aokolnychyi commented on code in PR #9050:
URL: https://github.com/apache/iceberg/pull/9050#discussion_r1401275467
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spark/v3.4/spark/src/main/java/org/apache/iceberg/spark/source/SparkWrite.java:
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@@ -390,7 +390,7 @@ private Expression conflictDetectionFilter() {
filter = Expressions.and(filter, expr);
}
- return filter;
+ return SERIALIZABLE == isolationLevel ? Expressions.alwaysTrue() :
filter;
Review Comment:
I spent a bit more time thinking about this and I am not fully convinced
using `true` as the conflict detection filter is the right approach, while I
admit it works in the given example. The whole idea of the conflict detection
filter is to control what is considered a serializable action against the
target table (not the transaction as a whole) if there are concurrent changes
to that table. In case of MERGE, we are dealing with a transaction that reads
from multiple tables, so that transaction can only be serializable if we have
control over both sides and can validate concurrent changes. Unfortunately, we
don't have that in Spark right now as there is no transaction API.
In other words, the MERGE breaks serializability not because the conflict
detection condition is wrong but because we have no way to validate concurrent
changes to the other side.
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