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Data Engineering
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Network bottleneck

jenshumrich
Contributor

Within a script, I noticed that the network connection between driver and the mounted network drives is often a huge bottleneck. It seems that the network through speed is unreasonable low for being an Azure 

  • Single node: Standard_DS12_v2 ยท DBR: 14.3.x-photon-scala2.12

Are there some ways how to improve upon the storing of a result to an Azure Blob storage? My current code looks like this:

joined_df.write.partitionBy("IdStation").mode("overwrite").parquet("/mnt/temp_folder")
 
Especially the IO wait of the CPU is more than just weird.
1 ACCEPTED SOLUTION

Accepted Solutions

filipniziol
Contributor III

Hi @jenshumrich ,

There is partitioning by IdStation. How many partitions are created? Isn't it a problem with too many files?
The partition size should around 1 GB and the file size should be or around 128 MB.

I see a lot of IO wait, so this would go in line with my suspicion that too many files are created.


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4 REPLIES 4

jenshumrich
Contributor

cpu.JPG

โ€ƒ

network.JPG

โ€ƒHere you can see the really slow network traffic, causing iowait on the CPU

filipniziol
Contributor III

Hi @jenshumrich ,

There is partitioning by IdStation. How many partitions are created? Isn't it a problem with too many files?
The partition size should around 1 GB and the file size should be or around 128 MB.

I see a lot of IO wait, so this would go in line with my suspicion that too many files are created.


ZoeCole
New Contributor II

Thank you.

jenshumrich
Contributor

You are right. I am creating 200 small files with the size of roughly 6 MB (in the quality system) and a few 100000s files in production. The partition is motivated by the original business need and further processing. Let me test with a the different partitioning. 

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