singhpk234 commented on code in PR #13459:
URL: https://github.com/apache/iceberg/pull/13459#discussion_r2183779315
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spark/v3.5/spark/src/main/java/org/apache/iceberg/spark/actions/RewriteTablePathSparkAction.java:
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@@ -312,22 +316,24 @@ private String rebuildMetadata() {
}
private String saveFileList(Set<Pair<String, String>> filesToMove) {
- List<Tuple2<String, String>> fileList =
- filesToMove.stream()
- .map(p -> Tuple2.apply(p.first(), p.second()))
- .collect(Collectors.toList());
- Dataset<Tuple2<String, String>> fileListDataset =
- spark().createDataset(fileList, Encoders.tuple(Encoders.STRING(),
Encoders.STRING()));
String fileListPath = stagingDir + RESULT_LOCATION;
- fileListDataset
- .repartition(1)
- .write()
- .mode(SaveMode.Overwrite)
- .format("csv")
- .save(fileListPath);
+ OutputFile fileList = table.io().newOutputFile(fileListPath);
Review Comment:
[doubt] staging location default value is table metadata path, but can be
set to anything ?
if thats the case :
1. what if table's fileIO didn't had the credentials to write to staging
directory but spark did, would this cause failures ?
2. when we are using the local disk to write this, but tables file IO was
pointing to object store ? would now that workloads fail ?
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