HeartSaVioR commented on a change in pull request #26108: [SPARK-26154][SS]
Streaming left/right outer join should not return outer nulls for already
matched rows
URL: https://github.com/apache/spark/pull/26108#discussion_r339282692
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/state/SymmetricHashJoinStateManager.scala
##########
@@ -435,9 +541,10 @@ class SymmetricHashJoinStateManager(
}
/** Put new value for key at the given index */
- def put(key: UnsafeRow, valueIndex: Long, value: UnsafeRow): Unit = {
+ def put(key: UnsafeRow, valueIndex: Long, value: UnsafeRow, matched:
Boolean): Unit = {
val keyWithIndex = keyWithIndexRow(key, valueIndex)
- stateStore.put(keyWithIndex, value)
+ val valueWithMatched = valueRowConverter.convertToValueRow(value,
matched)
Review comment:
Even we write v2 data here, we only update part of state instead of full
rewrite of state. It will leave v1 / v2 data co-exist and make state store not
possible to read the entire rows.
Individual row doesn't have schema information. Actually we don't even have
schema information for state store as well so we would encounter undefined
behavior if we do such unsafe thing. SPARK-27237 (#24173) proposes to introduce
schema information per state (not per row) and fail the query if schema is not
compatible.
We can still rewrite the state entirely in a batch query (cannot be online
modification) - please refer the README of
https://github.com/HeartSaVioR/spark-state-tools. I've already implemented the
migration of v1 to v2 for streaming aggregation / flatMapGroupsWithState, and I
may try to implement this migration as well. I'm also proposing the project as
a part of Apache Spark, but not as it is - I'm proposing batch data source for
"state" first (SPARK-28190), and once we adopt it, we could also consider to
have some tools for helping migration. Flink recently added the state API.
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