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Tag: pyspark

PySpark Incremental Count on Condition

Given a Spark dataframe with the following columns I am trying to construct an incremental/running count for each id based on when the contents of the event column evaluate to True. Here a new column called results would be created that contained the incremental count. I’ve tried using window functions but am stumped at this point. Ideally, the solution would

Filter expected value from list in df column

I have a data frame with the following column: I want to return a column with single value based on a conditional statement. I wrote the following function: When running the function on the column df.withColumn(“col”, filter_func(“raw_col”)) I have the following error col should be Column What’s wrong here? What should I do? Answer You can use array_contains function: But

How to use Selenium in Databricks and accessing and moving downloaded files to mounted storage and keep Chrome and ChromeDriver versions in sync?

I’ve seen a couple of posts on using Selenium in Databricks using %shto install Chrome Drivers and Chrome. This works fine for me, but I had a lot of trouble when I needed to download a file. The file would download, but I could not find it in the filesystem in databricks. Even if I changed the download path when

Spread List of Lists to Sparks DF with PySpark?

I’m currently struggling with following issue: Let’s take following List of Lists: How can I create following Sparks DF out of it with one row per element of each sublist: The only way I’m getting this done is by processing this list to another list with for-loops, which basically then already represents all rows of my DF, which is probably

Importing count() data for use within bokeh

I am trying to create a visualisation using the bokeh package which I have imported into the Databricks environment. I have transformed the data from a raw data frame into something resembling the following (albeit much larger): From there, I wish to create a line graph using the bokeh package to show the number of papers released per month (for

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