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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

indradbxlearn
by • New Contributor
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Feature Request: Cross-job dependencies with business-date awareness

SummaryWorkflows can chain tasks inside one job, but there is no native way to say: “Run job X once per day, after jobs A, B, C, D and E have each completed successfully for the same business date, even though they are independent jobs with their own...

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SumeshKashyap
Contributor III
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I can't speak to the roadmap, but you can remove two of your six components today. Put the table update trigger on your control table, not on the dimension tables. Only dimjob1-5 write to it, so manual and ad hoc dimension loads never fire factjob1, ...

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_its_akshaye
by • New Contributor II
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How to Track Hourly or Daily # of Upsert/Delete Metrics in a DLT Streaming Pipeline

We created a Delta Live Tables (DLT) streaming pipeline to ingest data from the Bronze layer to the Silver layer using Change Data Feed (CDF) enabled.The stream runs continuously and shows # of upserted and deleted rows at an aggregate level from the...

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Jen_Evangelista
New Contributor
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One distinction worth making before choosing the hourly bucket: _commit_timestamp measures when changes landed in the table, while a source event timestamp measures when the business event happened. Late arrivals make those different reports.For targ...

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Islam_hoti
by • Contributor
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Resolved! At what data size do you stop reaching for Spark?

Hi everyone,A question I keep having with my team and I would like to hear how others think about it.A lot of the jobs we run are not big. Plenty of our pipelines process a few gigabytes, some considerably less. We run them on Spark because that is w...

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Jen_Evangelista
New Contributor
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I would separate the engine decision from the compute-startup decision. One nuance on single-node Spark: it removes cross-machine shuffle traffic, but it doesn't remove every Exchange, local spill or startup cost.A useful comparison is the complete r...

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cdn_yyz_yul
by • Contributor III
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Resolved! schema evolution with structured streaming: upstream schema change causes downstream writer fails.

Hello,Bronze: use classic or job compute,  Autoloader with.option("mergeSchema", "true"). Schema evolution works correctly. data goes to bronze.my_bronze_table.Silver: uses serverless compute, reader reads bronze.my_bronze_table, does all necessary t...

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Jen_Evangelista
New Contributor
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Your follow-up points to the join input as the boundary to stabilize, rather than just the final Silver schema.If the enrichment logic permits it, parse and unpivot before the stateful join, so new attributes become rows such as entity_key, attribute...

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A_Motia
by • New Contributor
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Resolved! Production table maintenance

Hi Community members,I'm interested in how people monitor the effectiveness of Liquid Clustering as a Delta table grows over time.Consider below scenario:A table initially performs well, but MERGE operations gradually become slower even though the cl...

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Jen_Evangelista
New Contributor
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One correctness check on the pruning suggestion: adding a target-date filter to MERGE changes which rows can match.With ON t.id = s.id AND t.event_date >= batch_min_date, an existing key whose target date is older can become unmatched and get inserte...

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vijsharm
by • New Contributor III
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checkpoint changes not working on my databricks job

Hi,I do have a job processing kafka stream using kafka.readstream process and due to some issue we changed the checkpoint path to other path and it pulled all the records and later when i changed to the original checkpoint location it is not pulling ...

Data Engineering
checkpoint
  • 2014 Views
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aayush_410
New Contributor III
  • 7 kudos

Stay on the new checkpoint. It already holds the latest offsets, so just keep running it. The only cleanup is the duplicates from the replay. Dedupe the raw table on topic, partition, offset if you store them, otherwise on your business key or a hash...

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parth_db
by • New Contributor III
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Resolved! AutoLoader Type Widening

I have a few doubts regarding AutoLoader behavior and capabilities. Please check and correct wherever my assumptions or understanding are incorrect, much appreciated. Below is my specific code Example scenario:Target Managed Delta Table (Type Widenin...

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Jen_Evangelista
New Contributor
  • 7 kudos

Hi Parth, a useful update for anyone coming back to this thread: Auto Loader now supports type widening in Public Preview on DBR 16.4+ through cloudFiles.schemaEvolutionMode = addNewColumnsWithTypeWidening.Your current addNewColumns setting still doe...

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ankit2604
by • New Contributor
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Datavault implemention on Databricks

Hi everyone,I'm building a Data Vault 2.0 architecture entirely natively in Databricks from scratch. We have specifically decided not to use dbt.While Raw Vault ingestion is straightforward with Spark/Delta, I'm looking for architectural advice on co...

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Jen_Evangelista
New Contributor
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Great points from @balajij8 on the SDP/LDP approach. I've worked on a few Data Vault implementations, and these are the things that tend to bite when the Business Vault grows:1. Hash keys: standardize before hashing. Trim, upper-case and use a fixed ...

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srikanthp24
by • New Contributor III
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About Azure SQL Managed Connector

Hi Community,We are trying to configure a Databricks Lakeflow Connect managed SQL Server connector to ingest data from Azure SQL Database into Databricks.We are using a contained SQL database user that has access only to the specific source database,...

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Nirmata
New Contributor
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Adding to @balajij8’s answer: the reason a contained user can’t work is that ##MS_DatabaseConnector## is a server-level role, and server roles take logins from master, not database users. That’s the access the connector needs to reach master.To keep ...

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orlandovallejos
by • New Contributor
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External location Manage permission

Hi team, I'm trying to update the owner of an external location and I see the following message:Requires permission MANAGE on external location 'location_name'The owner of the resource, the user that created it doesn't have that permission? How is th...

Screenshot 2026-10-16 at 12.21.09 PM.png
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ShamenParis
Contributor III
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Hi @orlandovallejos , Check the Permissions tab to view access rights. If you can't see the external location permissions, reach out to your admin team. Keep in mind that these permissions are tied to the metastore, not the workspace

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i4ata
by • New Contributor II
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Databricks Connect + AutoDependencies + UDF + Streaming breaks

I have this toy python script:CATALOG = 'mpt_usd_gbl_bronze_dev' # <-- replaceSCHEMA = 'mpt_gbl_tco_fof' # <-- replacesrc=f'{CATALOG}.{SCHEMA}.toy_source'DEST = f'{CATALOG}.{SCHEMA}.toy_dest'from databricks.connect import DatabricksSession, Databrick...

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i4ata
New Contributor II
  • 2 kudos

Thanks for the reply and apologies for the typos in the snippet! I tried to get withDependencies() to work but as my UDF was requiring an external package, it was still failing. It can be replicated with the following snippet:CATALOG = 'catalog' # <-...

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DB1To3
by • Contributor III
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Resolved! Zerobus rescue (VARIANT) not working. No Preview Available.

Has anyone tried using the rescue feature for json in zerobus-ingest?  It seems like a very significant feature, assuming the schema incoming json is even 1% outside the control of team that may be ingesting on the databricks side. There needs to be ...

DB1To3_0-1792157909614.png DB1To3_1-1792158060551.png
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aayush_410
New Contributor III
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You’re reading the intended behavior correctly. Zerobus should route non-conforming fields into the rescue column instead of rejecting the record. Your error suggests the feature isn’t active on that table. Per the docs, if no column qualifies, the f...

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DB1To3
by • Contributor III
  • 580 Views
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Resolved! Zerobus Ingest with Kafka compliant API and WITHOUT a callback

Is see that kafka for zerobus is still in beta.  So maybe something will change. Can someone tell me whether they are aware of an authentication handshake with this API that might AVOID the callback?Here is the python example, which uses a sophistica...

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aayush_410
New Contributor III
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I don’t see a way to skip the callback inside the Kafka API itself, but there are workarounds.What the docs say (page updated Oct 1, 2026):OAUTHBEARER is the only auth mechanism. There is no documented anonymous or unauthenticated mode, and I wouldn’...

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DB1To3
by • Contributor III
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Resolved! Zerobus Variant Data not Processed as Expected (json data destined for Variant column).

Lets say I have a table receiving zerobus data (json) over HTTP/rest.That last VARIANT is "ValueJson".If I want to submit data to it, I would expect to be able to use normal json formatting:[ { "a": "E", "b": 123, "c": "xy...

DB1To3_0-1792159051588.png DB1To3_1-1792159180521.png
  • 183 Views
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Jen_Evangelista
New Contributor
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Agree it feels unnatural, but you can hide it from the remote client with a thin encoding step right before sending, so producers keep working with normal nested JSON.A small helper that encodes only the VARIANT columns:import jsonVARIANT_COLUMNS = {...

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Ram_Sundar
by • New Contributor
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Issue with query editor - auto suggest does not respect the casing of columns in CTE

This behaviour (see image) of auto-suggest in the new editor makes the usage of auto-suggest pretty much useless to me.I prefer PascalCase for column names in CTEs. Auto-suggest defaults to lowercase.I need to type out everything. The older version o...

cte-column-case.png
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data_pulse
New Contributor III
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@Ram_Sundar +1, I am seeing the same behaviour as-well. I tried the available editor settings (Autocomplete as you type, Automatic Genie Code Autocomplete, and the keyword/function casing options) and none of them changes the casing of CTE column sug...

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