Poorvankbhatia commented on code in PR #6:
URL: 
https://github.com/apache/flink-connector-redis-streams/pull/6#discussion_r3165701359


##########
flink-connector-redis-streams/src/main/java/org/apache/flink/connector/redis/streams/source/RedisStreamsDeserializationSchema.java:
##########
@@ -0,0 +1,35 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.flink.connector.redis.streams.source;
+
+import org.apache.flink.annotation.PublicEvolving;
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+
+import java.io.Serializable;
+import java.util.Map;
+
+/** Converts a Redis Stream entry into a record of type {@code T}. */
+@PublicEvolving
+public interface RedisStreamsDeserializationSchema<T> extends Serializable {
+
+    /** Returning {@code null} drops the record (still ACKed). */
+    T deserialize(String streamKey, String entryId, Map<String, String> 
fields) throws Exception;

Review Comment:
   Single T return makes every Redis entry to exactly one downstream record. 
   
   Plus, most deserializers only care about fields. If a future field needs to 
be exposed, the signature has to change.
   So, it's better to have a wrapper like `RedisStreamsRecord`.
   
   Also, IMO, we should switch to void `deserialize(record, Collector<T> out)`, 
same as Kafka's pattern — so users can emit zero (filter), one, or many (split 
a JSON array entry into N sub-events). wdyt?
   
   



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