The recipe execution is taking long time due to handling a large volume of data in dataiku

Mohammed Faraz

We are experiencing long execution times for a recipe in Dataiku due to handing large datasets, while we have implemented partitioning using a filter on a specific column, it still takes 1.5-2 hours to partitioning 30M records. Is there a more efficient way to handle and process this data quickly and effectively because we'll be using more recipe throughout the flow like join, prepare sync etc..

Operating system used: Windows 11

Yasmine_T

Hi Mohammed,

I hope that you are doing well. This will be better handled through a support ticket so we can get more informations regarding your use case and work with you on performance improvement. Could you please submit a support ticket (https://support.dataiku.com/support/tickets/new)?

We will be able to best assist you there.

Best,

Yasmine

Turribeach

The recipe execution is taking long time due to handling a large volume of data in dataiku

Mohammed Faraz

Mar 24, 2025

We are experiencing long execution times for a recipe in Dataiku due to handing large datasets, while we have implemented partitioning using a filter on a specific column, it still takes 1.5-2 hours to partitioning 30M records. Is there a more efficient way to handle and process this data quickly and effectively because we'll be using more recipe throughout the flow like join, prepare sync etc..

Operating system used: Windows 11

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What type of connection is your dataset using?

I will suggest you move away from partitioning data in Dataiku. Partitioning data in Dataiku does not improve performance like in other technologies, it merely avoids having to compute the whole dataset. This may reduce compute time but it introduces a whole set of limitations and issues when using partitions in Dataiku. If you only aim for using partitioning in Dataiku is performance you should move away from that and look at data technologies that can handle your datasets matching your performance requirements. A few samples are Databricks, BigQuery or Snowflake.