I am attempting to connect to a SQL Server from an Azure Databricks notebook using the pyodbc Python library. When I run the query, I encounter the following error: Error: ('01000', "[01000] [unixODBC][Driver Manager]Can't open lib 'ODBC Driver 17 for…
I am trying to load multiple documents into the MongoDb collection using databricks pyspark and while loading I am using updateDate filed as well , but after loading I could see updateDate field data type is string instead date data…
I recently encounter an issue with legacy dbx databricks cli installed via pip when running below command somehow the notebook parameters passed in environment variable is not picking up. databricks jobs run-now --job-id '$db_id' --notebook-params '$db_job_np' --version "2.1" Error: Error:…
I want to mount my ADLS2 storage into a Databricks workspace without sharing the data with every user in the workspace. We have multiple teams working on different clusters in the same workspace so we want to keep the data…
We want to enable the access for the users to create token. Now, I have logged in to the databricks account using the admin access, and I go to "Access Control" -> "Personal Access Tokens" and I want to enable…
in Azure databricks, need to connect to a table in odbc sql server and create a dataframe and create exactly the same table in databricks I have already completed the below codes and I can see as attached. How to…
In Pyspark, I have 2 dataframe. 1st dataframe say df1 is empty dataframe created from a schema. 2nd dataframe df2 is non-empty dataframe filled from a csv file. Now I want to merge such that all below scenarios are covered.…
Using autoloader, I am reading some continues data from storage to Databricks Delta Live table. The declaration of data pipeline is as follows. import dlt from pyspark.sql.functions import * from pyspark.sql.types import * sch = "StructType([StructField('Date', StringType(), True), StructField('machine', StringType(),…
I am trying to run the following code iter_max = 100 CC = 1 save_model = False with mlflow.start_run(run_name=run_name, experiment_id=experiment.experiment_id, nested=True) as run: text_clf = Pipeline([ ('vect', CountVectorizer()), ('tfidf', TfidfTransformer()), ('clf',LogisticRegression(max_iter=iter_max, C=CC))]) text_clf.fit(X_train, y_train) run_id = mlflow.active_run().info.run_id` But I get…
I have below pyspark row type data: indv_msg = [Row(cbm_json_output=Row(country_code='USA', date='06-10-2023', date_epoch='1696550400', id='USA-001535-1696550400', interfaceVersion='1.0.0', opmode_car_door=Row(health_category='GREEN', msg_id='1', num_yellow_preds_in_last_14_days=0, reason=None, reasonDetail=None), opmode_landing_door=Row(health_category='GREEN', msg_id='1', reason=None, reasonDetail=None), sensor=Row(component_type=None, health_category=None, landing_priority=None, msg_id='1', num_yellow_preds_in_last_14_days=None, reason=None, reasonDetail=None), unit_id='001535')) While trying to convert to json string, it is…