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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

Maatari
by New Contributor III
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Chaining stateful Operator

I would like to do a groupby followed by a join in structured streaming. I would read from from two delta table in snapshot mode i.e. latest snapshot.My question is specifically about chaining the stateful operator. groupby is update modechaning grou...

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mark_ott
Databricks Employee
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When chaining stateful operators like groupBy (aggregation) and join in Spark Structured Streaming, there are specific rules about the output mode required for the overall query and the behavior of each operator. Output Mode Requirements The groupBy...

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jmeidam
by Databricks Partner
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Displaying job-run progress when submitting jobs via databricks-sdk

When I run notebooks from within a notebook using `dbutils.notebook.run`, I see a nice progress table that updates automatically, showing the execution time, the status, links to the notebook and it is seamless.My goal now is to execute many notebook...

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Coffee77
Honored Contributor II
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All good in @mark_ott response. As a potential improvement, instead of using polling, I think it would be better to publish events to a Bus (i.e. Azure Event Hub) from notebooks so that consumers could launch queries when receiving, processing and fi...

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Maatari
by New Contributor III
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Readying a partitioned Table in Spark Structured Streaming

Does the pre-partitioning of a Delta Table has an influence on the number of "default" Partition of a Dataframe when readying the data?Put differently, using spark structured streaming, when readying from a delta table, is the number of Dataframe par...

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mark_ott
Databricks Employee
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Pre-partitioning of a Delta Table does not strictly determine the number of "default" DataFrame partitions when reading data with Spark Structured Streaming. Unlike Kafka, where each DataFrame partition maps one-to-one to a Kafka partition, Delta Lak...

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c-thiel
by New Contributor
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APPLY INTO Highdate instead of NULL for __END_AT

I really like the APPLY INTO function to keep track of changes and historize them in SCD2.However, I am a bit confused that current records get an __END_AT of NULL. Typically, __END_AT should be a highgate (i.e. 9999-12-31) or similar, so that a poin...

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mark_ott
Databricks Employee
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The APPLY INTO function for SCD2 historization typically sets the __END_AT field of current records to NULL rather than a "highgate" like 9999-12-31. This is by design and reflects that the record is still current and has no defined end date yet. Cur...

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NiraliGandhi
by New Contributor
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Pyspark - alias is not applied in pivot if only one aggregation

This is not making it consistent when we perform aggregation on multiple columns and thus it is hindering metadata driven transformation because of inconsistency.How can we request Databricks/pyspark to include this ? and is there any known work arou...

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mark_ott
Databricks Employee
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When using PySpark or Databricks to perform a pivot operation with only a single aggregation, you may notice that the alias is not applied as expected, leading to inconsistencies, especially when trying to automate or apply metadata-driven frameworks...

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novytskyi
by New Contributor
  • 4364 Views
  • 1 replies
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Timeout for dbutils.jobs.taskValues.set(key, value)

I have a job that call notebook with dbutils.jobs.taskValues.set(key, value) method and assigns around 20 parameters.When I run it - it works.But when I try to call 2 or more copies of a job with different parameters - it fails with error on differen...

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mark_ott
Databricks Employee
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The error you are encountering when running multiple simultaneous Databricks jobs using dbutils.jobs.taskValues.set(key, value) indicates a connection timeout issue to the Databricks backend API (connect timed out at ...us-central1.gcp.databricks.com...

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SebastianCar28
by New Contributor
  • 4584 Views
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How to implement Lifecycle of Data When Use ADLS

Hello everyone, nice to greet you. I have a question about the data lifecycle in ADLS. I know ADLS has its own rules, but they aren't working properly because I have two ADLS accounts: one for hot data and another for cool storage where the informati...

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mark_ott
Databricks Employee
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Yes, you can move data from your HOT ADLS account to a COOL ADLS account while handling Delta Lake log issues, but this requires special techniques due to the nature of Delta Lake’s transaction log. The problem stems from Delta tables’ dependency on ...

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SrinuM
by New Contributor III
  • 4548 Views
  • 1 replies
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Workspace Client dbutils issue

 host = "https://adb-xxxxxx.xx.azuredatabricks.net"token = "dapxxxxxxx"we are using databricksconnect from databricks.sdk import WorkspaceClientdbutil = WorkspaceClient(host=host,token=token).dbutilsfiles = dbutil.fs.ls("abfss://container-name@storag...

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mark_ott
Databricks Employee
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The error where files and directories can be read at the root ADLS level but not at the blob/subdirectory level, combined with a "No file or directory exists on path" message, is frequently due to permission configuration, incorrect path usage, or ne...

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Anshul_DBX
by New Contributor
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Executing Stored Procedures/update in Federated SQL Server

I have federated  Azure SQL DB in my DBX workspace, but I am not able to run update commands or execute a stored procedure, is this still not supported? 

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mark_ott
Databricks Employee
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Federated connections from Azure Databricks to Azure SQL DB via Lakehouse Federation currently only support read-only queries—meaning running update commands or executing stored procedures directly through the federated Unity Catalog interface is not...

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vamsi_simbus
by Databricks Partner
  • 1012 Views
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System tables for DLT Expectations Quality Metrics

Hi Everyone,I’m working with Delta Live Tables (DLT) and using Expectations to track data quality, but I’m having trouble finding where the expectation quality metrics are stored in the DLT system tables.My questions are:Which specific system table(s...

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ManojkMohan
Honored Contributor II
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@vamsi_simbus  DLT captures data quality metrics in specialized system tables known as “event” and “metrics” tables. Specifically, look in the following table:LIVE.DLT_EVENT_LOG or LIVE.DLT_METRICS: These tables contain granular event logs and metric...

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Suheb
by Contributor
  • 661 Views
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Resolved! What are best practices for designing a large-scale data engineering pipeline on Databricks for real

How do you design a scalable, reliable pipeline that handles both fast/continuous data and slower bulk data in the same system?

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Coffee77
Honored Contributor II
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Very generic question Here are general rules and best practices related to Databricks well-architected framework: https://docs.databricks.com/aws/en/lakehouse-architecture/well-architected Take a deeper look on operational excellence, reliability an...

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aravind-ey
by Databricks Partner
  • 26271 Views
  • 23 replies
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vocareum lab access

Hi I am doing a data engineering course in databricks(Partner labs) and would like to have access to vocareum workspace to practice using the demo sessions.can you please help me to get the access to this workspace?regards,Aravind

  • 26271 Views
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Latest Reply
Eicke
Databricks Partner
  • 6 kudos

You can log into databricks, search for "Canada Sales" in the Marketplace and find "Simulated Canada Sales and Opportunities Data". Get free instant access, wait a few seconds for the warehouse to be built for you et voila: the tables for building th...

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sunnyday
by New Contributor
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Naming jobs in the Spark UI in Databricks Runtime 15.4

I am asking almost the same question as: https://community.databricks.com/t5/data-engineering/how-to-improve-spark-ui-job-description-for-pyspark/td-p/48959 .  I would like to know how to improve the readability of the Spark UI by naming jobs.   I am...

  • 6308 Views
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Latest Reply
mark_ott
Databricks Employee
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You are correct—on Databricks Runtime 15.4 and with shared clusters (or clusters enabled with Unity Catalog), you will see the [JVM_ATTRIBUTE_NOT_SUPPORTED] error when trying to directly access sparkContext attributes that are only available in singl...

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Vishnu_9959
by New Contributor
  • 4253 Views
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Can we develop a connector that integrates nintex and Databricks community version

Can we develop a connector that integrates nintex and Databricks with community version

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Latest Reply
mark_ott
Databricks Employee
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It is technically possible to develop a connector that integrates Nintex with Databricks, but there are important limitations when trying to achieve this with Databricks Community Edition.​ Connector Integration Overview Nintex can be integrated with...

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rpilli
by New Contributor
  • 5124 Views
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Conditional Execution in DLT Pipeline based on the output

Hello ,I'm working on a Delta Live Tables (DLT) pipeline where I need to implement a conditional step that only triggers under specific conditions. Here's the challenge I'm facing:I have a function that checks if the data meets certain thresholds. If...

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mark_ott
Databricks Employee
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In Delta Live Tables (DLT), native conditional or branch-based control flow is limited; all table/stream definitions declared in your pipeline will execute, and dependencies are handled via @Dlt.table or @Dlt.view decorators. You can’t dynamically sk...

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