szehon-ho commented on code in PR #17707:
URL: https://github.com/apache/iceberg/pull/17707#discussion_r3884281023


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docs/docs/spark-procedures.md:
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@@ -410,6 +410,7 @@ Iceberg can compact data files in parallel using Spark with 
the `rewriteDataFile
 | `min-input-files` | 5 | Any file group with this number of files or more 
will be rewritten regardless of other criteria (the file group should have at 
least two files) |
 | `rewrite-all` | false | Force rewriting of all provided files overriding 
other options |
 | `max-file-group-size-bytes` | 107374182400 (100GB) | Largest amount of data 
that should be rewritten in a single file group. The entire rewrite operation 
is broken down into pieces based on partitioning and within partitions based on 
size into file-groups.  This helps with breaking down the rewriting of very 
large partitions which may not be rewritable otherwise due to the resource 
constraints of the cluster. |
+| `max-file-group-input-files` | Long.MAX_VALUE (unlimited) | Largest number 
of input files that should be rewritten in a single file group. If set below 
`min-input-files`, no group can reach `min-input-files`, so the file-count 
rewrite trigger never fires; groups are then rewritten only when they meet the 
size thresholds or contain files exceeding the delete-file/delete-ratio 
thresholds. |

Review Comment:
   Qualify this behavior with `rewrite-all=false`, here and on line 553. When 
`rewrite-all=true`, `SizeBasedFileRewritePlanner.planFileGroups` bypasses the 
size/delete group filters, so the statement that groups are rewritten “only 
when” those thresholds are met is not true.



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