- 1766 Views
- 2 replies
- 2 kudos
Resolved! DQX usage outside Databricks
Hello, When evaluating data quality frameworks for PySpark pipelines, I came across DQX. I noticed it's available on PyPI (databricks-labs-dqx) and GitHub, which is great for accessibility.However, I'm trying to understand the licensing requirements....
- 1766 Views
- 2 replies
- 2 kudos
- 2 kudos
Thanks a lot for the quick response, @ManojkMohan! This was very helpful.I'll keep this in mind.
- 2 kudos
- 1501 Views
- 3 replies
- 2 kudos
Resolved! Moving tables between pipelines in production
We are testing an ingestion from kafka to databricks using a streaming table. The streaming table was created by a DAB deployed to "production" which runs as a service principal. This means the service principal is the "owner" of the table.We now wan...
- 1501 Views
- 3 replies
- 2 kudos
- 2 kudos
You’ve hit two limitations:Streaming tables don’t allow SET OWNER – ownership cannot be changed.Lakeflow pipeline ID changes require pipeline-level permissions – if you’re not the pipeline owner, you can’t run ALTER STREAMING TABLE ... SET PIPELINE_I...
- 2 kudos
- 3863 Views
- 4 replies
- 3 kudos
When working with large data sets in Databricks, what are best practices to avoid memory out-of-memo
How can I optimize Databricks to handle large datasets without running into memory or performance problems?
- 3863 Views
- 4 replies
- 3 kudos
- 3 kudos
Hey! Great question — I’ve run into this issue quite a few times while working with large datasets in Databricks, and out-of-memory errors can be a real headache. One of the biggest things that helps is making sure your cluster configuration matches ...
- 3 kudos
- 6585 Views
- 2 replies
- 0 kudos
Change in UNRESOLVED_COLUMN error behavior in Runtime 14.3 LTS
I've noticed a change in how Databricks handles unresolved column references in PySpark when using All-purpose compute (not serverless).In Databricks Runtime 14.3 LTS, referencing a non-existent column like this:df = spark.table('default.example').se...
- 6585 Views
- 2 replies
- 0 kudos
- 0 kudos
Databricks has recently changed how unresolved column references are handled in PySpark on All-purpose compute clusters. In earlier Databricks Runtime (DBR) 14.3 LTS builds, referencing a non-existent column—such as: python df = spark.tabl...
- 0 kudos
- 8722 Views
- 8 replies
- 2 kudos
Issue with databricks.sdk - AccountClient Service Principals API
Hi everyone,I’ve been trying to work with the databricks.sdk Python library to manage service principals programmatically. However, I’m running into an issue when attempting to create a service principal using the AccountClient class. Below is the co...
- 8722 Views
- 8 replies
- 2 kudos
- 2 kudos
I am using the Python SDK and to authenticate I am using a SP and a Secret. Here is the code that worked for me in Azure Databricks notebook.from databricks.sdk import AccountClient acct_client = AccountClient( host="https://accounts.azuredatabr...
- 2 kudos
- 3206 Views
- 6 replies
- 1 kudos
Resolved! Serverless Compute - Spark - Jobs failing with Max iterations (1000) reached for batch Resolution
Hello Community,We have been trying to migrate our jobs from Classic Compute to Serverless Compute. As part of this process, we face several challenges, and this is one of them.When we try to execute the existing jobs with Serverless Compute, if the ...
- 3206 Views
- 6 replies
- 1 kudos
- 5906 Views
- 3 replies
- 1 kudos
The authentication value "ActiveDirectoryManagedIdentity" is not valid.
Hi Team,i am trying to connect to SQL server hosted in azure vm using Entra id authentication from Databricks.("authentication", "ActiveDirectoryManagedIdentity")Below is the notebook script i am using. driver = "com.microsoft.sqlserver.jdbc.SQLServe...
- 5906 Views
- 3 replies
- 1 kudos
- 1 kudos
You are encountering an error because the default SQL Server JDBC driver bundled with Databricks may not fully support the authentication value "ActiveDirectoryManagedIdentity"—this option requires at least version 10.2.0 of the Microsoft SQL Server ...
- 1 kudos
- 4975 Views
- 4 replies
- 1 kudos
Resolved! delta as streaming source, can the reader reads only newly appended rows?
Hello everyone,In our implementation of Medallion Architecture, we want to stream changes with spark structured streaming. I would like some advice on how to use delta table as source correctly, and if there is performance (memory usage) concern in t...
- 4975 Views
- 4 replies
- 1 kudos
- 1 kudos
In your scenario using Medallion Architecture with Delta tables as both streaming source and sink, it is important to understand Spark Structured Streaming behavior and performance characteristics, especially with joins and memory usage. Here is a di...
- 1 kudos
- 1949 Views
- 1 replies
- 0 kudos
Internal error 500 on databricks vector search endpoint
We are facing an internal 500 error accessing the vector search endpoint through streamlit application, if I refresh the application sometimes the error goes away, it has now started to become an usual occurrence. If I try to query the endpoint using...
- 1949 Views
- 1 replies
- 0 kudos
- 0 kudos
The intermittent Internal 500 errors you’re experiencing when accessing the vector search endpoint through a Streamlit app on Databricks—while direct console queries work—suggest an issue with the interaction between your Streamlit app’s environment ...
- 0 kudos
- 1452 Views
- 1 replies
- 0 kudos
Databricks Nested Json Flattening
Hi Databricks Community,I am facing an issue while exploding nested JSON data.In the content column, I have dynamic nested JSON, and I am using the below approach to parse and explode it.from pyspark.sql import SparkSessionfrom pyspark.sql.functions ...
- 1452 Views
- 1 replies
- 0 kudos
- 0 kudos
You are encountering an AttributeError related to strip, which likely means that some entries for activity.value are not strings (maybe None or dicts) and your code expects all to be strings before calling .strip(). This kind of problem can arise if ...
- 0 kudos
- 1919 Views
- 2 replies
- 0 kudos
Resolved! DATABRICKS LAKEFLOW SQL SERVER INGESTION PIPELINE ERROR
Hey Team,I am getting below error while creating pipeline :com.databricks.pipelines.execution.extensions.managedingestion.errors.ManagedIngestionNonRetryableException: [INGESTION_GATEWAY_DDL_OBJECTS_MISSING] DDL objects missing on table 'coedb.dbo.so...
- 1919 Views
- 2 replies
- 0 kudos
- 0 kudos
The error you are seeing means Databricks cannot capture DDL (table definition) changes, even though CDC (Change Data Capture) and CT (Change Tracking) are enabled. You must run the specific DDL support objects script for Databricks ingestion and the...
- 0 kudos
- 2151 Views
- 2 replies
- 0 kudos
Resolved! Urgency: How to do Data Migration task using Databricks Lakebridge tool ?
Dear community expert,I have completed two phases Analyzer & Converter of Databricks Lakebridge but stuck at migrating data from source to target using lakebridge. I have watched BrickBites Series on Lakebridge but did not find on how to migrate data...
- 2151 Views
- 2 replies
- 0 kudos
- 0 kudos
To migrate tables and views from Snowflake (source) to Databricks (target) using Lakebridge, you must export your data from Snowflake into a supported cloud storage (usually as Parquet files), then import these files into Databricks Delta tables. Lak...
- 0 kudos
- 10898 Views
- 8 replies
- 0 kudos
How we can send databricks log to Azure Application Insight ?
Hi All,I want to send databricks logs to azure application insight.Is there any way we can do it ??Any blog or doc will help me.
- 10898 Views
- 8 replies
- 0 kudos
- 0 kudos
Hello,I finally used he AppInsights agent from OpenTelemetry which is documented in the official Microsoft documentation here:https://learn.microsoft.com/en-us/azure/azure-monitor/app/opentelemetry-enable?tabs=javaBelow is an adaptation of this "Get ...
- 0 kudos
- 12666 Views
- 3 replies
- 3 kudos
When to Use and when Not to Use Liquid Clustering?
Hi everyone,I’m looking for some practical guidance and experiences around when to choose Liquid Clustering versus sticking with traditional partitioning + Z-ordering.From what I’ve gathered so far:For small tables (<10TB), Liquid Clustering gives s...
- 12666 Views
- 3 replies
- 3 kudos
- 3 kudos
Deciding between Liquid Clustering and traditional partitioning with Z-ordering depends on table size, query patterns, number of clustering columns, and file optimization needs. For tables under 10TB with queries consistently filtered on 1–2 columns,...
- 3 kudos
- 2554 Views
- 4 replies
- 0 kudos
Resolved! MERGE operation not performing data skipping with liquid clustering on key columns
Hi, I need some help understanding a performance issue.I have a table that reads approximately 800K records every 30 minutes in an incremental manner.Let’s say its primary key is:timestamp, x, y This table is overwritten every 30 minutes and serves ...
- 2554 Views
- 4 replies
- 0 kudos
- 0 kudos
MERGE is not a pure read plus filter operationEven though Liquid Clustering organizes your data by key ranges and writes min/max stats, the MERGE engine has to identify both matches and non-matches.That means the query planner must:Scan all candidate...
- 0 kudos
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