rdblue edited a comment on pull request #19:
URL: https://github.com/apache/iceberg-docs/pull/19#issuecomment-1022430192
I have the same reaction as @RussellSpitzer. I like the visualization of
snapshots, but I don't consider rollback to be time travel. Rollback alters the
state of the table, while time travel actually reads older versions.
The trouble here is that there isn't a good SQL demonstration of time travel
yet. We've added table names for time travel in 3.2, but we're waiting for
Spark 3.3 to get the `AS OF TIMESTAMP` and `AS OF VERSION` syntax. Maybe we
should use those anyway? Or maybe we should use Spark's dataframe syntax to
demo time travel right now:
```scala
spark.read.option("as-of-timestamp", System.currentTimeMillis() -
ONE_DAY_MS).load("db.table)
```
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