[GitHub] [hudi] pengzhiwei2018 commented on pull request #3393: [HUDI-1842] Spark Sql Support For The Exists Hoodie Table
pengzhiwei2018 commented on pull request #3393: URL: https://github.com/apache/hudi/pull/3393#issuecomment-894607773 @hudi-bot run azure -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: commits-unsubscr...@hudi.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [hudi] pengzhiwei2018 commented on pull request #3393: [HUDI-1842] Spark Sql Support For The Exists Hoodie Table
pengzhiwei2018 commented on pull request #3393: URL: https://github.com/apache/hudi/pull/3393#issuecomment-894603173 @hudi-bot run azure -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: commits-unsubscr...@hudi.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [hudi] pengzhiwei2018 commented on pull request #3393: [HUDI-1842] Spark Sql Support For The Exists Hoodie Table
pengzhiwei2018 commented on pull request #3393: URL: https://github.com/apache/hudi/pull/3393#issuecomment-892526491 -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: commits-unsubscr...@hudi.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [hudi] pengzhiwei2018 commented on pull request #3393: [HUDI-1842] Spark Sql Support For The Exists Hoodie Table
pengzhiwei2018 commented on pull request #3393: URL: https://github.com/apache/hudi/pull/3393#issuecomment-893180101 > > > > Hey peng. I did a round of testing on this patch. Here are my findings. > > > > Insert into is till prefixing col name to meta fields. (3rd col and 4th col) > > > > ``` > > > > select * from hudi_ny where tpep_pickup_datetime like '%00:04:03%'; > > > > 20210802105420 20210802105420_2_23 2019-01-01 00:04:03 2019-01-01 c5e6a617-dfc5-4051-8c1a-8daead3847af-0_2-37-62_20210802105420.parquet 2 2019-01-01 00:04:03 2019-01-01 00:11:48 1 3.011 N 137 262 1 10.00.5 0.5 2.260.0 0.3 13.56 NULL2019-01-01 > > > > 20210803162030 20210803162030_0_1 tpep_pickup_datetime:2021-01-01 00:04:03date_col=2021-01-01 c5c72f9e-9a63-48ca-a981-4302890f5210-0_0-27-1635_20210803162030.parquet 2 2021-01-01 00:04:03 2021-01-01 00:11:48 1 3.011 N 137 262 10.00.5 0.5 2.260.0 0.3 13.56 NULL 2021-01-01 > > > > Time taken: 0.524 seconds, Fetched 2 row(s) > > > > ``` > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > 1st row was part of the table before onboarding to spark-sql. > > > > 2nd row was inserted using insert into. > > > > Hi @nsivabalan , I know the difference now. The spark sql use the `SqlKeyGenerator` which is a sub-class of `ComplexKeyGenerator` to generated record key which will add the column name to the record key. While the `SimpleKeyGenerator` will not do that. So we should keep the behavior the same for `ComplexKeyGenerator` and `SimpleKeyGenerator`. > > > > > > > > > sorry, I don't get you. I understand SqlKeyGenerator extends from ComplexKeyGen. but why do we need to keep the same for SimpleKeyGen? We should not add any field prefix for SimpleKeyGen. If not, no updates will work for an existing table. > > > > > > Hi @nsivabalan , Have solved the record key not matched issue. Please take a test again~ > > @pengzhiwei2018 I tested the patch. I can see the column names are no longer being prefixed. Updates and deletes by record key is working fine now. However., the uri encoding of partition path is still an issue. For example, I did an insert to an existing partition. The insert was successful but it created a new partition as below: > > ``` > insert into hudi_trips_cow values(1.0, 2.0, "driver_2", 3.0, 4.0, 100.0, "rider_2", 12345, "765544i-e89b-12d3-a456-42665544", "americas/united_states/san_francisco/"); > > % ls -l /private/tmp/hudi_trips_cow > total 0 > drwxr-xr-x 4 sagars wheel 128 Aug 4 16:49 americas > drwxr-xr-x 6 sagars wheel 192 Aug 4 16:50 americas%2Funited_states%2Fsan_francisco%2F > drwxr-xr-x 3 sagars wheel 96 Aug 4 16:49 asia > ``` Hi @codope , can you drop the table and create again with the latest code of this patch. I am afraid this happen because you create the table by the old code of the patch. I have fix this issue in the latest . -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: commits-unsubscr...@hudi.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [hudi] pengzhiwei2018 commented on pull request #3393: [HUDI-1842] Spark Sql Support For The Exists Hoodie Table
pengzhiwei2018 commented on pull request #3393: URL: https://github.com/apache/hudi/pull/3393#issuecomment-892526491 > > Hey peng. I did a round of testing on this patch. Here are my findings. > > Insert into is till prefixing col name to meta fields. (3rd col and 4th col) > > ``` > > select * from hudi_ny where tpep_pickup_datetime like '%00:04:03%'; > > 20210802105420 20210802105420_2_23 2019-01-01 00:04:03 2019-01-01 c5e6a617-dfc5-4051-8c1a-8daead3847af-0_2-37-62_20210802105420.parquet 2 2019-01-01 00:04:03 2019-01-01 00:11:48 1 3.011 N 137 262 1 10.00.5 0.5 2.260.0 0.3 13.56 NULL2019-01-01 > > 20210803162030 20210803162030_0_1 tpep_pickup_datetime:2021-01-01 00:04:03date_col=2021-01-01 c5c72f9e-9a63-48ca-a981-4302890f5210-0_0-27-1635_20210803162030.parquet 2 2021-01-01 00:04:03 2021-01-01 00:11:48 1 3.011 N 137 262 10.00.5 0.5 2.260.0 0.3 13.56 NULL 2021-01-01 > > Time taken: 0.524 seconds, Fetched 2 row(s) > > ``` > > > > > > > > > > > > > > > > > > > > > > > > 1st row was part of the table before onboarding to spark-sql. > > 2nd row was inserted using insert into. > > Hi @nsivabalan , I know the difference now. The spark sql use the `SqlKeyGenerator` which is a sub-class of `ComplexKeyGenerator` to generated record key which will add the column name to the record key. While the `SimpleKeyGenerator` will not do that. So we should keep the behavior the same for `ComplexKeyGenerator` and `SimpleKeyGenerator`. > > sorry, I don't get you. I understand SqlKeyGenerator extends from ComplexKeyGen. but why do we need to keep the same for SimpleKeyGen? We should not add any field prefix for SimpleKeyGen. If not, no updates will work for an existing table. Hi @nsivabalan , Have solved the record key not matched issue. Please take a test again~ -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: commits-unsubscr...@hudi.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
