Converting PySpark to Pandas in Synapse results in error

Ganapathy Subramanian 20 Microsoft Employee

I'm new to Synapse but have experience with Python. In the process of converting PySpark to Pandas, I'm encountering an error which reads:

/opt/spark/python/lib/pyspark.zip/pyspark/sql/pandas/conversion.py:201: UserWarning: toPandas attempted Arrow optimization because 'spark.sql.execution.arrow.pyspark.enabled' is set to true, but has reached the error below and can not continue. Note that 'spark.sql.execution.arrow.pyspark.fallback.enabled' does not have an effect on failures in the middle of computation.

Does anyone have any suggestions for resolving this issue?

phemanth 11,900 Reputation points Microsoft Vendor

2024-04-03T14:03:18.5533333+00:00
@Ganapathy Subramanian

Thanks for reaching out to Microsoft Q&A.

The error message you're encountering in Synapse Workspace indicates an issue during the conversion of a PySpark DataFrame to a Pandas DataFrame using .toPandas(). It seems Arrow optimization, enabled by the configuration spark.sql.execution.arrow.pyspark.enabled, is failing midway through the process.

Here are some suggestions to address this issue:

**Increase Driver Memory:**The most likely culprit is insufficient memory allocated to the Spark driver. The conversion process might be trying to hold the entire DataFrame in memory, causing issues. Try increasing the driver memory using the Synapse Workspace configuration options. This will provide more space for the driver to handle the conversion.

**Disable Arrow Optimization (Temporarily):**Arrow is a columnar data format that can improve performance during the conversion process. However, in your case, it seems to be causing problems. You can temporarily disable Arrow optimization by setting spark.sql.execution.arrow.pyspark.enabled to false. This might be a good option for troubleshooting purposes.

**Reduce DataFrame Size (if possible):**If your DataFrame is very large, converting it entirely to Pandas might not be feasible. Consider filtering or sampling the data in PySpark before conversion to reduce its size. This will make the conversion process less memory-intensive.

**Alternative Conversion Methods:**Depending on your use case, there might be alternative approaches to achieve what you need without converting the entire DataFrame to Pandas. Look into functionalities offered by Koalas, a library that allows using Pandas-like operations on PySpark DataFrames.

Remember, disabling Arrow optimization might not be the ideal long-term solution. Investigate the root cause of the Arrow failure and consider increasing memory allocation or exploring alternative conversion methods for better performance.

Hope this helps. Do let us know if you any further queries.
Ganapathy Subramanian 20 Reputation points Microsoft Employee

2024-04-03T19:36:20.57+00:00

Thanks for the response, i tried disabling "**Disable Arrow Optimization (Temporarily):spark.sql.execution.arrow.pyspark.enabled to false. ". It didn't worked for me. From your recommendation i can see memory is the culprit let me try your options.
phemanth 11,900 Reputation points Microsoft Vendor

2024-04-05T05:34:04.1033333+00:00

@Ganapathy Subramanian We haven’t heard from you on the last response and was just checking back to see if you have a resolution yet. In case if you have any resolution please do share that same with the community as it can be helpful to others. Otherwise, will respond with more details and we will try to help.
Ganapathy Subramanian 20 Reputation points Microsoft Employee

2024-04-06T22:17:52.2266667+00:00

Instead of converting whole data to pandas, i changed the plan to convert only the pivot values. This didn't caused the issues & it worked.
phemanth 11,900 Reputation points Microsoft Vendor

2024-04-07T04:20:29.6866667+00:00

@Ganapathy Subramanian Glad to know your issue has been resolved. Since the Microsoft Q&A community has a policy that "The question author cannot accept their own answer. They can only accept answers by others "I'll repost your solution in case you'd like to accept the answer.

Accepted answer

phemanth 11,900 Reputation points Microsoft Vendor

2024-04-07T04:18:54.1733333+00:00

@Ganapathy Subramanian Welcome to Microsoft Q&A platform and thanks for posting your question.

I'm glad that you were able to resolve your issue and thank you for posting your solution so that others experiencing the same thing can easily reference this! Since the Microsoft Q&A community has a policy that "The question author cannot accept their own answer. They can only accept answers by others "I'll repost your solution in case you'd like to accept the answer.

Ask: I'm new to Synapse but have experience with Python. In the process of converting PySpark to Pandas, I'm encountering an error which reads:

/opt/spark/python/lib/pyspark.zip/pyspark/sql/pandas/conversion.py:201: UserWarning: toPandas attempted Arrow optimization because 'spark.sql.execution.arrow.pyspark.enabled' is set to true, but has reached the error below and can not continue. Note that 'spark.sql.execution.arrow.pyspark.fallback.enabled' does not have an effect on failures in the middle of computation.

Does anyone have any suggestions for resolving this issue?

Solution: Instead of converting whole data to pandas, i changed the plan to convert only the pivot values. This didn't caused the issues & it worked.

If I missed anything please let me know and I'd be happy to add it to my answer, or feel free to comment below with any additional information.

If you have any other questions, please let me know. Thank you again for your time and patience throughout this issue.

Please don’t forget to Accept Answer and Yes for "was this answer helpful" wherever the information provided helps you, this can be beneficial to other community members.
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