stevenzwu commented on a change in pull request #2064:
URL: https://github.com/apache/iceberg/pull/2064#discussion_r559716019
##########
File path: flink/src/main/java/org/apache/iceberg/flink/sink/FlinkSink.java
##########
@@ -209,7 +224,16 @@ public Builder equalityFieldColumns(List<String> columns) {
}
}
- IcebergStreamWriter<RowData> streamWriter = createStreamWriter(table,
tableSchema, equalityFieldIds);
+ // Convert the flink requested table schema to flink row type.
+ RowType flinkRowType = toFlinkRowType(table.schema(), tableSchema);
+
+ // Shuffle by partition key if possible.
+ if (shouldShuffleByPartition(table.properties()) &&
!table.spec().isUnpartitioned()) {
+ rowDataInput = rowDataInput.keyBy(new
PartitionKeySelector(table.spec(), table.schema(), flinkRowType));
Review comment:
Hashing over very large cardinality (like `user_id`) is fine. But I
should caution about `keyBy` over partition key which has relatively small
cardinality (like `bucket(user_id)`). It can get pretty uneven distribution.
```
{0=19, 1=62, 2=169, 3=282, 4=364, 5=318, 6=317, 7=207, 8=131, 9=60, 10=37,
11=15, 12=14, 13=4, 14=1}
```
Here is the sample code.
```java
@Test
public void testKeyBy() {
final int maxParallelism = 4000;
final int numberOfTasks = 2000;
final int numberOfBuckets = 10000;
final Integer[] assignment = new Integer[2000];
for (int i = 0; i < numberOfTasks; ++i) {
assignment[i] = 0;
}
for (int i = 0; i < numberOfBuckets; ++i) {
final String key = "date=20210119/bucket=" + i;
final int assignedTask =
KeyGroupRangeAssignment.assignKeyToParallelOperator(
key, maxParallelism, numberOfTasks);
assignment[assignedTask] += 1;
}
final Map<Integer, Long> assignmentStats =
Lists.newArrayList(assignment).stream()
.collect(Collectors.groupingBy(Function.identity(),
Collectors.counting()));
System.out.println(assignmentStats);
}
```
To avoid this problem, we have to write a custom partitioner that directly
map bucket id to the subtask. The custom partitioner can be passed into
`DataStream#partitionCustom()`.
```java
static class BucketPartitioner implements Partitioner<Integer> {
@Override
public int partition(Integer key, int numPartitions) {
return key % numPartitions;
}
}
```
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