Stuck on an issue?

Lightrun Answers was designed to reduce the constant googling that comes with debugging 3rd party libraries. It collects links to all the places you might be looking at while hunting down a tough bug.

And, if you’re still stuck at the end, we’re happy to hop on a call to see how we can help out.

Dealing with StringType to varchar(256) limit in python

See original GitHub issue

Hi, I have seen #118 and also read the documentation which says

Note: Due to limitations in Spark, metadata modification is unsupported in 
the Python, SQL, and R language APIs.

While I understand this limitation, I’m wondering how a python user should deal with dataframes that have text columns with values exceeding 256 characters.

Im trying to save a dataframe to redshift where a column of type string has entries as large as 1000 characters and any hacks / workarounds will be appreciated 😃

Issue Analytics

State:
Created 7 years ago
Reactions:1
Comments:8 (1 by maintainers)

Top GitHub Comments

1reaction

pallavicommented, Apr 16, 2019

spark-redshift now lets you do this in version runtime-3.0. here’s an example: https://gist.github.com/pallavi/f83a45308ba8387f6b227c28aa209077

0reactions

ar-mscommented, Jun 18, 2020

I tried using the createTableColumnTypes option, it seems to work with postgres but not with spark-redshift which seems to ignore the option. The solution provided by @pallavi is working perfectly.