HashDistributionSortedTableSpec:
+ See https://iceberg.apache.org/docs/1.6.0/spark-writes/#writing-distribution-modes 
Using write.distribution-mode
- should create the appropriate number of Iceberg files
  + Given a table that has a distribution mode of 
hash
and is created with:
CREATE TABLE polaris.my_namespace.HashDistributionSortedTableSpec (
  id int,
  label String,
  partitionKey long,
  date Date,
  timestamp Timestamp
) USING iceberg TBLPROPERTIES (
  'format-version' = '2',
  'write.spark.fanout.enabled' = 'true',
  'write.distribution-mode' = 'hash',
  'sort-order' = 'partitionKey ASC NULLS FIRST',
  'spark.sql.adaptive.advisoryPartitionSizeInBytes' = '1073741824',
  'write.spark.advisory-partition-size-bytes' = '1073741824',
  'write.target-file-size-bytes' = '1073741824'
) PARTITIONED BY (partitionKey); 
  + And a query plan that looks like:
== Optimized Logical Plan ==
Repartition 6, true, Statistics(sizeInBytes=6.3 MiB)
+- Project [id#1453, partitionKey#1455L, date#1456, timestamp#1457, concat(cast(otherId#1471L as string), xxx) AS label#1490], Statistics(sizeInBytes=6.3 MiB)
   +- Join Inner, (partitionKey#1455L = otherId#1471L), Statistics(sizeInBytes=4.9 MiB)
      :- LocalRelation [id#1453, partitionKey#1455L, date#1456, timestamp#1457], Statistics(sizeInBytes=640.0 B, rowCount=20)
      +- Project [value#1468L AS otherId#1471L], Statistics(sizeInBytes=7.8 KiB)
         +- SerializeFromObject [input[0, bigint, false] AS value#1468L], Statistics(sizeInBytes=7.8 KiB)
            +- MapElements uk.co.odinconsultants.iceberg.distributions.AbstractWriteDistributionSpec$$Lambda$5586/0x0000000802566990@2b704646, class java.lang.Long, [StructField(value,LongType,true)], obj#1467: bigint, Statistics(sizeInBytes=7.8 KiB)
               +- DeserializeToObject staticinvoke(class java.lang.Long, ObjectType(class java.lang.Long), valueOf, id#1463L, true, false, true), obj#1466: java.lang.Long, Statistics(sizeInBytes=7.8 KiB)
                  +- Range (0, 1000, step=1, splits=Some(4)), Statistics(sizeInBytes=7.8 KiB, rowCount=1.00E+3)

== Physical Plan ==
AdaptiveSparkPlan isFinalPlan=false
+- Exchange RoundRobinPartitioning(6), REPARTITION_BY_NUM, [plan_id=3047]
   +- Project [id#1453, partitionKey#1455L, date#1456, timestamp#1457, concat(cast(otherId#1471L as string), xxx) AS label#1490]
      +- BroadcastHashJoin [partitionKey#1455L], [otherId#1471L], Inner, BuildLeft, false
         :- BroadcastExchange HashedRelationBroadcastMode(List(input[1, bigint, false]),false), [plan_id=3044]
         :  +- LocalTableScan [id#1453, partitionKey#1455L, date#1456, timestamp#1457]
         +- Project [value#1468L AS otherId#1471L]
            +- SerializeFromObject [input[0, bigint, false] AS value#1468L]
               +- MapElements uk.co.odinconsultants.iceberg.distributions.AbstractWriteDistributionSpec$$Lambda$5586/0x0000000802566990@2b704646, obj#1467: bigint
                  +- DeserializeToObject staticinvoke(class java.lang.Long, ObjectType(class java.lang.Long), valueOf, id#1463L, true, false, true), obj#1466: java.lang.Long
                     +- Range (0, 1000, step=1, splits=4)


 
  + And it has 20 rows over 5 data file(s) when writing with 4 executor threads 
  + When we add another 20 rows of the same data that is logically distributed over 5 partition(s) 
  + Then there are now 5 more data files 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +  
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +