-
Notifications
You must be signed in to change notification settings - Fork 2.4k
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
[SUPPORT] - Performance Variation in Hudi 0.14 #11481
Comments
@RuyRoaV Can you provide event logs or spark UI. On configurations, I recommend not to use archive beyond save point. You can also try to use SIMPLE index once. As for some of the usecases where most of the file groups are updated, SIMPLE index perform much better. |
Hello @ad1happy2go I have attached some screenshots of the Spark UI. Is there any specific screen that you'd like to see? Thanks for the input, will take that into account. I've also seen on some other GitHub issues, seen changing to and RLI index being recommended. Would that work for a COW table? or would the SIMPLE index still be a better approach? Best regards, |
@RuyRoaV RLI will work if you need global index. It works for COW table as well. |
Hi Aditya I have tried out your recommendation and found the following: ** Using SIMPLE INDEX** The average execution time was reduced from 20 min to around 11 min, which is great. In the Spark UI screenshot, you can see that a big percentage of the execution time is taken by a We are in a need to reduce the job runtime even more, is there any other recommendation regarding the different configurations that we can set? We may try deactivating of the archival beyond the savepoint a bit later. But I am curious about why would that help us improve in performance? Using RECORD LEVEL I replaced the index for a table, for which its upsert Glue job was already running in under 5 minutes. Overall, the job runtime has remained the same, being I'll try with one of our long running jobs and will let you know the outcome. By the way is there a way to check the index type of a table? Thanks Best regards |
I think the table index type is set with "hoodie.index.type=" when writing. I don't think it is set on the table property level. BTW, Can you share the number of records ( and size ) in a batch? |
@RuyRoaV Do you still see any more performance issues. Let us know. Yo check index you can see details of the running jobs in spark UI. |
Hi @ad1happy2go We are still seeing performance issues. Right now we are trying to see which combination of parameters might help. But we are a bit lost in which parameters we need to tweak. To give a bit more of context of how our table will be upserted:
The bottle neck in our Glue job is this task where some of our executors will be stuck for ~15 min, whereas other executors will finish their task in ~2 min You can find here the logs of one of our executors: Th bottleneck is task 63, which starts at 15:11:51 and finishes at 15:28:57. What I have seen in the logs is that the
Would you be able to shed some light in why this could be happening? and how can we optimize the data writing? Thanks. Best regards. |
Describe the problem you faced
We have a Glue 4.0 job to perform an upsert on a Hudi managed COW table. In some occasions, the Glue job runs in under 5 minutes, whereas in others it runs for up to 20 minutes. Moreover, we have noticed that, in those instances, the job is performing a count at
HoodieSparkSqlWriter.scala:1072
action for over 17 minutes; in other job runs this only takes around 1 minute.Regarding some specifications for the table:
We have 3 partition fields:
A precombine field:
and 3 recordkey fields:
You can see more about the table description here:
We are also using a BLOOM type index and these are some other configurations that we are setting.
Could you please advise us on which actions we should take to bring down the execution time?
Expected behavior
We would like to understand why we are looking this variation in the execution times and advice on the actions needed
to prevent this behaviour.
Environment Description
Glue version: 4
Worker Type: G.2x
Hudi version : 0.14.1
Spark version : 3.3
Max DPU Capacity: 120
Storage (HDFS/S3/GCS..) : S3
Running on Docker? (yes/no) : No
The text was updated successfully, but these errors were encountered: