described above seem to indicate the opposite.

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andreapeterson
by Contributor
  • 618 Views
  • 1 replies
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Question about which tags appear in drop down

Hi there, I have a question regarding the appearance of tags in the drop down when adding a tag to a resource (catalog, schema, table, column - level). When does a tag get populated in a drop down? I noticed when I created a column level tag, and wan...

  • 618 Views
  • 1 replies
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Latest Reply
lingareddy_Alva
Esteemed Contributor
  • 0 kudos

Hello @andreapeterson Yes, your understanding of Databricks tag behavior is correct. In Databricks Unity Catalog, tags follow a hierarchical inheritance pattern:Downward inheritance: Tags applied at higher levels (catalog → schema → table) become ava...

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sparklez
by New Contributor III
  • 2056 Views
  • 3 replies
  • 2 kudos

Resolved! Creating Cluster configuration with library dependency using DABS

I am trying to create a cluster configuration using DABS and defining library dependencies.My yaml file looks like this: resources: clusters: project_Job_Cluster: cluster_name: "Project Cluster" spark_version: "16.3.x-cpu-ml-scala2.12" node_type_id: ...

  • 2056 Views
  • 3 replies
  • 2 kudos
Latest Reply
lingareddy_Alva
Esteemed Contributor
  • 2 kudos

Hi @sparklez You're encountering this issue because the libraries field is not valid in the cluster configuration.Libraries need to be specified at the job level, not the cluster level.Option 1: Job-Level Libraries (Recommended)Move the libraries sec...

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Pratikmsbsvm
by Contributor
  • 3606 Views
  • 5 replies
  • 7 kudos

Resolved! Migrating From Azure to Databricks

Hi Techie,May someone please help me with Pros and Cons from migrating my Realtime streaming solution from Azure to Databricks.which component I can replaced with Databricks and what benefit I can get out of it.Current Architecture:- Many Thanks 

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  • 3606 Views
  • 5 replies
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vaibhavs120
Contributor
  • 7 kudos

I completely agree with @lingareddy_Alva on the costing part. One small point I would like to mention is We should only enable SPOT instances (60-90% cost savings) in Development/non-critical(PROD) environment. This option works great and is indeed c...

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anil_reddaboina
by New Contributor II
  • 1858 Views
  • 2 replies
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Slow running Spark job issue - due to the unknown spark stages created by Databircks Compute cluster

Hi Team,Recently we migrated the spark jobs from self hosted spark(YARN) Cluster to Databricks.Currently we are using the Databricks workflows with Job_Compute clusters and the Job Type - Spark JAR type execution, so when we run the job in databricks...

databricks_new_stages.png
  • 1858 Views
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anil_reddaboina
New Contributor II
  • 0 kudos

Hey Brahma,Thanks for your reply. As a first step I will disable AQE config and test it. We are using the node pools with job_compute cluster type so that its not spinning up a new cluster for each Job. I'm configuring the below two configs also, do ...

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chsoni12
by New Contributor II
  • 1330 Views
  • 1 replies
  • 0 kudos

Legacy Autoscaling(workflow) VS Enhanced Autoscaling(DLT)

I conducted a proof of concept (POC) to compare the performance of the DLT pipeline and Databricks Workflow using the same workload, task, code, and cluster configuration. Both configurations were set with autoscaling enabled, with a minimum of 1 wor...

  • 1330 Views
  • 1 replies
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Latest Reply
Brahmareddy
Esteemed Contributor
  • 0 kudos

Hi chsoni12,How are you doing today?, As per my understanding, That's a great observation, and it's awesome that you're testing performance and cost between DLT and regular workflows. The key difference here lies in how autoscaling works. DLT pipelin...

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