- 25 Views
- 2 replies
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Offline Feature Store in Databricks Serving
Hi, I am planning to deploy a model (pyfunc) with Databricks Serving. During inference, my model needs to retrieve some data from delta tables. I could make these tables to an offline feature store as well.Latency is not so important. It doesnt matt...
- 25 Views
- 2 replies
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There is a ready feature engineering function for that: # on non ML runtime please install databricks-feature-engineering>=0.13.0a3" from databricks.feature_engineering import FeatureEngineeringClient fe = FeatureEngineeringClient() from databrick...
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- 53 Views
- 1 replies
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Best practices for structuring databricks workspaces for CI/CD and ML workflows
Hi everyone,I’m designing the CI/CD process for our environment environment focused on machine learning and data science projects, and I’d like to understand what the best practices are regarding workspace organization—especially when using Unity Cat...
- 53 Views
- 1 replies
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When designing a CI/CD process for Databricks environments — especially for machine learning and data science projects using Unity Catalog — enterprise-scale workspace organization should balance isolation, governance, and collaboration. The recommen...
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- 83 Views
- 2 replies
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Safe Update Strategy for Online Feature Store Without Endpoint Disruption
Hi Team,We are implementing Databricks Online Feature Store using Lakebase architecture and have run into some constraints during development:Requirements:Deploy an offline table as a synced online table and create a feature spec that queries from th...
- 83 Views
- 2 replies
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The recommended way to safely update an online Databricks Feature Store without breaking the serving endpoint or causing downtime involves a version-controlled, atomic update pattern that preserves schema consistency and endpoint stability. Key Issue...
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- 53 Views
- 2 replies
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how to speed up inference?
Hi guys,I'm new to this concept, but we have several ML models that follow the same structure from the code. What I don’t fully understand is how to handle different types of models efficiently — right now, I need to loop through my items to get the ...
- 53 Views
- 2 replies
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Hi @jeremy98 I have not tried this - but could using Python's multiprocessing library to assign the inference for different models to different CPU cores be something you would want to give an attempt? Also here's a useful blog - https://docs.datab...
- 0 kudos
- 58 Views
- 1 replies
- 1 kudos
How does Databricks AutoML handle null imputation for categorical features by default?
Hi everyone I’m using Databricks AutoML (classification workflow) on Databricks Runtime 10.4 LTS ML+, and I’d like to clarify how missing (null) values are handled for categorical (string) columns by default.From the AutoML documentation, I see that:...
- 58 Views
- 1 replies
- 1 kudos
- 1 kudos
Hello @spearitchmeta , I looked internally to see if I could help with this and I found some information that will shed light on your question. Here’s how missing (null) values in categorical (string) columns are handled in Databricks AutoML on Dat...
- 1 kudos
- 2620 Views
- 1 replies
- 1 kudos
Can I Replicate Azure Document Intelligence's Custom Table Extraction in Databricks?
I am using Azure Document Intelligence to get data from a table in a PDF file. The table's headers do not visually align with the values. Therefore, the standard and pre-built models cannot correctly read the data.I have built a custom-trained Azure ...
- 2620 Views
- 1 replies
- 1 kudos
- 1 kudos
Hi @AlbertWang, you can easily achieve this using AgenBricks - Information Extraction. Your PDFs will be converted to text using the ai_parse_document function and saved in a Databricks table. You can then create the agent using that text table to ge...
- 1 kudos
- 3132 Views
- 3 replies
- 7 kudos
Spark context not implemented Error when using Databricks connect
I am developing an application using databricks connect and when I try to use VectorAssembler I get the Error sc is not none Assertion Error. is there a workaround for this ?
- 3132 Views
- 3 replies
- 7 kudos
- 7 kudos
Ran into exactly the same issue as @Łukasz1 After some googling, I found this SO post explaining the issue: later versions of databricks connect no longer support the SparkContext API. Our code is failing because the underlying library is trying to f...
- 7 kudos
- 210 Views
- 1 replies
- 1 kudos
Best Practices for Collaborative Notebook Development in Databricks
Hi everyone! I’m looking to learn more about effective strategies for collaborative development in Databricks notebooks. Since notebooks are often used by multiple data scientists, analysts, and engineers, managing collaboration efficiently is critic...
- 210 Views
- 1 replies
- 1 kudos
- 1 kudos
For version control, use this approach.Git Integration with Databricks ReposCore Features:Databricks Git Folders (Repos) provides native Git integration with visual UI and REST API access Supports all major providers: GitHub, GitLab, Azure DevOps, Bi...
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- 2195 Views
- 4 replies
- 2 kudos
Resolved! Unable to Access Delta View from Azure Machine Learning via Delta Sharing – Is View Access Supported
Unable to Access Delta View from Azure Machine Learning via Delta Sharing – Is View Access Supported?I am able to access the tables but while accessing the view I am getting below error.Response from server: { 'details': [ { '@type': 'type.googleapis...
- 2195 Views
- 4 replies
- 2 kudos
- 2 kudos
View sharing is supported (launched GA) in Databricks. See https://docs.databricks.com/aws/en/delta-sharing/create-share#add-views-to-a-share. You likely need a workspace id override. Creating the recipient from a workspace with proper access and res...
- 2 kudos
- 228 Views
- 1 replies
- 0 kudos
GenAI experiment tracing does not render markdown images
When traces include base64 encoded images in Markdown, they do not render properly. This makes the analysis of traces including images difficult.Just for context, the same trace in other tracing tools like LangSmith renders as expected. An example of...
- 228 Views
- 1 replies
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Thank you for the for the flag juandados! I will ping my product team to get a timeline for you.
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- 758 Views
- 1 replies
- 1 kudos
AutoML Forecast fails when using feature_store_lookups with timestamp key
We are running AutoML Forecast on Databricks Runtime 15.4 ML LTS and 16.4 ML LTS, using a time series dataset with temporal covariates from the Feature Store (e.g. a corona_dummy feature). We use feature_store_lookups with lookup_key and timestamp_lo...
- 758 Views
- 1 replies
- 1 kudos
- 1 kudos
Hi @ostae911 , are you still facing this issue? It looks like your usage of the timestamp column is correct. It can be used as a primary key on the time series feature table. Is it possible that there are other duplicate columns between the training ...
- 1 kudos
- 1417 Views
- 3 replies
- 1 kudos
Resolved! Serving Endpoint Disappears After One Day
I'm encountering an issue where a serving endpoint I create disappears from the list of serving endpoints after a day. This has happened both when I created the endpoint from the Databricks UI and using the Databricks SDK.
- 1417 Views
- 3 replies
- 1 kudos
- 1 kudos
Hey @prashant_089 , what you are experiencing should not happen on its own except for some extremely outlying circumstanctes. IF YOU ARE USING Databricks Free Edition you shold ignore everything below. Here are some troubleshooting suggestions/tips: ...
- 1 kudos
- 2211 Views
- 3 replies
- 0 kudos
Resolved! Problem loading a pyfunc model in job run
Hi, I'm currently working on a automated job to predict forecasts using a notebook than work just fine when I run it manually, but keep failling when schedueled, here is my code: import mlflow # Load model as a PyFuncModel. loaded_model = mlflow.pyf...
- 2211 Views
- 3 replies
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Hey AmineM! If your MLflow model loads fine in a Databricks notebook but fails in a scheduled job on serverless compute with an error like: TypeError: code() argument 13 must be str, not int the root cause is almost always a mismatch between the ...
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- 1048 Views
- 4 replies
- 2 kudos
Resolved! What is the most efficient way of running sentence-transformers on a Spark DataFrame column?
We're trying to run the bundled sentence-transformers library from SBert in a notebook running Databricks ML 16.4 on an AWS g4dn.2xlarge [T4] instance.However, we're experiencing out of memory crashes and are wondering what the optimal to run sentenc...
- 1048 Views
- 4 replies
- 2 kudos
- 2 kudos
If you didn't get this to work with Pandas API on Spark, you might also try importing and instantiating the SentenceTransformer model inside the pandas UDF for proper distributed execution. Each executor runs code independently, and when Spark execut...
- 2 kudos
- 263 Views
- 1 replies
- 0 kudos
Inference Tables Empty
Hello,I have been using Databricks Free Platform for a while. Everything seems to work well. However, I've been trying to generate the payload from the deployed endpoint and I got always an empty inference table.When I check the configuration, I got ...
- 263 Views
- 1 replies
- 0 kudos
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Hi @salesbrj ,Most probably this will be related to limitation in Free Edition. In limitations section I can see following entry:No custom models on GPU or batch inferencehttps://docs.databricks.com/aws/en/getting-started/free-edition-limitations
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