majian1998 opened a new pull request, #10419:
URL: https://github.com/apache/hudi/pull/10419
In the current version, HoodieFileIndex is a member variable of
HoodieBaseRelation. PR #7871 has made Hudi's acquisition of Relation behave
more like Spark's. However, in Spark, the relation is cached as follows:
```
catalog.getCachedPlan(qualifiedTableName, () => {
val dataSource = DataSource(
sparkSession,
userSpecifiedSchema = if (table.schema.isEmpty) None else
Some(table.schema),
partitionColumns = table.partitionColumnNames,
bucketSpec = table.bucketSpec,
className = table.provider.get,
options = dsOptions,
catalogTable = Some(table)
)
LogicalRelation(dataSource.resolveRelation(checkFilesExist = false), table)
})
```
This results in the continuous use of the same HoodieFileIndex instance.
However, HoodieFileIndex contains cached items like cachedAllPartitionPaths
and cachedAllInputFileSlices, which only reset upon creating a new
HoodieFileIndex. A sparkSession will only execute refreshTable when actions
like 'insert' are performed. If HoodieFileIndex is never refreshed, then a
SparkSession that only executes queries will always see the version that was
cached during the initial query. This is not the expected behavior. In
practice, Delta Lake seems to attempt updating the snapshot with each listFiles
operation. After PR #7871, Hudi would recreate the relation with each query,
obtaining the latest snapshot. Therefore, I believe there should be an
assessment at the start of listFiles to determine whether the cache (snapshot)
needs to be updated.
### Change Logs
Determine Whether to Update Cache Based on Timeline Changes Before Listing
Files
### Impact
None
### Risk level (write none, low medium or high below)
medium
### Documentation Update
None
### Contributor's checklist
- [ ] Read through [contributor's
guide](https://hudi.apache.org/contribute/how-to-contribute)
- [ ] Change Logs and Impact were stated clearly
- [ ] Adequate tests were added if applicable
- [ ] CI passed
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