[jira] [Commented] (HUDI-1668) GlobalSortPartitioner is getting called twice during bulk_insert.

["Nishith Agarwal (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/HUDI-1668?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17350651#comment-17350651 ] 

Nishith Agarwal commented on HUDI-1668:
---------------------------------------

[~shivnarayan] [~sugamberku] Spark has a 3 stage sorting technique
 # In the first stage, spark will do a sample scan of the data to find how many partitions should this data be mapped to if it were to be sorted
 # In the second stage, spark will do the actual sorting of this data by writing data to N different buckets/partitions known as mappers.
 # In the third stage, the data will be pulled by the reducers using external sorting techniques (this is only seen in the stage of the job consuming this data)

Having 2 stages for sorting is pretty common. if you need more information, this can be found out here -> [https://stackoverflow.com/questions/51831696/what-happens-under-the-hood-when-you-sort-a-dataframe-in-spark]

 

 

> GlobalSortPartitioner is getting called twice during bulk_insert.
> -----------------------------------------------------------------
>
>                 Key: HUDI-1668
>                 URL: https://issues.apache.org/jira/browse/HUDI-1668
>             Project: Apache Hudi
>          Issue Type: Bug
>            Reporter: Sugamber
>            Priority: Minor
>              Labels: sev:high, user-support-issues
>         Attachments: 1st.png, 2nd.png, Screen Shot 2021-04-17 at 11.23.17 AM.png, Screenshot 2021-04-21 at 6.40.19 PM.png, Screenshot 2021-04-21 at 6.40.40 PM.png
>
>
> Hi Team,
> I'm using bulk insert option to load close to 2 TB data. The process is taking near by 2 hours to get completed. While looking at the job log, it is identified that [sortBy at GlobalSortPartitioner.java:41|https://gdlcuspc1a3-6.us-central1.us.walmart.net:18481/history/application_1614298633248_1444/1/jobs/job?id=1] is running twice. 
> It is getting triggered at 1 stage. *refer this screenshot ->[^1st.png]*.
> Second time it is getting trigged from  *HoodieSparkSqlWriter.scala:433* *[count at HoodieSparkSqlWriter.scala:433|https://gdlcuspc1a3-6.us-central1.us.walmart.net:18481/history/application_1614298633248_1444/1/jobs/job?id=2]*   step.
> In both cases, same number of job got triggered and running time is close to each other. *Refer this screenshot* -> [^2nd.png]
> Is there any way to run only one time so that data can be loaded faster or it is expected behaviour.
> *Spark and Hudi configurations*
>  
> {code:java}
> Spark - 2.3.0
> Scala- 2.11.12
> Hudi - 0.7.0
>  
> {code}
>  
> Hudi Configuration
> {code:java}
> "hoodie.cleaner.commits.retained" = 2  
> "hoodie.bulkinsert.shuffle.parallelism"=2000  
> "hoodie.parquet.small.file.limit" = 100000000  
> "hoodie.parquet.max.file.size" = 128000000  
> "hoodie.index.bloom.num_entries" = 1800000  
> "hoodie.bloom.index.filter.type" = "DYNAMIC_V0"  
> "hoodie.bloom.index.filter.dynamic.max.entries" = 2500000  
> "hoodie.bloom.index.bucketized.checking" = "false"  
> "hoodie.datasource.write.operation" = "bulk_insert"  
> "hoodie.datasource.write.table.type" = "COPY_ON_WRITE"
> {code}
>  
> Spark Configuration -
> {code:java}
> --num-executors 180 
> --executor-cores 4 
> --executor-memory 16g 
> --driver-memory=24g 
> --conf spark.rdd.compress=true 
> --queue=default 
> --conf spark.serializer=org.apache.spark.serializer.KryoSerializer
> --conf spark.executor.memoryOverhead=1600 
> --conf spark.driver.memoryOverhead=1200 
> --conf spark.driver.maxResultSize=2g
> --conf spark.kryoserializer.buffer.max=512m 
> {code}



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