There are a variety of ways to filter strings in PySpark, each with their own advantages and disadvantages. This post will consider three of the…
Category: Data Science
Following on from my pandas to pyspark cheatsheet here is another cheatsheet to help convert SQL queries into PySpark dataframe commands. Like the last one…
Recently the Apache Foundation have released a very useful new storage format for use with Spark called Delta. Delta is an extension to the parquet…
Pyspark is very powerful. However because it is based on Scala we need to be careful about types as they are not Pythonic. And because…
If you work in data science you have probably come across the pipeline model for handling data transformations. It is used by many machine learning…
I recently gave a talk at PyData Edinburgh about some of the work I am doing at QueryClick. We investigated the effectiveness of TV and…
This is a follow on post from my last post about starting with PySpark and Databricks. Here is a link to a table I have…
Databricks is a very handy cloud platform for large scale data processing and machine learning using Spark. However it does have some idiosyncrasies. Here are…
Occasionally you may want to invoke a stored procedure from your python code in order to manipulate data as part of a larger task. Naively…
In the last blog post I discussed using SQL Alchemy to import SQL database data into pandas for data analysis. But what if you wish…