I was going through delta lake documentation page. There is a line like this : In the last line, we see a double assignment of same variable (spark). Does this do something different compared to : In general, in python, is there a meaning to double assignment of same variable ? Answer Short answer: It’s meaningless. Aside from a few
Tag: pyspark
Taking the recency time of client purchase with PySpark
The sample of the dataset I am working on: I’d like to take the customer’s most recent purchase (the customer’s date.max()) and the previous maximum purchase (the penultimate purchase) and take the difference between the two (I’m assuming the same product on all purchases). I still haven’t found something in pyspark that does this. One example of my idea was
Rename a redshift SQL table within PySpark Databricks
I want to rename a redshift table within a Python Databricks notebook. Currently I have a query that pulls in data and creates a table: I want to take this table I created and rename it. I referenced this doc but find it hard to follow. I want to run this SQL command alter table public.test rename to test_table_to_be_dropped in
Using join to find similarities between two datasets containing strings in PySpark
I’m trying to match text records in two datasets, mostly via using PySpark (not using libraries such as BM25 or NLP techniques as much as I can for now -using Spark ML and SparkNLP libraries are fine). I’m towards finishing the pre-processing phase. I’ve cleaned the text in both datasets, tokenized it and created bi-Grams (stored in a column called
Pyspark agg max function showing different result
I was just studying some pyspark code and didnt understand these particular lines. I have a python code such as below: When showing empDF after Isn’t it supposed to show the longest list? It is showing [Python , R] as the output ? I dont understand how is this output coming? Answer Pyspark’s max function returns the maximum value of
pyspark: turn array of dict to new columns
I am struggling to transform my pyspark dataframe which looks like this: to this: I tried to pivot and a bunch of others things but don’t get the result above. Note that I don’t have the exact number of dict in the column Tstring Do you know how I can do this? Answer Using transform function you can convert each
Parse multiple line CSV using PySpark , Python or Shell
Input (2 columns) : Note: Harry and Prof. does not have starting quotes Output (2 columns) What I tried (PySpark) ? Issue The above code worked fine where multiline had both start and end double quotes (For eg: row starting with Ronald) But it didnt work with rows where we only have end quotes but no start quotes (like Harry
PySpark – Selecting all rows within each group
I have a dataframe similar to below. From the above dataframe, I would like to keep all rows upto the most recent sale relative to the date. So essentially, I will only have unique date for each row. In the case of above example, output would look like: Can you please guide on how can I go to this result?
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
Why do I got TypeError: cannot pickle ‘_thread.RLock’ object when using pyspark
I’m using spark to deal with my data, like that: But I got this error from spark: Traceback (most recent call last): File “/private/var/www/http/hawk-scripts/hawk_etl/scripts/spark_rds_to_parquet.py”, line 46, in process() File “/private/var/www/http/hawk-scripts/hawk_etl/scripts/spark_rds_to_parquet.py”, line 36, in process result = spark.sparkContext.parallelize(dataframe_mysql, 1).map(func) File “/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/pyspark/python/lib/pyspark.zip/pyspark/context.py”, line 574, in parallelize File “/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/pyspark/python/lib/pyspark.zip/pyspark/context.py”, line 611, in _serialize_to_jvm File “/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/pyspark/python/lib/pyspark.zip/pyspark/serializers.py”, line 211, in dump_stream File “/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/pyspark/python/lib/pyspark.zip/pyspark/serializers.py”, line 133,