pvary commented on code in PR #10331:
URL: https://github.com/apache/iceberg/pull/10331#discussion_r1599612377


##########
flink/v1.19/flink/src/main/java/org/apache/iceberg/flink/sink/shuffle/StatisticsType.java:
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@@ -0,0 +1,55 @@
+/*
+ * 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.iceberg.flink.sink.shuffle;
+
+/**
+ * Range distribution requires gathering statistics on the sort keys to 
determine proper range
+ * boundaries to distribute/cluster rows before writer operators.
+ */
+public enum StatisticsType {
+  /**
+   * Tracks the data statistics as {@code Map<SortKey, Long>} frequency. It 
works better for
+   * low-cardinality scenarios (like country, event_type, etc.) where the 
cardinalities are in
+   * hundreds or thousands.
+   *
+   * <ul>
+   *   <li>Pro: accurate measurement on the statistics/weight of every key.
+   *   <li>Con: memory footprint can be large if the key cardinality is high.
+   * </ul>
+   */
+  Map,
+
+  /**
+   * Sample the sort keys via reservoir sampling. Then split the range 
partitions via range bounds
+   * from sampled values. It works better for high-cardinality scenarios (like 
device_id, user_id,
+   * uuid etc.) where the cardinalities can be in millions or billions.
+   *
+   * <ul>
+   *   <li>Pro: relatively low memory footprint for high-cardinality sort keys.
+   *   <li>Con: memory footprint can be large if the key cardinality is high.

Review Comment:
   nit: fix the comment pls.



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