TheR1sing3un opened a new pull request, #13188:
URL: https://github.com/apache/hudi/pull/13188
Fix the incorrect data read after changing the column type from float to
double
There are two reasons for the above problems：
1. `InternalSchemaCache` cannot obtain the path of the commit file
correctly. Because after version 1.x, we placed the commit file separately in
the `timeline` directory. However, `InternalSchemaCache` still retrievals files
from `basePath/.hoodie`, thus failing to obtain the correct schema.
2. When we read parquet file without `enableVectorizedReader`, we use spark
's `CAST` for type conversion when we need to do scheme evolution, but spark
has a loss of precision when dealing with `CAST` that converts `float` to
`double`.
Change logs:
1. pass the correct timeline path for `InternalSchemaCache`
2. for schema evolution without `enableVectorizedReader`, for the case
`CAST(FLOAT as DOUBLE)` we turn it to `CAST(CAST(FLOAT as STRING) as DOUBLE)`.
### Change Logs
1. pass the correct timeline path for `InternalSchemaCache`
2. for schema evolution without `enableVectorizedReader`, for the case
`CAST(FLOAT as DOUBLE)` we turn it to `CAST(CAST(FLOAT as STRING) as DOUBLE)`.
_Describe context and summary for this change. Highlight if any code was
copied._
### Impact
fix the incorrectness after change data type from float to double
### Risk level (write none, low medium or high below)
low
### Documentation Update
none
- _The config description must be updated if new configs are added or the
default value of the configs are changed_
- _Any new feature or user-facing change requires updating the Hudi website.
Please create a Jira ticket, attach the
ticket number here and follow the
[instruction](https://hudi.apache.org/contribute/developer-setup#website) to
make
changes to the website._
### Contributor's checklist
- [x] Read through [contributor's
guide](https://hudi.apache.org/contribute/how-to-contribute)
- [x] Change Logs and Impact were stated clearly
- [x] Adequate tests were added if applicable
- [x] CI passed
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