cccs-jc opened a new issue, #10156:
URL: https://github.com/apache/iceberg/issues/10156
### Apache Iceberg version
1.5.0 (latest release)
### Query engine
Spark
### Please describe the bug 🐞
When using spark readStream the option `stream-from-timestamp` is used to
position the read at the specified timestamp. The query below uses the current
time to read from the head of the queue.
```python
ts = int(time.time() * 1000)
df = spark.readStream.format("iceberg")
.option("streaming-skip-delete-snapshots", True)
.option("streaming-skip-overwrite-snapshots", True)
.option("streaming-max-files-per-micro-batch", max_files)
.option("streaming-max-rows-per-micro-batch", max_rows)
.option("stream-from-timestamp", ts)
.load(source_table)
```
You can kill your streaming job and wait 10 minutes. Then start it again.
The readStream will load the checkpointed offset from disk and is supposed to
read from that offset. However, there is a bug that cause it to skip the
commits that occurred in that 10 minutes and instead the readStream reads from
the latest commit.
I can work around this bug by not specifying the `stream-from-timestamp` if
the query uses the checkpointed offset.
```python
ts = int(time.time() * 1000)
use_ts = checkpoint_dir_exists(checkpoint_location) == False
df = (
get_spark().readStream.format("iceberg")
.option("streaming-skip-delete-snapshots", True)
.option("streaming-skip-overwrite-snapshots", True)
.option("streaming-max-files-per-micro-batch", max_files)
.option("streaming-max-rows-per-micro-batch", max_rows)
)
if use_ts:
df = df.option("stream-from-timestamp", ts)
df = df.load(source_table)
```
But this is error prone. As a user I expect the readStream to continue from
the last checkpointed offset.
I suspect the issue might be here.
https://github.com/apache/iceberg/blob/fc5b2b336c774b0b8b032f7d87a1fb21e76b3f20/spark/v3.5/spark/src/main/java/org/apache/iceberg/spark/source/SparkMicroBatchStream.java#L326
This seems to short-circuit the saved `startOffset` by checking of the last
snapshot in the table is older than the requested `stream-from-timestamp`.
@singhpk234 I have not stepped through the code to be sure. Is my theory
possible?
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