How to even start a basic query in databricks using python? The data I need is in databricks and so far I have been using Juypterhub to pull the data and modify few things. But now I want to eliminate a step of pulling the data in Jupyterhub and directly move my python code in databricks then schedule the job.
Tag: databricks
pandas to_excel converts _x10e6 _ to ღ. How do I avoid this?
I have been trying to create an excel file with several sheets from delta tables, however some of my column names include _x10e6 _ which is apparently translated to ღ. I have tried to use encoding=’unicode_escape’ and encoding=’utf-8′ without luck. I cannot use xlsxwriter because I am appending to an existing file. Does anybody know how I can keep _x10e6
Counting consecutive occurrences of a specific value in PySpark
I have a column named info defined as well: I would like to count the consecutive occurrences of 1s and insert 0 otherwise. The final column would be: I tried using the following function, but it didn’t work. Answer From Adding a column counting cumulative pervious repeating values, credits to @blackbishop
Is there a more efficient way to write code for bin values in Databricks SQL?
I am using Databricks SQL, and want to understand if I can make my code lighter: Instead of writing each line, is there a cool way to state that all of these columns starting with “age_” need to be null in 1 or 2 lines of code? Answer If each bin is a column then you probably are going to
SAS Proc Transpose to Pyspark
I am trying to convert a SAS proc transpose statement to pyspark in databricks. With the following data as a sample: I would expect the result to look like this I tried using the pandas pivot_table() function with the following code however I ran into some performance issues with the size of the data: Is there a way to translate
Using .withColumn on all remaining columns in DF
I want to anonymize or replace almost all columns in a pyspark dataframe except a few ones. I know its possible to do something like: However, doing this for all columns is a tedious process. I would rather want to do something along the lines of this: This does however not seem to work. Is there other work arounds that
Pandas UDF throws error not of required length
I have a delta table which has thrift data from kafka and I am using a UDF to deserialize it. I have no issues when I use regular UDF, but I get an error when I try to use Pandas UDF. This runs fine i.e. ruglar UDF But when I use Pandas UDF I get an error PythonException: ‘RuntimeError: Result
Multi-processing in Azure Databricks
I have been tasked lately, to ingest JSON responses onto Databricks Delta-lake. I have to hit the REST API endpoint URL 6500 times with different parameters and pull the responses. I have tried two modules, ThreadPool and Pool from the multiprocessing library, to make each execution a little quicker. ThreadPool: How to choose the number of threads for ThreadPool, when
How to Send Emails From Databricks
I have used the code from Send email from Databricks Notebook with attachment to attempt sending code from my Databricks Community edition: I have used the following code: As you can see the code is almost identical. However, when I run the code I get the following error: Is this error also because I’m running on Databricks Community edition, as
How to get conditional values into new column from several external lists or arrays
I have the following dataframe: To which I have to create an additional column new_col_cond that is dependent on the values of multiple external lists/arrays (I have also tried with dictionaries), for example: The new column depends on the value of ratio and selects from either array according to id as index. I have tried: with errors coming. I assume