xushiyan commented on code in PR #7039:
URL: https://github.com/apache/hudi/pull/7039#discussion_r1016732662
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hudi-common/src/main/java/org/apache/hudi/common/util/CommitUtils.java:
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@@ -44,6 +46,28 @@ public class CommitUtils {
private static final Logger LOG = LogManager.getLogger(CommitUtils.class);
private static final String NULL_SCHEMA_STR =
Schema.create(Schema.Type.NULL).toString();
+ public static transient ConcurrentHashMap<String, List<Integer>>
PERSISTED_RDD_IDS = new ConcurrentHashMap();
Review Comment:
this tightly couples with spark specific logic, and interacting with
spark-internal logic is at this layer is my major concern. And not in favor of
maintaining a global state for distributed processing. Can we try tackling this
within spark client itself? from high-level, we basically want to track the
persisted RDDs' ids and filter the RDDs by the tracked ids when unpersisting.
all these can happen within a client's lifecycle so theoretically this can be
encapsulated well. just to throw some ideas, haven't verified it by checking
the code myself
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