zhangdove commented on issue #1230:
URL: https://github.com/apache/iceberg/issues/1230#issuecomment-713372597
When Analyzing Iceberg's Catalog, I find that There is still an issue left
here, and I have made some new discoveries:
`spark.read.format("iceberg").load("hdfs://nn:8020/path/to/table")` By this
way, Iceberg table loading does not use the Iceberg Catalog. Of course,
Iceberg's metadata information will not be cached. Instead, Iceberg Table will
be obtained directly by using `IcebergSource.findTable(options,conf)`.
However, when Iceberg table is loaded using `spark.table("prod.db.table")`,
CachingCatalog(`cache-enabled`default value is true) automatically looks for
Iceberg table from the cache(Caffeine Cache).
Finally, whether it is incorrect that I find that the description of the
document [in this
place](https://github.com/apache/iceberg/blob/master/site/docs/spark.md#querying-with-dataframes)?
The correct description should not be this ?
`Using spark.table("prod.db.table") loads an isolated table reference that
is not refreshed when other queries update the table.`
@rdblue How do you think this description? Should we update this place?
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