You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@hudi.apache.org by "Udit Mehrotra (Jira)" <ji...@apache.org> on 2021/08/25 09:23:00 UTC

[jira] [Updated] (HUDI-1779) Fail to bootstrap/upsert a table which contains timestamp column

     [ https://issues.apache.org/jira/browse/HUDI-1779?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Udit Mehrotra updated HUDI-1779:
--------------------------------
    Fix Version/s:     (was: 0.9.0)
                   0.10.0

> Fail to bootstrap/upsert a table which contains timestamp column
> ----------------------------------------------------------------
>
>                 Key: HUDI-1779
>                 URL: https://issues.apache.org/jira/browse/HUDI-1779
>             Project: Apache Hudi
>          Issue Type: Bug
>            Reporter: lrz
>            Priority: Major
>              Labels: pull-request-available, sev:high
>             Fix For: 0.10.0
>
>         Attachments: unsupportInt96.png, upsertFail.png, upsertFail2.png
>
>
> current when hudi bootstrap a parquet file, or upsert into a parquet file which contains timestmap column, it will fail because these issues:
> 1) At bootstrap operation, if the origin parquet file was written by a spark application, then spark will default save timestamp as int96(see spark.sql.parquet.int96AsTimestamp), then bootstrap will fail, it’s because of Hudi can not read Int96 type now.(this issue can be solve by upgrade parquet to 1.12.0, and set parquet.avro.readInt96AsFixed=true, please check [https://github|https://github/] <[https://github/]>.com/apache/parquet-mr/pull/831/files) 
> 2) after bootstrap, doing upsert will fail because we use hoodie schema to read origin parquet file. The schema is not match because hoodie schema  treat timestamp as long and at origin file it’s Int96 
> 3) after bootstrap, and partial update for a parquet file will fail, because we copy the old record and save by hoodie schema( we miss a convertFixedToLong operation like spark does)



--
This message was sent by Atlassian Jira
(v8.3.4#803005)