- 337 Views
- 1 replies
- 0 kudos
workflow not pickingup correct host value (While working with MLflow model registry URI)
Exception: mlflow.exceptions.MlflowException: An API request to https://canada.cloud.databricks.com/api/2.0/mlflow/model-versions/list-artifacts failed due to a timeout. The error message was: HTTPSConnectionPool(host='canada.cloud.databricks.com', p...
- 337 Views
- 1 replies
- 0 kudos
- 0 kudos
@Dharma25 The error clearly shows that MLflow requests are being incorrectly routed to "canada.cloud.databricks.com" instead of your actual workspace URL, causing the timeout.This is a known issue that can occur with MLflow in Databricks, particularl...
- 0 kudos
- 1748 Views
- 3 replies
- 0 kudos
Resolved! Error in creating a serving endpoint: registered model not found
I have registered a custom model which loads another model in the load_context method. Everything works fine when I load (with mlflow.pyfunc.load_model) and use the model in a notebook. When I try to create a serving endpoint for it I keep becoming t...
- 1748 Views
- 3 replies
- 0 kudos
- 0 kudos
It is registered in the Unity Catalog. I have found a complete other solution now. With the help of TransformedTargetRegressor I don't need a separate normalisation step anymore and therefore don't load a model in load_context anymore.
- 0 kudos
- 98 Views
- 3 replies
- 1 kudos
Resolved! How to install Tensorflow 1 based compute or packages in Databricks
I want to install Tensorflow 1 based packages along with python 3.7 etc. I tried multiple ways including using a custom docker image. But nothing seems to workAlso I know that the minimum runtime version available in Databricks is 10.4So is it possib...
- 98 Views
- 3 replies
- 1 kudos
- 1 kudos
@aswinkks You're right to be cautious — as of 2025, using TensorFlow 1.x in modern environments likeDatabricks has become increasingly difficult, if not practically unsupported, due to the combination of:- Deprecation of Python 3.7- TensorFlow 1.x be...
- 1 kudos
- 243 Views
- 1 replies
- 0 kudos
Model Serving Endpoint: Cuda-OOM for Custom Model
Hello all,I am tasked to evaluate a new LLM for some use-cases. In particular, I need to build a POC for a chat bot based on that model. To that end, I want to create a custom Serving Endpoint for an LLM pulled from huggingfaces. The model itself is...
- 243 Views
- 1 replies
- 0 kudos
- 0 kudos
Here are some suggestions: 1. Update coda.yaml. Replace the current config with this optimized version: channels: - conda-forge dependencies: - python=3.10 # 3.12 may cause compatibility issues - pip - pip: - mlflow==2.21.3 - torch...
- 0 kudos
- 700 Views
- 2 replies
- 0 kudos
Problem with ipywidgets and plotly on Databricks
Hi everyone, I am encountering a problem when using ipywidgets with plotly on Databricks. I am trying to pass interactive arguments to a function and then plot with plotly. When I do the followingdef f(m, b) : plt.figure(2) x = np.linspace(-10,...
- 700 Views
- 2 replies
- 0 kudos
- 0 kudos
Thanks for the suggestion! You're absolutely right. The code was already all in my message, but I can make it easier to copy-paste (and add the imports):from ipywidgets import interactive import matplotlib.pyplot as plt import numpy as np def f(m, b...
- 0 kudos
- 23615 Views
- 6 replies
- 6 kudos
Resolved! Access the environment variable from the custom container base cluster
Hi Databricks Community, I want to set environment variables for all clusters in my workspace. The goal is to the have environment variable, available in all notebooks executed on the cluster.The environment variable is generated in global init scrip...
- 23615 Views
- 6 replies
- 6 kudos
- 6 kudos
Thanks @Lukasz Lu​ - that worked for me as well. When I used the following script:#!/bin/bash echo MY_TEST_VAR=value1 | tee -a /etc/environment >> /databricks/spark/conf/spark-env.shfor non-docker clusters, MY_TEST_VAR shows up twice in ` /databrick...
- 6 kudos
- 2595 Views
- 2 replies
- 1 kudos
Resolved! Using Datbricks Connect with serverless compute and MLflow
Hi all,I have been using databricks-connect with serverless compute to develop and debug my databricks related code. It worked great so far. Now I started integrating ML-Flow in my workflow, and I am encountering an issue. When I run the following co...
- 2595 Views
- 2 replies
- 1 kudos
- 1 kudos
The error you are encountering, pyspark.errors.exceptions.connect.AnalysisException: [CONFIG_NOT_AVAILABLE] Configuration spark.mlflow.modelRegistryUri is not available. SQLSTATE: 42K0I, is a known issue when using MLflow with serverless clusters in ...
- 1 kudos
- 270 Views
- 0 replies
- 0 kudos
Custom Multi-agent deployment error
Hi. I am deploying a custom multi-agent system comprising of a genie agent and a RAG solution. While deploying, I am getting the following error:I am using 16.1 ML (Node: Standard_D4ads_v5 16GB,4 core) cluster and I am using the following code for lo...
- 270 Views
- 0 replies
- 0 kudos
- 383 Views
- 3 replies
- 0 kudos
Error when uploading MLFlow artifacts to DBFS
Hi everyone,I'm attempting to use MLFlow experiment tracking from a local machine, but I'm encountering difficulties in uploading artifacts.I've tried a sample code as simple as the following.import mlflow import os os.environ["DATABRICKS_HOST"] = "...
- 383 Views
- 3 replies
- 0 kudos
- 0 kudos
It is considered best practice not to store any production data or assets in DBFS (Databricks File System). The primary reason is that DBFS does not provide robust security controls-anyone with workspace access can potentially access items stored the...
- 0 kudos
- 2515 Views
- 4 replies
- 2 kudos
Problem serving a langchain model on Databricks
Hi, I've encountered a problem of serving a langchain model I just created successfully on Databricks.I was using the following code to set up a model in unity catalog:from mlflow.models import infer_signatureimport mlflowimport langchainmlflow.set_r...
- 2515 Views
- 4 replies
- 2 kudos
- 2 kudos
Hi,The warnings/errors in the logs of the langchain model log process can give you a good hint, although it may be not that evident at first sight.It happened something similar to me - same error message, and the cause was having used an OpenAI model...
- 2 kudos
- 2117 Views
- 2 replies
- 0 kudos
Accessing Databricks Volumes from a Serving Endpoint Using a Custom Model Class in Unity Catalog
Hi everyone,I’m looking for accessing Unity Catalog (UC) Volumes from a Databricks Serving Endpoint. Here’s my current setup:I have a custom AI model class for inference, which I logged into Unity Catalog using mlflow.pyfunc.log_model.I’ve created a ...
- 2117 Views
- 2 replies
- 0 kudos
- 0 kudos
Hey VELU1122,did you find a solution for it. We are struggling with the same problem currently. Thanks
- 0 kudos
- 1334 Views
- 4 replies
- 0 kudos
Resolved! FeatureEngineeringClient workspace id error
Hi, I am working from local notebook using vscode databricks extension.I am trying to use FeatureEngineeringClient, when I create data set training_set = fe.create_training_set( df=filtered_data_train, feature_lookups=payments_feat...
- 1334 Views
- 4 replies
- 0 kudos
- 0 kudos
I’ve done some additional research and found that the FeatureStoreClient is not officially supported when accessing a managed Databricks environment from an external IDE, even when using Databricks Connect. The client library is designed to operate w...
- 0 kudos
- 2286 Views
- 2 replies
- 2 kudos
"error_code":"INVALID_PARAMETER_VALUE","message":"INVALID_PARAMETER_VALUE: Failed to generate access
Hello everyone,I have an Azure Databricks subscription with my company, and I want to use external LLMs in databricks, like claude-3 or gemini. I managed to create a serving endpoint for Anthropic and I am able to use claude 3.But I want to use a Gem...
- 2286 Views
- 2 replies
- 2 kudos
- 1668 Views
- 1 replies
- 0 kudos
Resolved! Enabled the AI Builder Preview but unable to see the feature on the menu even after 3-4 hours
I am an account admin and enabled the beta feature. Does any additional permissions need to be added before I can see the feature on the workspace.
- 1668 Views
- 1 replies
- 0 kudos
- 0 kudos
Realized that our workspace is hosted in a different region. AI Builder is available for only couple of regions at the moment. I was able to spin up a new workspace and it works. Can close this thread
- 0 kudos
- 469 Views
- 0 replies
- 0 kudos
When does everyone utilize the model register?
Hi, I'm Yuki,I'm considering when I should use register_model.In my case, I'm running the training batch once a week and if the model is good, I want to update the champion.I have created the code to register the model if the score is the best.# star...
- 469 Views
- 0 replies
- 0 kudos
Join Us as a Local Community Builder!
Passionate about hosting events and connecting people? Help us grow a vibrant local community—sign up today to get started!
Sign Up Now-
Access control
3 -
Access Data
2 -
AccessKeyVault
1 -
ADB
2 -
Airflow
1 -
Amazon
2 -
Apache
1 -
Apache spark
3 -
APILimit
1 -
Artifacts
1 -
Audit
1 -
Autoloader
6 -
Autologging
2 -
Automation
2 -
Automl
32 -
AWS
7 -
Aws databricks
1 -
AWSSagemaker
1 -
Azure
32 -
Azure active directory
1 -
Azure blob storage
2 -
Azure data lake
1 -
Azure Data Lake Storage
3 -
Azure data lake store
1 -
Azure databricks
32 -
Azure event hub
1 -
Azure key vault
1 -
Azure sql database
1 -
Azure Storage
2 -
Azure synapse
1 -
Azure Unity Catalog
1 -
Azure vm
1 -
AzureML
2 -
Bar
1 -
Beta
1 -
Better Way
1 -
BI Integrations
1 -
BI Tool
1 -
Billing and Cost Management
1 -
Blob
1 -
Blog
1 -
Blog Post
1 -
Broadcast variable
1 -
Business Intelligence
1 -
CatalogDDL
1 -
Centralized Model Registry
1 -
Certification
2 -
Certification Badge
1 -
Change
1 -
Change Logs
1 -
Chatgpt
2 -
Check
2 -
Classification Model
1 -
Cloud Storage
1 -
Cluster
10 -
Cluster policy
1 -
Cluster Start
1 -
Cluster Termination
2 -
Clustering
1 -
ClusterMemory
1 -
CNN HOF
1 -
Column names
1 -
Community Edition
1 -
Community Edition Password
1 -
Community Members
1 -
Company Email
1 -
Condition
1 -
Config
1 -
Configure
3 -
Confluent Cloud
1 -
Container
2 -
ContainerServices
1 -
Control Plane
1 -
ControlPlane
1 -
Copy
1 -
Copy into
2 -
CosmosDB
1 -
Courses
2 -
Csv files
1 -
Dashboards
1 -
Data
8 -
Data Engineer Associate
1 -
Data Engineer Certification
1 -
Data Explorer
1 -
Data Ingestion
2 -
Data Ingestion & connectivity
11 -
Data Quality
1 -
Data Quality Checks
1 -
Data Science & Engineering
2 -
databricks
5 -
Databricks Academy
3 -
Databricks Account
1 -
Databricks AutoML
9 -
Databricks Cluster
3 -
Databricks Community
5 -
Databricks community edition
4 -
Databricks connect
1 -
Databricks dbfs
1 -
Databricks Feature Store
1 -
Databricks Job
1 -
Databricks Lakehouse
1 -
Databricks Mlflow
4 -
Databricks Model
2 -
Databricks notebook
10 -
Databricks ODBC
1 -
Databricks Platform
1 -
Databricks Pyspark
1 -
Databricks Python Notebook
1 -
Databricks Runtime
9 -
Databricks SQL
8 -
Databricks SQL Permission Problems
1 -
Databricks Terraform
1 -
Databricks Training
2 -
Databricks Unity Catalog
1 -
Databricks V2
1 -
Databricks version
1 -
Databricks Workflow
2 -
Databricks Workflows
1 -
Databricks workspace
2 -
Databricks-connect
1 -
DatabricksContainer
1 -
DatabricksML
6 -
Dataframe
3 -
DataSharing
1 -
Datatype
1 -
DataVersioning
1 -
Date Column
1 -
Dateadd
1 -
DB Notebook
1 -
DB Runtime
1 -
DBFS
5 -
DBFS Rest Api
1 -
Dbt
1 -
Dbu
1 -
DDL
1 -
DDP
1 -
Dear Community
1 -
DecisionTree
1 -
Deep learning
4 -
Default Location
1 -
Delete
1 -
Delt Lake
4 -
Delta
24 -
Delta lake table
1 -
Delta Live
1 -
Delta Live Tables
6 -
Delta log
1 -
Delta Sharing
3 -
Delta-lake
1 -
Deploy
1 -
DESC
1 -
Details
1 -
Dev
1 -
Devops
1 -
Df
1 -
Different Notebook
1 -
Different Parameters
1 -
DimensionTables
1 -
Directory
3 -
Disable
1 -
Distribution
1 -
DLT
6 -
DLT Pipeline
3 -
Dolly
5 -
Dolly Demo
2 -
Download
2 -
EC2
1 -
Emr
2 -
Ensemble Models
1 -
Environment Variable
1 -
Epoch
1 -
Error handling
1 -
Error log
2 -
Eventhub
1 -
Example
1 -
Experiments
4 -
External Sources
1 -
Extract
1 -
Fact Tables
1 -
Failure
2 -
Feature Lookup
2 -
Feature Store
52 -
Feature Store API
2 -
Feature Store Table
1 -
Feature Table
6 -
Feature Tables
4 -
Features
2 -
FeatureStore
2 -
File Path
2 -
File Size
1 -
Fine Tune Spark Jobs
1 -
Forecasting
2 -
Forgot Password
2 -
Garbage Collection
1 -
Garbage Collection Optimization
1 -
Github
2 -
Github actions
2 -
Github Repo
2 -
Gitlab
1 -
GKE
1 -
Global Init Script
1 -
Global init scripts
4 -
Governance
1 -
Hi
1 -
Horovod
1 -
Html
1 -
Hyperopt
4 -
Hyperparameter Tuning
2 -
Iam
1 -
Image
3 -
Image Data
1 -
Inference Setup Error
1 -
INFORMATION
1 -
Input
1 -
Insert
1 -
Instance Profile
1 -
Int
2 -
Interactive cluster
1 -
Internal error
1 -
Invalid Type Code
1 -
IP
1 -
Ipython
1 -
Ipywidgets
1 -
JDBC Connections
1 -
Jira
1 -
Job
4 -
Job Parameters
1 -
Job Runs
1 -
Join
1 -
Jsonfile
1 -
Kafka consumer
1 -
Key Management
1 -
Kinesis
1 -
Lakehouse
1 -
Large Datasets
1 -
Latest Version
1 -
Learning
1 -
Limit
3 -
LLM
3 -
LLMs
1 -
Local computer
1 -
Local Machine
1 -
Log Model
2 -
Logging
1 -
Login
1 -
Logs
1 -
Long Time
2 -
Low Latency APIs
2 -
LTS ML
3 -
Machine
3 -
Machine Learning
24 -
Machine Learning Associate
1 -
Managed Table
1 -
Max Retries
1 -
Maximum Number
1 -
Medallion Architecture
1 -
Memory
3 -
Metadata
1 -
Metrics
3 -
Microsoft azure
1 -
ML Lifecycle
4 -
ML Model
4 -
ML Practioner
3 -
ML Runtime
1 -
MlFlow
75 -
MLflow API
5 -
MLflow Artifacts
2 -
MLflow Experiment
6 -
MLflow Experiments
3 -
Mlflow Model
10 -
Mlflow registry
3 -
Mlflow Run
1 -
Mlflow Server
5 -
MLFlow Tracking Server
3 -
MLModels
2 -
Model Deployment
4 -
Model Lifecycle
6 -
Model Loading
2 -
Model Monitoring
1 -
Model registry
5 -
Model Serving
3 -
Model Serving Cluster
2 -
Model Serving REST API
6 -
Model Training
2 -
Model Tuning
1 -
Models
8 -
Module
3 -
Modulenotfounderror
1 -
MongoDB
1 -
Mount Point
1 -
Mounts
1 -
Multi
1 -
Multiline
1 -
Multiple users
1 -
Nested
1 -
New Feature
1 -
New Features
1 -
New Workspace
1 -
Nlp
3 -
Note
1 -
Notebook
6 -
Notification
2 -
Object
3 -
Onboarding
1 -
Online Feature Store Table
1 -
OOM Error
1 -
Open Source MLflow
4 -
Optimization
2 -
Optimize Command
1 -
OSS
3 -
Overwatch
1 -
Overwrite
2 -
Packages
2 -
Pandas udf
4 -
Pandas_udf
1 -
Parallel
1 -
Parallel processing
1 -
Parallel Runs
1 -
Parallelism
1 -
Parameter
2 -
PARAMETER VALUE
2 -
Partner Academy
1 -
Pending State
2 -
Performance Tuning
1 -
Photon Engine
1 -
Pickle
1 -
Pickle Files
2 -
Pip
2 -
Points
1 -
Possible
1 -
Postgres
1 -
Pricing
2 -
Primary Key
1 -
Primary Key Constraint
1 -
Progress bar
2 -
Proven Practices
2 -
Public
2 -
Pymc3 Models
2 -
PyPI
1 -
Pyspark
6 -
Python
21 -
Python API
1 -
Python Code
1 -
Python Function
3 -
Python Libraries
1 -
Python Packages
1 -
Python Project
1 -
Pytorch
3 -
Reading-excel
2 -
Redis
2 -
Region
1 -
Remote RPC Client
1 -
RESTAPI
1 -
Result
1 -
Runtime update
1 -
Sagemaker
1 -
Salesforce
1 -
SAP
1 -
Scalability
1 -
Scalable Machine
2 -
Schema evolution
1 -
Script
1 -
Search
1 -
Security
2 -
Security Exception
1 -
Self Service Notebooks
1 -
Server
1 -
Serverless
1 -
Serving
1 -
Shap
2 -
Size
1 -
Sklearn
1 -
Slow
1 -
Small Scale Experimentation
1 -
Source Table
1 -
Spark
13 -
Spark config
1 -
Spark connector
1 -
Spark Error
1 -
Spark MLlib
2 -
Spark Pandas Api
1 -
Spark ui
1 -
Spark Version
2 -
Spark-submit
1 -
SparkML Models
2 -
Sparknlp
3 -
Spot
1 -
SQL
19 -
SQL Editor
1 -
SQL Queries
1 -
SQL Visualizations
1 -
Stage failure
2 -
Storage
3 -
Stream
2 -
Stream Data
1 -
Structtype
1 -
Structured streaming
2 -
Study Material
1 -
Summit23
2 -
Support
1 -
Support Team
1 -
Synapse
1 -
Synapse ML
1 -
Table
4 -
Table access control
1 -
Tableau
1 -
Task
1 -
Temporary View
1 -
Tensor flow
1 -
Test
1 -
Timeseries
1 -
Timestamps
1 -
TODAY
1 -
Training
6 -
Transaction Log
1 -
Trying
1 -
Tuning
2 -
UAT
1 -
Ui
1 -
Unexpected Error
1 -
Unity Catalog
12 -
Use Case
2 -
Use cases
1 -
Uuid
1 -
Validate ML Model
2 -
Values
1 -
Variable
1 -
Vector
1 -
Versioncontrol
1 -
Visualization
2 -
Web App Azure Databricks
1 -
Weekly Release Notes
2 -
Whl
1 -
Worker Nodes
1 -
Workflow
2 -
Workflow Jobs
1 -
Workspace
2 -
Write
1 -
Writing
1 -
Z-ordering
1 -
Zorder
1
- « Previous
- Next »
User | Count |
---|---|
89 | |
39 | |
36 | |
25 | |
25 |